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Sample records for robust adaptive interval

  1. Robust adaptive control for interval time-delay systems

    Institute of Scientific and Technical Information of China (English)

    Yizhong WANG; Huaguang ZHANG; Jun YANG

    2006-01-01

    This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.

  2. Robust misinterpretation of confidence intervals

    NARCIS (Netherlands)

    Hoekstra, Rink; Morey, Richard; Rouder, Jeffrey N.; Wagenmakers, Eric-Jan

    2014-01-01

    Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more

  3. Robust misinterpretation of confidence intervals

    NARCIS (Netherlands)

    Hoekstra, R.; Morey, R.D.; Rouder, J.N.; Wagenmakers, E.-J.

    2014-01-01

    Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more

  4. Robust Adaptive Control.

    Science.gov (United States)

    1985-09-19

    13.2 3.6. 14.0. 1.8. 11111.52 *.6 L 3 n1 i erated ~~~m nc. AFOSR-TR- 798 s AD-A 161 349 ROBUST ADAPTIVE CONTROL * FINAL REPORT PREPARED BY: R~ OBERT L... Centre Block Computes the Norm of the [1I] Solo, V., "Time Series Recursions and Stochastc Regressors. The Rematning Elemerts Imple- Approximation

  5. Robust misinterpretation of confidence intervals.

    Science.gov (United States)

    Hoekstra, Rink; Morey, Richard D; Rouder, Jeffrey N; Wagenmakers, Eric-Jan

    2014-10-01

    Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more useful alternative to NHST, and their use is strongly encouraged in the APA Manual. Nevertheless, little is known about how researchers interpret CIs. In this study, 120 researchers and 442 students-all in the field of psychology-were asked to assess the truth value of six particular statements involving different interpretations of a CI. Although all six statements were false, both researchers and students endorsed, on average, more than three statements, indicating a gross misunderstanding of CIs. Self-declared experience with statistics was not related to researchers' performance, and, even more surprisingly, researchers hardly outperformed the students, even though the students had not received any education on statistical inference whatsoever. Our findings suggest that many researchers do not know the correct interpretation of a CI. The misunderstandings surrounding p-values and CIs are particularly unfortunate because they constitute the main tools by which psychologists draw conclusions from data.

  6. Adaptive Robust Variable Selection

    CERN Document Server

    Fan, Jianqing; Barut, Emre

    2012-01-01

    Heavy-tailed high-dimensional data are commonly encountered in various scientific fields and pose great challenges to modern statistical analysis. A natural procedure to address this problem is to use penalized least absolute deviation (LAD) method with weighted $L_1$-penalty, called weighted robust Lasso (WR-Lasso), in which weights are introduced to ameliorate the bias problem induced by the $L_1$-penalty. In the ultra-high dimensional setting, where the dimensionality can grow exponentially with the sample size, we investigate the model selection oracle property and establish the asymptotic normality of the WR-Lasso. We show that only mild conditions on the model error distribution are needed. Our theoretical results also reveal that adaptive choice of the weight vector is essential for the WR-Lasso to enjoy these nice asymptotic properties. To make the WR-Lasso practically feasible, we propose a two-step procedure, called adaptive robust Lasso (AR-Lasso), in which the weight vector in the second step is c...

  7. Adaptively robust filtering with classified adaptive factors

    Institute of Scientific and Technical Information of China (English)

    CUI Xianqiang; YANG Yuanxi

    2006-01-01

    The key problems in applying the adaptively robust filtering to navigation are to establish an equivalent weight matrix for the measurements and a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information to the state parameter estimates. In this paper, an adaptively robust filtering with classified adaptive factors was proposed, based on the principles of the adaptively robust filtering and bi-factor robust estimation for correlated observations. According to the constant velocity model of Kalman filtering, the state parameter vector was divided into two groups, namely position and velocity. The estimator of the adaptively robust filtering with classified adaptive factors was derived, and the calculation expressions of the classified adaptive factors were presented. Test results show that the adaptively robust filtering with classified adaptive factors is not only robust in controlling the measurement outliers and the kinematic state disturbing but also reasonable in balancing the contributions of the predicted position and velocity, respectively, and its filtering accuracy is superior to the adaptively robust filter with single adaptive factor based on the discrepancy of the predicted position or the predicted velocity.

  8. Robust stability of interval parameter matrices

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This note is devoted to the problem of robust stability of interval parameter matrices. Based on some basic facts relating the H∞ norm of a transfer function to the Riccati matrix inequality and Hamilton matrix, several test conditions with parameter perturbation bounds are obtained.

  9. A robust adaptive robot controller

    NARCIS (Netherlands)

    Berghuis, Harry; Ortega, Romeo; Nijmeijer, Henk

    1993-01-01

    A globally convergent adaptive control scheme for robot motion control with the following features is proposed. First, the adaptation law possesses enhanced robustness with respect to noisy velocity measurements. Second, the controller does not require the inclusion of high gain loops that may excit

  10. A robust adaptive robot controller

    OpenAIRE

    1993-01-01

    A globally convergent adaptive control scheme for robot motion control with the following features is proposed. First, the adaptation law possesses enhanced robustness with respect to noisy velocity measurements. Second, the controller does not require the inclusion of high gain loops that may excite the unmodeled dynamics and amplify the noise level. Third, we derive for the unknown parameter design a relationship between compensator gains and closed-loop convergence rates that is independen...

  11. Robust Adaptive Quantum Phase Estimation

    CERN Document Server

    Roy, Shibdas; Huntington, Elanor H

    2014-01-01

    Quantum parameter estimation is central to many fields such as quantum computation, communications and metrology. Optimal estimation theory has been instrumental in achieving the best accuracy in quantum parameter estimation, which is possible when we have very precise knowledge of and control over the model. However, uncertainties in key parameters underlying the system are unavoidable and may impact the quality of the estimate. We show here how quantum optical phase estimation of a squeezed state of light exhibits improvement when using a robust fixed-interval smoother designed with uncertainties explicitly introduced in parameters underlying the phase noise.

  12. Probabilistic robust stabilization of fractional order systems with interval uncertainty.

    Science.gov (United States)

    Alagoz, Baris Baykant; Yeroglu, Celaleddin; Senol, Bilal; Ates, Abdullah

    2015-07-01

    This study investigates effects of fractional order perturbation on the robust stability of linear time invariant systems with interval uncertainty. For this propose, a probabilistic stability analysis method based on characteristic root region accommodation in the first Riemann sheet is developed for interval systems. Stability probability distribution is calculated with respect to value of fractional order. Thus, we can figure out the fractional order interval, which makes the system robust stable. Moreover, the dependence of robust stability on the fractional order perturbation is analyzed by calculating the order sensitivity of characteristic polynomials. This probabilistic approach is also used to develop a robust stabilization algorithm based on parametric perturbation strategy. We present numerical examples demonstrating utilization of stability probability distribution in robust stabilization problems of interval uncertain systems.

  13. Toward robust adaptive radiation therapy strategies.

    Science.gov (United States)

    Böck, Michelle; Eriksson, Kjell; Forsgren, Anders; Hårdemark, Björn

    2017-06-01

    To set up a framework combining robust treatment planning with adaptive re-optimization in order to maintain high treatment quality, to respond to interfractional geometric variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. The authors propose robust adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan applied during the first fractions should be able to handle anticipated systematic and random errors. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errors on the delivered dose distribution is evaluated. For a patient having received a dose that does not satisfy specified plan quality criteria, the plan is re-optimized based on these individually measured errors. The re-optimized plan is then applied during subsequent fractions until a new scheduled adaptation becomes necessary. In this study, three different adaptive strategies are introduced and investigated. (a) In the first adaptive strategy, the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust re-optimization. (b) In the second strategy, the degree of conservativeness is adapted in response to the measured dose delivery errors. (c) In the third strategy, the uncertainty margins around the target are recalculated based on the measured errors. The simulated treatments are subjected to systematic and random errors that are either similar to the anticipated errors or unpredictably larger in order to critically evaluate the performance of these three adaptive strategies. According to the simulations, robustly optimized treatment plans provide sufficient treatment quality for those treatment error scenarios similar to the anticipated error scenarios. Moreover, combining robust planning with adaptation leads to improved organ

  14. Computation of robustly stabilizing PID controllers for interval systems.

    Science.gov (United States)

    Matušů, Radek; Prokop, Roman

    2016-01-01

    The paper is focused on the computation of all possible robustly stabilizing Proportional-Integral-Derivative (PID) controllers for plants with interval uncertainty. The main idea of the proposed method is based on Tan's (et al.) technique for calculation of (nominally) stabilizing PI and PID controllers or robustly stabilizing PI controllers by means of plotting the stability boundary locus in either P-I plane or P-I-D space. Refinement of the existing method by consideration of 16 segment plants instead of 16 Kharitonov plants provides an elegant and efficient tool for finding all robustly stabilizing PID controllers for an interval system. The validity and relatively effortless application of presented theoretical concepts are demonstrated through a computation and simulation example in which the uncertain mathematical model of an experimental oblique wing aircraft is robustly stabilized.

  15. A Novel Robust Adaptive Fuzzy Controller

    Institute of Scientific and Technical Information of China (English)

    LIU Xiao-hua; WANG Xiu-hong; FEN En-min

    2002-01-01

    For a class of continuous-time nonlinear system, a novel robust adaptive fuzzy controller is proposed by using of Lyapunov method. It is proven that the control algorithm is globally stable, the output tracking-error can convergence to a domain of zero under the assumptions. As a result, the system controlled has stronger robustness for disturbance and modeling error.

  16. A robust adaptive controller for robot manipulators

    NARCIS (Netherlands)

    Berghuis, Harry; Ortega, Romeo; Nijmeijer, Henk

    1992-01-01

    The authors propose a globally convergent adaptive control scheme for robot motion control with the following features: first, the adaptation law processes enhanced robustness with respect to noisy velocity measurements; secondly, the controller does not require the inclusion of high-gain loops that

  17. Robust adaptive beamforming for MIMO monopulse radar

    Science.gov (United States)

    Rowe, William; Ström, Marie; Li, Jian; Stoica, Petre

    2013-05-01

    Researchers have recently proposed a widely separated multiple-input multiple-output (MIMO) radar using monopulse angle estimation techniques for target tracking. The widely separated antennas provide improved tracking performance by mitigating complex target radar cross-section fades and angle scintillation. An adaptive array is necessary in this paradigm because the direct path from any transmitter could act as a jammer at a receiver. When the target-free covariance matrix is not available, it is critical to include robustness into the adaptive beamformer weights. This work explores methods of robust adaptive monopulse beamforming techniques for MIMO tracking radar.

  18. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    Science.gov (United States)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  19. Robust Adaptable Video Copy Detection

    DEFF Research Database (Denmark)

    Assent, Ira; Kremer, Hardy

    2009-01-01

    Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change...... in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models....

  20. Robust Adaptable Video Copy Detection

    DEFF Research Database (Denmark)

    Assent, Ira; Kremer, Hardy

    2009-01-01

    Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change...... in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models....

  1. A robust adaptive controller for robot manipulators

    OpenAIRE

    1992-01-01

    The authors propose a globally convergent adaptive control scheme for robot motion control with the following features: first, the adaptation law processes enhanced robustness with respect to noisy velocity measurements; secondly, the controller does not require the inclusion of high-gain loops that may excite the unmodeled dynamics and amplify the noise level; thirdly the authors derive for the known parameter design a relationship between compensator gains and closed-loop convergence rates ...

  2. Robust and Adaptive Control With Aerospace Applications

    CERN Document Server

    Lavretsky, Eugene

    2013-01-01

    Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems.  The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: ·         case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; ·         detailed background material for each chapter to motivate theoretical developments; ·         realistic examples and simulation data illustrating key features ...

  3. Robust Adaptive Control of Hypnosis During Anesthesia

    Science.gov (United States)

    2007-11-02

    1 of 4 ROBUST ADAPTIVE CONTROL OF HYPNOSIS DURING ANESTHESIA Pascal Grieder1, Andrea Gentilini1, Manfred Morari1, Thomas W. Schnider2 1ETH Zentrum...A closed-loop controller for hypnosis was designed and validated on humans at our laboratory. The controller aims at regulat- ing the Bispectral Index...BIS) - a surro- gate measure of hypnosis derived from the electroencephalogram of the patient - with the volatile anesthetic isoflurane administered

  4. Real Time & Power Efficient Adaptive - Robust Control

    Science.gov (United States)

    Ioan Gliga, Lavinius; Constantin Mihai, Cosmin; Lupu, Ciprian; Popescu, Dumitru

    2017-01-01

    A design procedure for a control system suited for dynamic variable processes is presented in this paper. The proposed adaptive - robust control strategy considers both adaptive control advantages and robust control benefits. It estimates the degradation of the system’s performances due to the dynamic variation in the process and it then utilizes it to determine when the system must be adapted with a redesign of the robust controller. A single integral criterion is used for the identification of the process, and for the design of the control algorithm, which is expressed in direct form, through a cost function defined in the space of the parameters of both the process and the controller. For the minimization of this nonlinear function, an adequate mathematical programming minimization method is used. The theoretical approach presented in this paper was validated for a closed loop control system, simulated in an application developed in C. Because of the reduced number of operations, this method is suitable for implementation on fast processes. Due to its effectiveness, it increases the idle time of the CPU, thereby saving electrical energy.

  5. Robustness of muscle synergies during visuomotor adaptation

    Directory of Open Access Journals (Sweden)

    Reinhard eGentner

    2013-09-01

    Full Text Available During visuomotor adaptation a novel mapping between visual targets and motor commands is gradually acquired. How muscle activation patterns are affected by this process is an open question. We tested whether the structure of muscle synergies is preserved during adaptation to a visuomotor rotation. Eight subjects applied targeted isometric forces on a handle instrumented with a force transducer while electromyographic (EMG activity was recorded from 13 shoulder and elbow muscles. The recorded forces were mapped into horizontal displacements of a virtual sphere with simulated mass, elasticity, and damping. The task consisted of moving the sphere to a target at one of eight equally spaced directions. Subjects performed three baseline blocks of 32 trials, followed by six blocks with a 45° CW rotation applied to the planar force, and finally three wash-out blocks without the perturbation. The sphere position at 100 ms after movement onset revealed significant directional error at the beginning of the rotation, a gradual learning in subsequent blocks, and aftereffects at the beginning of the wash-out. The change in initial force direction was closely related to the change in directional tuning of the initial EMG activity of most muscles. Throughout the experiment muscle synergies extracted using a non-negative matrix factorization algorithm from the muscle patterns recorded during the baseline blocks could reconstruct the muscle patterns of all other blocks with an accuracy significantly higher than chance indicating structural robustness. In addition, the synergies extracted from individual blocks remained similar to the baseline synergies throughout the experiment. Thus synergy structure is robust during visuomotor adaptation suggesting that changes in muscle patterns are obtained by rotating the directional tuning of the synergy recruitment.

  6. Learning adaptive metric for robust visual tracking.

    Science.gov (United States)

    Jiang, Nan; Liu, Wenyu; Wu, Ying

    2011-08-01

    Matching the visual appearances of the target over consecutive image frames is the most critical issue in video-based object tracking. Choosing an appropriate distance metric for matching determines its accuracy and robustness, and thus significantly influences the tracking performance. Most existing tracking methods employ fixed pre-specified distance metrics. However, this simple treatment is problematic and limited in practice, because a pre-specified metric does not likely to guarantee the closest match to be the true target of interest. This paper presents a new tracking approach that incorporates adaptive metric learning into the framework of visual object tracking. Collecting a set of supervised training samples on-the-fly in the observed video, this new approach automatically learns the optimal distance metric for more accurate matching. The design of the learned metric ensures that the closest match is very likely to be the true target of interest based on the supervised training. Such a learned metric is discriminative and adaptive. This paper substantializes this new approach in a solid case study of adaptive-metric differential tracking, and obtains a closed-form analytical solution to motion estimation and visual tracking. Moreover, this paper extends the basic linear distance metric learning method to a more powerful nonlinear kernel metric learning method. Extensive experiments validate the effectiveness of the proposed approach, and demonstrate the improved performance of the proposed new tracking method.

  7. Robust Absolute Stability of General Interval Lur'e Type Nonlinear Control Systems

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In this paper, Lyapunov function method isused to study the robust absolute stability of general interval Lur'e type nonlinear control systems. As a result, algebraically sufficient conditions with interval matrix inequality form are obtained for the general interval Lur'e type nonlinear control systems, thus the relationship between the stability of symmetrical interval matrix and the robust absolute stability of general interval Lur'e type nonlinear control systems is established.

  8. Robustness and Adaptiveness Analysis of Future Fleets

    CERN Document Server

    Wesolkowski, Slawomir; Whitacre, James M; Bender, Axel; Abbass, Hussein

    2009-01-01

    Making decisions about the structure of a future military fleet is a challenging task. Several issues need to be considered such as the existence of multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future might hold. It is uncertain what future events might be encountered; how fleet design decisions will influence and shape the future; and how present and future decision makers will act based on available information, their personal biases regarding the importance of different objectives, and their economic preferences. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different classes of uncertainty are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present clear risks to the fleet. We call this the analysis of a fleet's strate...

  9. Robust Inter-beat Interval Estimation in Cardiac Vibration Signals

    NARCIS (Netherlands)

    Brueser, C.; Winter, S.; Leonhardt, S.

    2013-01-01

    Reliable and accurate estimation of instantaneous frequencies of physiological rhythms, such as heart rate, is critical for many healthcare applications. Robust estimation is especially challenging when novel unobtrusive sensors are used for continuous health monitoring in uncontrolled environments,

  10. Function approximation using adaptive and overlapping intervals

    Energy Technology Data Exchange (ETDEWEB)

    Patil, R.B.

    1995-05-01

    A problem common to many disciplines is to approximate a function given only the values of the function at various points in input variable space. A method is proposed for approximating a function of several to one variable. The model takes the form of weighted averaging of overlapping basis functions defined over intervals. The number of such basis functions and their parameters (widths and centers) are automatically determined using given training data and a learning algorithm. The proposed algorithm can be seen as placing a nonuniform multidimensional grid in the input domain with overlapping cells. The non-uniformity and overlap of the cells is achieved by a learning algorithm to optimize a given objective function. This approach is motivated by the fuzzy modeling approach and a learning algorithms used for clustering and classification in pattern recognition. The basics of why and how the approach works are given. Few examples of nonlinear regression and classification are modeled. The relationship between the proposed technique, radial basis neural networks, kernel regression, probabilistic neural networks, and fuzzy modeling is explained. Finally advantages and disadvantages are discussed.

  11. Low overhead and nonlinear-tolerant adaptive zero-guard-interval CO-OFDM.

    Science.gov (United States)

    Wang, Wei; Zhuge, Qunbi; Gao, Yuliang; Qiu, Meng; Morsy-Osman, Mohamed; Chagnon, Mathieu; Xu, Xian; Plant, David V

    2014-07-28

    We propose an adaptive channel estimation (CE) method for zero-guard-interval (ZGI) coherent optical (CO)-OFDM systems, and demonstrate its performance in a single channel 28 Gbaud polarization-division multiplexed ZGI CO-OFDM experiment with only 1% OFDM processing overhead. We systematically investigate its robustness against various transmission impairments including residual chromatic dispersion, polarization-mode dispersion, state of polarization rotation, sampling frequency offset and fiber nonlinearity. Both experimental and numerical results show that the adaptive CE-aided ZGI CO-OFDM is highly robust against these transmission impairments in fiber optical transmission systems.

  12. A robust adaptive load frequency control for micro-grids.

    Science.gov (United States)

    Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede; Davari, Pooya; Dragicevic, Tomislav

    2016-11-01

    The goal of this study is to introduce a novel robust load frequency control (LFC) strategy for micro-grid(s) (MG(s)) in islanded mode operation. Admittedly, power generators in MG(s) cannot supply steady electric power output and sometimes cause unbalance between supply and demand. Battery energy storage system (BESS) is one of the effective solutions to these problems. Due to the high cost of the BESS, a new idea of Vehicle-to-Grid (V2G) is that a battery of Electric-Vehicle (EV) can be applied as a tantamount large-scale BESS in MG(s). As a result, a new robust control strategy for an islanded micro-grid (MG) is introduced that can consider electric vehicles׳ (EV(s)) effect. Moreover, in this paper, a new combination of the General Type II Fuzzy Logic Sets (GT2FLS) and the Modified Harmony Search Algorithm (MHSA) technique is applied for adaptive tuning of proportional-integral (PI) controller. Implementing General Type II Fuzzy Systems is computationally expensive. However, using a recently introduced α-plane representation, GT2FLS can be seen as a composition of several Interval Type II Fuzzy Logic Systems (IT2FLS) with a corresponding level of α for each. Real-data from an offshore wind farm in Sweden and solar radiation data in Aberdeen (United Kingdom) was used in order to examine the performance of the proposed novel controller. A comparison is made between the achieved results of Optimal Fuzzy-PI (OFPI) controller and those of Optimal Interval Type II Fuzzy-PI (IT2FPI) controller, which are of most recent advances in the area at hand. The Simulation results prove the successfulness and effectiveness of the proposed controller.

  13. Synthetically adaptive robust filtering for satellite orbit determination

    Institute of Scientific and Technical Information of China (English)

    YANG; Yuanxi

    2004-01-01

    The quality of the satellite orbit determination is rested on the knowledge of perturbing forces acting on the satellite and stochastic properties of the observations, and the ability of controlling various kinds of errors. After a brief discussion on the dynamic and geometric orbit determinations, Sage adaptive filtering and robust filtering are reviewed. A new synthetically adaptive robust filtering based on a combination of robust filtering and Sage filtering is developed. It is shown, by derivations and calculations, that the synthetically adaptive robust filtering for orbit determination is not only robust but also simple in calculation. It controls the effects of the outliers of tracking observations and the satellite dynamical disturbance on the parameter estimates of the satellite orbit.

  14. Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

    Directory of Open Access Journals (Sweden)

    Zongze Wu

    2015-10-01

    Full Text Available The maximum correntropy criterion (MCC has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error (MSE criterion, the proposed algorithm can achieve better convergence performance especially in the presence of impulsive non-Gaussian (e.g., α-stable noises. Additionally, some theoretical results concerning the convergence behavior are also obtained. Simulation examples are presented to confirm the superior performance of the new algorithm.

  15. Nonlinear Direct Robust Adaptive Control Using Lyapunov Method

    Directory of Open Access Journals (Sweden)

    Chunbo Xiu

    2013-07-01

    Full Text Available    The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.

  16. Robust Adaptive Control of Multivariable Nonlinear Systems

    Science.gov (United States)

    2011-03-28

    IEEE Transactions on Automatic Control , 42(9): 1200-1221, 1997. 6. D. Li, N. Hovakimyan...limitations of performance,” IEEE Transactions on Automatic Control , vol. 52, no. 7, pp. 1604–1615, 2008. 8. X. Wang, N. Hovakimyan, 1L Adaptive...550-564, 2010. 5. C. Cao, N. Hovakimyan, Stability Margins of 1L Adaptive Control Architecture, IEEE Transactions on Automatic Control , vol. 55,

  17. Robust, Adaptive Radar Detection and Estimation

    Science.gov (United States)

    2015-07-21

    targets) Range of Target Dop . Freq. -99.2 Hz to 372 Hz from a single coherent processing interval from 11(= J) channels and 32(= P ) pulses. Therefore...Power 40 dB Number of Targets 226 ( 200 detectable targets) Range of Target Dop . Freq. -99.2 Hz to 372 Hz value of themselves for each diagonal of

  18. A Novel Robust Interval Kalman Filter Algorithm for GPS/INS Integrated Navigation

    Directory of Open Access Journals (Sweden)

    Chen Jiang

    2016-01-01

    Full Text Available Kalman filter is widely applied in data fusion of dynamic systems under the assumption that the system and measurement noises are Gaussian distributed. In literature, the interval Kalman filter was proposed aiming at controlling the influences of the system model uncertainties. The robust Kalman filter has also been proposed to control the effects of outliers. In this paper, a new interval Kalman filter algorithm is proposed by integrating the robust estimation and the interval Kalman filter in which the system noise and the observation noise terms are considered simultaneously. The noise data reduction and the robust estimation methods are both introduced into the proposed interval Kalman filter algorithm. The new algorithm is equal to the standard Kalman filter in terms of computation, but superior for managing with outliers. The advantage of the proposed algorithm is demonstrated experimentally using the integrated navigation of Global Positioning System (GPS and the Inertial Navigation System (INS.

  19. Robust adaptive regulation without persistent excitation

    Science.gov (United States)

    Lozano-Leal, Rogelio

    1989-01-01

    A globally convergent adaptive regulator for minimum- or nonminimum-phase systems subject to bounded disturbances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least-Squares identification algorithm a with dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given.

  20. Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.

    Science.gov (United States)

    Fei, Juntao; Zhou, Jian

    2012-12-01

    In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.

  1. Adaptive Fuzzy and Robust H∞ Compensation Control for Uncertain Robot

    Directory of Open Access Journals (Sweden)

    Yuan Chen

    2013-06-01

    Full Text Available In this paper, two types of robust adaptive compensation control schemes for the trajectory tracking control of robot manipulator with uncertain dynamics are proposed. The proposed controllers incorporate the computed-torque control scheme as a nominal portion of the controller; an adaptive fuzzy control algorithm to approximate the structured uncertainties; and a nonlinear H∞ tracking control model as a feedback portion to eliminate the effects of the unstructured uncertainties and approximation errors. The validity of the robust adaptive compensation control schemes is investigated by numerical simulations of a two-link rotary robot manipulator

  2. Patterns of interval correlations in neural oscillators with adaptation

    Directory of Open Access Journals (Sweden)

    Tilo eSchwalger

    2013-11-01

    Full Text Available Neural firing is often subject to negative feedback by adaptationcurrents. These currents can induce strong correlations among the timeintervals between spikes. Here we study analytically the intervalcorrelations of a broad class of noisy neural oscillators withspike-triggered adaptation of arbitrary strength and time scale. Ourweak-noise theory provides a general relation between the correlationsand the phase-response curve (PRC of the oscillator, provesanti-correlations between neighboring intervals for adapting neuronswith type I PRC and identifies a single order parameter thatdetermines the qualitative pattern of correlations. Monotonicallydecaying or oscillating correlation structures can be related toqualitatively different voltage traces after spiking, which can beexplained by the phase plane geometry. At high firing rates, thelong-term variability of the spike train associated with thecumulative interval correlations becomes small, independent of modeldetails. Our results are verified by comparison with stochasticsimulations of the exponential, leaky, and generalizedintegrate-and-fire models with adaptation.

  3. Capacity planning for waste management systems: an interval fuzzy robust dynamic programming approach.

    Science.gov (United States)

    Nie, Xianghui; Huang, Guo H; Li, Yongping

    2009-11-01

    This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information.

  4. 2-D algebraic test for robust stability of time-delay systems with interval parameters

    Institute of Scientific and Technical Information of China (English)

    Xiao Yang

    2006-01-01

    The robust stability test of time-delay systems with interval parameters can be concluded into the robust stability of the interval quasipolynomials. It has been revealed that the robust stability of the quasipolynomials depends on that of their edge polynomials. This paper transforms the interval quasipolynomials into two-dimensional (2-D) interval polynomials (2-D s-z hybrid polynomials), proves that the robust stability of interval 2-D polynomials are sufficient for the stability of given quasipolynomials. Thus, the stability test of interval quasipolynomials can be completed in 2-D s-z domain instead of classical 1-D s domain. The 2-D s-z hybrid polynomials should have different forms under the time delay properties of given quasipolynomials. The stability test proposed by the paper constructs an edge test set from Kharitonov vertex polynomials to reduce the number of testing edge polynomials. The 2-D algebraic tests are provided for the stability test of vertex 2-D polynomials and edge 2-D polynomials family. To verify the results of the paper to be correct and valid, the simulations based on proposed results and comparison with other presented results are given.

  5. Design of the robust synchronous generator stator voltage regulator based on the interval plant model

    Directory of Open Access Journals (Sweden)

    Stojić Đorđe

    2013-01-01

    Full Text Available In this paper a novel method for the stator voltage regulator of a synchronous generator based on the interval plant mode, is presented. Namely, it is shown in the literature that, in order to design a controller for the first-order compensator, the limited number of interval plants needs to be examined. Consequently, the intervals of the plant model parameter variations used to calculate the four extreme interval plants required for the sequential PI controller design are determined. The controller is designed using frequency-domain-based techniques, while its robust performance is examined using simulation tests.

  6. Robust adaptive subspace detection in impulsive noise

    KAUST Repository

    Atitallah, Ismail Ben

    2016-09-13

    This paper addresses the design of the Adaptive Subspace Matched Filter (ASMF) detector in the presence of compound Gaussian clutters and a mismatch in the steering vector. In particular, we consider the case wherein the ASMF uses the regularized Tyler estimator (RTE) to estimate the clutter covariance matrix. Under this setting, a major question that needs to be addressed concerns the setting of the threshold and the regularization parameter. To answer this question, we consider the regime in which the number of observations used to estimate the RTE and their dimensions grow large together. Recent results from random matrix theory are then used in order to approximate the false alarm and detection probabilities by deterministic quantities. The latter are optimized in order to maximize an upper bound on the asymptotic detection probability while keeping the asymptotic false alarm probability at a fixed rate. © 2016 IEEE.

  7. Robust adaptive tracking control of robotic systems with uncertainties

    Institute of Scientific and Technical Information of China (English)

    Yaonan WANG; Jinzhu PENG; Wei SUN; Hongshan YU; Hui ZHANG

    2008-01-01

    To deal with the uncertainty factors of robotic systems,a robust adaptive tracking controller is Droposed.The knowledge of the uncertainty factors is assumed to be unidentified;the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded,immeasurable disturbances entering the System.The stability of the proposed controller is proven by the Lyapunov method.The proposed controller can easily be implemented and the stability of the closed system can be ensured;the tracking error and adaptation parameter error are uniformly ultimately bounded(UUB).Finally,some simulation examples are utilized to illustrate the control performance.

  8. Adaptive robust control of robot manipulators -- Theory and experiment

    Energy Technology Data Exchange (ETDEWEB)

    Imura, Junichi; Sugie, Toshiharu; Yoshikawa, Tsuneo (Kyoto Univ. (Japan))

    1994-10-01

    In this paper, a new adaptive robust control scheme for manipulators is proposed that overcomes the drawbacks of conventional adaptive robust control methods. The proposed controller has a simple structure by exploiting the special structure of the manipulator dynamics, and achieves the specified tracking precision without any a priori information on uncertainty. Furthermore, the feedback gain of the proposed method is almost necessary and minimum for the specified precision. To verify the advantages of the method, experimental results are shown for the trajectory control of a 2 DOF direct-drive arm.

  9. Robust adaptive matched field processing with sector eigenvector constraints

    Institute of Scientific and Technical Information of China (English)

    YANG Kunde; MA Yuanliang

    2006-01-01

    Standard adaptive beamforming or matched field processing requires accurate replica fields finely gridded over the search parameter space for localization with sidelobe control. This paper presents an Adaptive Matched Field Processing (AMFP) algo rithm, which aims at gaining robustness for the environmentai mismatch, and simultaneously reducing the real-time computational load. The new method integrates the merits of several AMFP beamformers with neighboring location constraints, environmental perturbation constraints and sector focusing constraints. The robustness and effectiveness of the suggested algorithm has been illustrated through the numerical simulation and the experimental Mediterranean benchmark shallow-water data.

  10. ADAPTIVE INTERVAL WAVELET PRECISE INTEGRATION METHOD FOR PARTIAL DIFFERENTIAL EQUATIONS

    Institute of Scientific and Technical Information of China (English)

    MEI Shu-li; LU Qi-shao; ZHANG Sen-wen; JIN Li

    2005-01-01

    The quasi-Shannon interval wavelet is constructed based on the interpolation wavelet theory, and an adaptive precise integration method, which is based on extrapolation method is presented for nonlinear ordinary differential equations (ODEs). And then, an adaptive interval wavelet precise integration method (AIWPIM) for nonlinear partial differential equations(PDEs) is proposed. The numerical results show that the computational precision of AIWPIM is higher than that of the method constructed by combining the wavelet and the 4th Runge-Kutta method, and the computational amounts of these two methods are almost equal. For convenience, the Burgers equation is taken as an example in introducing this method, which is also valid for more general cases.

  11. Adaptive interactive genetic algorithms with individual interval fitness

    Institute of Scientific and Technical Information of China (English)

    Dunwei Gong; Guangsong Guo; Li Lu; Hongmei Ma

    2008-01-01

    It is necessary to enhance the performance of interactive genetic algorithms in order to apply them to complicated optimization problems successfully. An adaptive interactive genetic algorithm with individual interval fitness is proposed in this paper in which an individual fitness is expressed by an interval. Through analyzing the fitness, information reflecting the distribution of an evolutionary population is picked up, namely, the difference of evaluating superior individuals and the difference of evaluating a population. Based on these, the adaptive probabilities of crossover and mutation operators of an individual are presented. The algorithm proposed in this paper is applied to a fashion evolutionary design system, and the results show that it can find many satisfactory solutions per generation. The achievement of the paper provides a new approach to enhance the performance of interactive genetic algorithms.

  12. Adaptive robust Kalman filtering for precise point positioning

    Science.gov (United States)

    Guo, Fei; Zhang, Xiaohong

    2014-10-01

    The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises.

  13. Histogram Equalization to Model Adaptation for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Hoirin Kim

    2010-01-01

    Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.

  14. Robust time and frequency domain estimation methods in adaptive control

    Science.gov (United States)

    Lamaire, Richard Orville

    1987-01-01

    A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

  15. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    Science.gov (United States)

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system.

  16. Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics

    Institute of Scientific and Technical Information of China (English)

    LIU Yu-sheng; CHEN Jiang; LI Xing-yuan

    2006-01-01

    Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.

  17. Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

    Institute of Scientific and Technical Information of China (English)

    Mingjun ZHANG; Huaguang ZHANG

    2006-01-01

    In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.

  18. Robust adaptive beamforming algorithm based on Bayesian approach

    Institute of Scientific and Technical Information of China (English)

    Xin SONG; Jinkuan WANG; Yinghua HAN; Han WANG

    2008-01-01

    The performance of adaptive array beamform-ing algorithms substantially degrades in practice because of a slight mismatch between actual and presumed array res-ponses to the desired signal. A novel robust adaptive beam-forming algorithm based on Bayesian approach is therefore proposed. The algorithm responds to the current envi-ronment by estimating the direction of arrival (DOA) of the actual signal from observations. Computational com-plexity of the proposed algorithm can thus be reduced com-pared with other algorithms since the recursive method is used to obtain inverse matrix. In addition, it has strong robustness to the uncertainty of actual signal DOA and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently approach the optimum. Simulation results show that the proposed algorithm is bet-ter in performance than conventional adaptive beamform-ing algorithms.

  19. Robust adaptive output feedback control of nonlinearly parameterized systems

    Institute of Scientific and Technical Information of China (English)

    LIU Yusheng; LI Xingyuan

    2007-01-01

    The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.

  20. Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.

    Science.gov (United States)

    Hu, Yi-Chung

    2014-01-01

    On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.

  1. Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms

    Science.gov (United States)

    2014-01-01

    On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets. PMID:25110755

  2. Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

    Directory of Open Access Journals (Sweden)

    Chao Huang

    2016-06-01

    Full Text Available Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

  3. Geometric computations with interval and new robust methods applications in computer graphics, GIS and computational geometry

    CERN Document Server

    Ratschek, H

    2003-01-01

    This undergraduate and postgraduate text will familiarise readers with interval arithmetic and related tools to gain reliable and validated results and logically correct decisions for a variety of geometric computations plus the means for alleviating the effects of the errors. It also considers computations on geometric point-sets, which are neither robust nor reliable in processing with standard methods. The authors provide two effective tools for obtaining correct results: (a) interval arithmetic, and (b) ESSA the new powerful algorithm which improves many geometric computations and makes th

  4. Robust Fusion of Irregularly Sampled Data Using Adaptive Normalized Convolution

    Directory of Open Access Journals (Sweden)

    Schutte Klamer

    2006-01-01

    Full Text Available We present a novel algorithm for image fusion from irregularly sampled data. The method is based on the framework of normalized convolution (NC, in which the local signal is approximated through a projection onto a subspace. The use of polynomial basis functions in this paper makes NC equivalent to a local Taylor series expansion. Unlike the traditional framework, however, the window function of adaptive NC is adapted to local linear structures. This leads to more samples of the same modality being gathered for the analysis, which in turn improves signal-to-noise ratio and reduces diffusion across discontinuities. A robust signal certainty is also adapted to the sample intensities to minimize the influence of outliers. Excellent fusion capability of adaptive NC is demonstrated through an application of super-resolution image reconstruction.

  5. Robust Adaptive Synchronization of the Energy Resource System with Constraint

    Directory of Open Access Journals (Sweden)

    Duo Meng

    2013-01-01

    Full Text Available Two different chaos synchronization methods are proposed for a class of energy resource demand supply-system with input constraint. Firstly, chaotic synchronization is achieved for a class of energy resource demand supply system with known system parameters based on the Lyapunov theory. Secondly, an adaptive control approach is investigated for a class of energy resource demand supply system with input constraint, and the parameters of the system are unknown based on the Lyapunov stability and robust adaptive theory. To address the input constraint, new auxiliary signals and design systems are employed. Numerical simulations are provided to illustrate the effectiveness of the proposed approach.

  6. Robust decentralized adaptive stabilization for a class of interconnected systems

    Institute of Scientific and Technical Information of China (English)

    Zhaojing WU; Xuejun XIE; Siying ZHANG

    2004-01-01

    The robust decentralized adaptive output-feedback stabilization for a class of interconnected systems with static and dynamic interconnections by using the MT-filters and backstepping design method is studied. By introducing a new filtered tramformation, the adaptive laws were derived for measurement. Under the assumption of the nonlinear growth conditions imposed on the nonlinear interconnections and by constructing the error system and using a new proof method, the global stability of the closed-loop system was effectively analyzed, and the exponential convergence of all the signals except for parameter estimates were guaranteed.

  7. Robust adaptive matched field processing with environmental uncertainty

    Institute of Scientific and Technical Information of China (English)

    YANG Kunde; MA Yuanliang; ZHANG Zhongbing; ZOU Shixin

    2006-01-01

    The main challenges on detection and localization of quiet targets in littoral regions for passive sonar are the complicated acoustic propagation and the prevalence of loud ship interferences on the surface. Adaptive matched field processing can provide the ability to null surface interferences, but the mismatch between the computed and actual array steering vectors due to environment uncertainty, and the motion of both targets and interferences can result in loss of array gain significantly. To address the problem of environmental mismatch and target motion, a robust motion compensation algorithm and a system scheme for adaptive matched field processing have been developed. Both Numerical simulation and analysis of experimental data demonstrates that the robust AMFP scheme could suppress surface loud interferences and improve the detection performance for underwater weak moving targets in complex shallow water.

  8. A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

    Institute of Scientific and Technical Information of China (English)

    Yin Hao; Zhang Jiangshan; Zhu Yaoting; Zhu Guangxi

    2003-01-01

    A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

  9. A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

    Institute of Scientific and Technical Information of China (English)

    YinHao; ZhangJiangshan

    2003-01-01

    A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed.The encoder combines the best features of Fine Granularity Scalabla (FGS) coding,frame-dropping coding,video redundancy coding,and human visual model.According to packet loss and available bandwidth of the network,the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model,rate shaping,and periodically inserting key frame.The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm.It is shown that RAVE is a very efficient robust videl encoder that provides improved visual quality for the receiver and consumes equal or less network resource.Results are confirmed by subjective tests and simulation tests.

  10. Variable Neural Adaptive Robust Control: A Switched System Approach

    Energy Technology Data Exchange (ETDEWEB)

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  11. Robust adaptive synchronization of chaotic neural networks by slide technique

    Institute of Scientific and Technical Information of China (English)

    Lou Xu-Yang; Cui Bao-Tong

    2008-01-01

    In this paper,we focus on the robust adaptive synchronization between two coupled chaotic neural networks with all the parameters unknown and time-varying delay.In order to increase the robustness of the two coupled neural networks,the key idea is that a sliding-mode-type controller is employed.Moreover,without the estimate values of the network unknown parameters taken as an updating object,a new updating object is introduced in the constructing of controller.Using the proposed controller,without any requirements for the boundedness,monotonicity and differentiability of activation functions,and symmetry of connections,the two coupled chaotic neural networks can achieve global robust synchronization no matter what their initial states are.Finally,the numerical simulation validates the effectiveness and feasibility of the proposed technique.

  12. Robustness Assessment and Adaptive FDI for Car Engine

    Institute of Scientific and Technical Information of China (English)

    Mahavir Singh Sangha; Dingli Yu; J.Barry Gomm

    2008-01-01

    A new on-line fault detection and isolation (FDI) scheme proposed for engines using an adaptive neural network classifier is evaluated for a wide range of operational modes to check the robustness of the scheme in this paper. The neural classifier is adaptive to cope with the significant parameter uncertainty, disturbances, and environment changes. The developed scheme is capable of diagnosing faults in on-line mode and can be directly implemented in an on-board diagnosis system (hardware). The robustness of the FDI for the closed-loop system with crankshaft speed feedback is investigated by testing it for a wide range of operational modes including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all these changes occurring at the same time. The evaluations are performed using a mean value engine model (MVEM), which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.

  13. Adaptive Robust Waveform Selection for Unknown Target Detection in Clutter

    Institute of Scientific and Technical Information of China (English)

    Lu-Lu Wang; Hong-Qiang Wang; Yu-Liang Qin; Yong-Qiang Cheng

    2014-01-01

    @@@A basic assumption of most recently proposed waveform design algorithms is that the target impulse response is a known deterministic function or a stochastic process with a known power spectral density (PSD). However, it is well-known that a target impulse response is neither easily nor accurately obtained; besides it changes sharply with attitude angles. Both of the aforementioned cases complicate the waveform design process. In this paper, an adaptive robust waveform selection method for unknown target detection in clutter is proposed. The target impulse response is considered to be unknown but belongs to a known uncertainty set. An adaptive waveform library is devised by using a signal-to-clutter-plus-noise ratio (SCNR)- based optimal waveform design method. By applying the minimax robust waveform selection method, the optimal robust waveform is selected to ensure the lowest performance bound of the unknown target detection in clutter. Results show that the adaptive waveform library outperforms the predefined linear frequency modulation (LFM) waveform library on the SCNR bound.

  14. Interval-parameter robust quadratic programming for water quality management under uncertainty

    Science.gov (United States)

    Li, Y. P.; Huang, G. H.; Nie, S. L.; Mo, D. W.

    2008-07-01

    Effective planning of water quality management is important for facilitating sustainable socio-economic development in watershed systems. An interval-parameter robust quadratic programming (IRQP) method is developed by incorporating techniques of robust programming and interval quadratic programming within a general optimization framework. The IRQP improves upon existing quadratic programming methods, and can tackle uncertainties presented as interval numbers and fuzzy sets as well as their combinations. Moreover, it can deal with nonlinearities in the objective function such that economies-of-scale effects can be reflected. The developed method is applied to a case study of a water quality management under uncertainty. A number of decision alternatives are generated based on the interval solutions as well as the projected applicable conditions. They represent multiple decision options with various environmental and economic considerations. Willingness to accept a low economic revenue will guarantee satisfying the water quality requirements. A strong desire to acquire a high benefit will run the risk of violating environmental criteria.

  15. Robust stability test for 2-D continuous-discrete systems with interval parameters

    Institute of Scientific and Technical Information of China (English)

    肖扬

    2004-01-01

    It is revealed that the dynamic stability of 2-D recursive continuous-discrete systems with interval parameters involves the problem of robust Hurwitz-Schur stability of bivariate polynomials family. It is proved that the HurwitzSchur stability of the denominator polynomials of the systems is necessary and sufficient for the asymptotic stability of the 2-D hybrid systems. The 2-D hybrid transformation, i.e. 2-D Laplace-Z transformation, has been proposed to solve the stability analysis of the 2-D continuous-discrete systems, to get the 2-D hybrid transfer functions of the systems. The edge test for the Hurwitz-Schur stability of interval bivariate polynomials is introduced. The Hurwitz-Schur stability of the interval family of 2-D polynomials can be guaranteed by the stability of its finite edge polynomials of the family. An algorithm about the stability test of edge polynomials is given.

  16. Adaptive Interval Configuration to Enhance Dynamic Approach for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    Most proposed algorithms for mining association rules follow the conventional le vel-wise approach. The dynamic candidate generation idea introduced in the dyna mic itemset counting (DIC) a lgorithm broke away from the level-wise limitation which could find the large i t emsets using fewer passes over the database than level-wise algorithms. However , the dynamic approach is very sensitive to the data distribution of the database and it requires a proper interval size. In this paper an optimization technique named adaptive interval configuration (AIC) has been developed to enhance the d y namic approach. The AIC optimization has the following two functions. The first is that a homogeneous distribution of large itemsets over intervals can be achie ved so that less unnecessary candidates could be generated and less database sca nning passes are guaranteed. The second is that the near optimal interval size c ould be determined adaptively to produce the best response time. We also develop ed a candidate pruning technique named virtual partition pruning to reduce the s ize-2 candidate set and incorporated it into the AIC optimization. Based on the optimization technique, we proposed the efficient AIC algorithm for mining asso c iation rules. The algorithms of AIC, DIC and the classic Apriori were implemente d on a Sun Ultra Enterprise 4000 for performance comparison. The results show th at the AIC performed much better than both DIC and Apriori, and showed a strong robustness.

  17. Robust adaptive output stabilization using dynamic normalizing signal

    Institute of Scientific and Technical Information of China (English)

    Haixia SU; Xuejun XIE; Haikuan LIU

    2007-01-01

    For a class of nonlinear systems with dynamic uncertainties,robust adaptive stabilization problem is considered in this paper.Firstly,by introducing an observer,an augmented system is obtained.Based on the system,we construct an exp-ISpS Lyapunov function for the unmodeled dynamics,prove that the unmodeled dynamics is exp-ISpS,and then obtain a dynamic normalizing signal to counteract the dynamic disturbances.By the backstepping technique,an adaptive controller is given,it is proved that all the signals in the adaptive control system are globally uniformly ultimately bounded,and the output can be regulated to the origin with any prescribed accuracy.A simulation example further demonstrates the efficiency of the control scheme.

  18. Robust direct adaptive fuzzy control for nonlinear MIMO systems

    Institute of Scientific and Technical Information of China (English)

    ZHANG Huaguang; ZHANG Mingjun

    2006-01-01

    For a class of nonlinear multi-input multi-output systems with uncertainty, a robust direct adaptive fuzzy control scheme was proposed. The feedback control law and adaptive law for parameters were derived based on Lyapunov design approach. The overall control scheme can guarantee that the tracking error converges in the small neighborhood of origin, and all signals of the closed-loop system are uniformly bounded. The main advantage of the proposed control scheme is that in each subsystem only one parameter vector needs to be adjusted on-line in the adaptive mechanism, and so the on-line computing burden is reduced. In addition, the proposed control scheme is a smooth control with no chattering phenomena. A simulation example was proposed to demonstrate the effectiveness of the proposed control algorithm.

  19. Robust guaranteed-cost adaptive quantum phase estimation

    Science.gov (United States)

    Roy, Shibdas; Berry, Dominic W.; Petersen, Ian R.; Huntington, Elanor H.

    2017-05-01

    Quantum parameter estimation plays a key role in many fields like quantum computation, communication, and metrology. Optimal estimation allows one to achieve the most precise parameter estimates, but requires accurate knowledge of the model. Any inevitable uncertainty in the model parameters may heavily degrade the quality of the estimate. It is therefore desired to make the estimation process robust to such uncertainties. Robust estimation was previously studied for a varying phase, where the goal was to estimate the phase at some time in the past, using the measurement results from both before and after that time within a fixed time interval up to current time. Here, we consider a robust guaranteed-cost filter yielding robust estimates of a varying phase in real time, where the current phase is estimated using only past measurements. Our filter minimizes the largest (worst-case) variance in the allowable range of the uncertain model parameter(s) and this determines its guaranteed cost. It outperforms in the worst case the optimal Kalman filter designed for the model with no uncertainty, which corresponds to the center of the possible range of the uncertain parameter(s). Moreover, unlike the Kalman filter, our filter in the worst case always performs better than the best achievable variance for heterodyne measurements, which we consider as the tolerable threshold for our system. Furthermore, we consider effective quantum efficiency and effective noise power, and show that our filter provides the best results by these measures in the worst case.

  20. How protein materials balance strength, robustness, and adaptability

    Science.gov (United States)

    Buehler, Markus J.; Yung, Yu Ching

    2010-01-01

    Proteins form the basis of a wide range of biological materials such as hair, skin, bone, spider silk, or cells, which play an important role in providing key functions to biological systems. The focus of this article is to discuss how protein materials are capable of balancing multiple, seemingly incompatible properties such as strength, robustness, and adaptability. To illustrate this, we review bottom-up materiomics studies focused on the mechanical behavior of protein materials at multiple scales, from nano to macro. We focus on alpha-helix based intermediate filament proteins as a model system to explain why the utilization of hierarchical structural features is vital to their ability to combine strength, robustness, and adaptability. Experimental studies demonstrating the activation of angiogenesis, the growth of new blood vessels, are presented as an example of how adaptability of structure in biological tissue is achieved through changes in gene expression that result in an altered material structure. We analyze the concepts in light of the universality and diversity of the structural makeup of protein materials and discuss the findings in the context of potential fundamental evolutionary principles that control their nanoscale structure. We conclude with a discussion of multiscale science in biology and de novo materials design. PMID:20676305

  1. Robust adaptive control of underwater vehicles: A comparative study

    Directory of Open Access Journals (Sweden)

    Thor I. Fossen

    1996-01-01

    Full Text Available Robust adaptive control of underwater vehicles in 6 DOF is analysed in the context of measurement noise. The performance of the adaptive control laws of Sadegh and Harowitz (1990 and Slotine and Benedetto (1990 are compared. Both these schemes require that all states are measured, that is the velocities and positions in surge, sway, heave, roll, pitch and yaw. However, for underwater vehicles it is difficult to measure the linear velocities whereas angular velocity measurements can be obtained by using a 3 axes angular rate sensor. This problem is addressed by designing a nonlinear observer for linear velocity state estimation. The proposed observer requires that the position and the attitude are measured, e.g. by using a hydroacoustic positioning system for linear positions, two gyros for roll and pitch and a compass for yaw. In addition angular rate measurements will be assumed available from a 3-axes rate sensor or a state estimator. It is also assumed that the measurement rate is limited to 2 Hz for all the sensors. Simulation studies with a 3 DOF AUV model are used to demonstrate the convergence and robustness of the adaptive control laws and the velocity state observer.

  2. An adaptive robust controller for time delay maglev transportation systems

    Science.gov (United States)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  3. An Adaptive Robust Watermarking Algorithm for Audio Signals Using SVD

    Science.gov (United States)

    Dutta, Malay Kishore; Pathak, Vinay K.; Gupta, Phalguni

    This paper proposes an efficient watermarking algorithm which embeds watermark data adaptively in the audio signal. The algorithm embeds the watermark in the host audio signal in such a way that the degree of embedding (DOE) is adaptive in nature and is chosen in a justified manner according to the localized content of the audio. The watermark embedding regions are selectively chosen in the high energy regions of the audio signal which make the embedding process robust to synchronization attacks. Synchronization codes are added along with the watermark in the wavelet domain and hence the embedded data can be subjected to self synchronization and the synchronization code can be used as a check to combat false alarm that results from data modification due to watermark embedding. The watermark is embedded by quantization of the singular value decompositions in the wavelet domain which makes the process perceptually transparent. The experimental results suggest that the proposed algorithm maintains a good perceptual quality of the audio signal and maintains good robustness against signal processing attacks. Comparative analysis indicates that the proposed algorithm of adaptive DOE has superior performance in comparison to existing uniform DOE.

  4. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    DEFF Research Database (Denmark)

    Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.

    2015-01-01

    and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding-mode control (ARTSMC) system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances......This paper presents a microgrid stability controller (MSC) in order to provide existing DGs the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics....... The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing DG’s output power. When the microgrid is operating...

  5. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    Directory of Open Access Journals (Sweden)

    Elisa Capello

    2014-01-01

    Full Text Available The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required.

  6. A decentralized adaptive robust method for chaos control.

    Science.gov (United States)

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-09-01

    This paper presents a control strategy, which is based on sliding mode control, adaptive control, and fuzzy logic system for controlling the chaotic dynamics. We consider this control paradigm in chaotic systems where the equations of motion are not known. The proposed control strategy is robust against the external noise disturbance and system parameter variations and can be used to convert the chaotic orbits not only to the desired periodic ones but also to any desired chaotic motions. Simulation results of controlling some typical higher order chaotic systems demonstrate the effectiveness of the proposed control method.

  7. Passivity and robust synchronisation of switched interval coupled neural networks with time delay

    Science.gov (United States)

    Li, Ning; Cao, Jinde

    2016-09-01

    This paper is concerned with passivity and robust synchronisation of switched coupled neural networks with uncertain parameters. First, the mathematical model of switched coupled neural networks with interval uncertain parameters is established, which consists of L modes and switches from one mode to another according to the switching rule. Second, by employing passivity theory and linear matrix inequality techniques, delay-independent and delay-dependent conditions are derived to guarantee the passivity of switched interval coupled neural networks. Moreover, based on the proposed passivity results, global synchronisation criteria can be obtained for switched coupled neural networks with or without uncertain parameters. Finally, an illustrative example is provided to demonstrate the effectiveness of the obtained results.

  8. Adaptive Sliding Mode Control Using Robust Feedback Compensator for MEMS Gyroscope

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2013-01-01

    Full Text Available An adaptive sliding mode control using robust feedback compensator is presented for a MEMS gyroscope in the presence of external disturbances and parameter uncertainties. An adaptive controller with a robust term is used to improve the robustness of the control system and compensate the system nonlinearities. The proposed robust adaptive control can estimate the angular velocity and all the system parameters including damping and stiffness coefficients in the Lyapunov framework. In addition, standard adaptive control scheme without robust algorithm is compared with the proposed robust adaptive scheme in the aspect of numerical simulation and algorithm derivation. Numerical simulations show that the robust adaptive control has better robustness in the presence of external disturbances than the standard adaptive control.

  9. Robust visual tracking via adaptive kernelized correlation filter

    Science.gov (United States)

    Wang, Bo; Wang, Desheng; Liao, Qingmin

    2016-10-01

    Correlation filter based trackers have proved to be very efficient and robust in object tracking with a notable performance competitive with state-of-art trackers. In this paper, we propose a novel object tracking method named Adaptive Kernelized Correlation Filter (AKCF) via incorporating Kernelized Correlation Filter (KCF) with Structured Output Support Vector Machines (SOSVM) learning method in a collaborative and adaptive way, which can effectively handle severe object appearance changes with low computational cost. AKCF works by dynamically adjusting the learning rate of KCF and reversely verifies the intermediate tracking result by adopting online SOSVM classifier. Meanwhile, we bring Color Names in this formulation to effectively boost the performance owing to its rich feature information encoded. Experimental results on several challenging benchmark datasets reveal that our approach outperforms numerous state-of-art trackers.

  10. Robust adaptive backstepping control for piezoelectric nano-manipulating systems

    Science.gov (United States)

    Zhang, Yangming; Yan, Peng; Zhang, Zhen

    2017-01-01

    In this paper we present a systematic modeling and control approach for nano-manipulations of a two-dimensional PZT (piezoelectric transducer) actuated servo stage. The major control challenges associated with piezoelectric nano-manipulators typically include the nonlinear dynamics of hysteresis, model uncertainties, and various disturbances. The adverse effects of these complications will result in significant performance loss, unless effectively eliminated. The primary goal of the paper is on the ultra high precision control of such systems by handling various model uncertainties and disturbances simultaneously. To this end, a novel robust adaptive backstepping-like control approach is developed such that parametric uncertainties can be estimated adaptively while the nonlinear dynamics and external disturbances are treated as bounded disturbances for robust elimination. Meanwhile, the L2-gain of the closed-loop system is considered, and an H∞ optimization problem is formulated to improve the tracking accuracy. Numerical simulations and real time experiments are finally conducted, which significantly outperform conventional PID methods and achieve around 1% tracking error for circular contouring tasks.

  11. Robust Adaptive LCMV Beamformer Based On An Iterative Suboptimal Solution

    Directory of Open Access Journals (Sweden)

    Xiansheng Guo

    2015-06-01

    Full Text Available The main drawback of closed-form solution of linearly constrained minimum variance (CF-LCMV beamformer is the dilemma of acquiring long observation time for stable covariance matrix estimates and short observation time to track dynamic behavior of targets, leading to poor performance including low signal-noise-ratio (SNR, low jammer-to-noise ratios (JNRs and small number of snapshots. Additionally, CF-LCMV suffers from heavy computational burden which mainly comes from two matrix inverse operations for computing the optimal weight vector. In this paper, we derive a low-complexity Robust Adaptive LCMV beamformer based on an Iterative Suboptimal solution (RAIS-LCMV using conjugate gradient (CG optimization method. The merit of our proposed method is threefold. Firstly, RAIS-LCMV beamformer can reduce the complexity of CF-LCMV remarkably. Secondly, RAIS-LCMV beamformer can adjust output adaptively based on measurement and its convergence speed is comparable. Finally, RAIS-LCMV algorithm has robust performance against low SNR, JNRs, and small number of snapshots. Simulation results demonstrate the superiority of our proposed algorithms.

  12. A robust adaptive load frequency control for micro-grids

    DEFF Research Database (Denmark)

    Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede

    2016-01-01

    micro-grid (MG) is introduced that can consider electric vehicles׳ (EV(s)) effect. Moreover, in this paper, a new combination of the General Type II Fuzzy Logic Sets (GT2FLS) and the Modified Harmony Search Algorithm (MHSA) technique is applied for adaptive tuning of proportional-integral (PI...... wind farm in Sweden and solar radiation data in Aberdeen (United Kingdom) was used in order to examine the performance of the proposed novel controller. A comparison is made between the achieved results of Optimal Fuzzy-PI (OFPI) controller and those of Optimal Interval Type II Fuzzy-PI (IT2FPI...

  13. Robust fault detection in bond graph framework using interval analysis and Fourier-Motzkin elimination technique

    Science.gov (United States)

    Jha, Mayank Shekhar; Chatti, Nizar; Declerck, Philippe

    2017-09-01

    This paper addresses the fault diagnosis problem of uncertain systems in the context of Bond Graph modelling technique. The main objective is to enhance the fault detection step based on Interval valued Analytical Redundancy Relations (named I-ARR) in order to overcome the problems related to false alarms, missed alarms and robustness issues. These I-ARRs are a set of fault indicators that generate the interval bounds called thresholds. A fault is detected once the nominal residuals (point valued part of I-ARRs) exceed the thresholds. However, the existing fault detection method is limited to parametric faults and it presents various limitations with regards to estimation of measurement signal derivatives, to which I-ARRs are sensitive. The novelties and scientific interest of the proposed methodology are: (1) to improve the accuracy of the measurements derivatives estimation by using a dedicated sliding mode differentiator proposed in this work, (2) to suitably integrate the Fourier-Motzkin Elimination (FME) technique within the I-ARRs based diagnosis so that measurements faults can be detected successfully. The latter provides interval bounds over the derivatives which are included in the thresholds. The proposed methodology is studied under various scenarios (parametric and measurement faults) via simulations over a mechatronic torsion bar system.

  14. Robust Adaptive Reactive Power Control for Doubly Fed Induction Generator

    Directory of Open Access Journals (Sweden)

    Huabin Wen

    2014-01-01

    Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.

  15. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    Directory of Open Access Journals (Sweden)

    Xiaoling Su

    2015-03-01

    Full Text Available This paper presents a microgrid stability controller (MSC in order to provide existing distributed generation units (DGs the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding-mode control (ARTSMC system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances. The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing the DGs’ output power. When the microgrid is operating in islanded mode, it provides voltage and frequency support, while guaranteeing seamless transition between the two operation modes. Simulation and experimental results show the effectiveness of the proposed approach.

  16. Switching Control System Based on Robust Model Reference Adaptive Control

    Institute of Scientific and Technical Information of China (English)

    HU Qiong; FEI Qing; MA Hongbin; WU Qinghe; GENG Qingbo

    2016-01-01

    For conventional adaptive control,time-varying parametric uncertainty and unmodeled dynamics are ticklish problems,which will lead to undesirable performance or even instability and nonrobust behavior,respectively.In this study,a class of discrete-time switched systems with unmodeled dynamics is taken into consideration.Moreover,nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper,and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance.For robustness against unmodeled dynamics and uncertainty,robust model reference aclaptive control (RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems.Meanwhile,two different switching laws are presented for switched systems and nonlinear systems,respectively.Thereby,the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems.Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes.Furthermore,as to the proposed scheme for nonlinear systems,its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.

  17. Robust Adaptive Backstepping Control Design for a Nonlinear Hydraulic-Mechanical System

    DEFF Research Database (Denmark)

    Choux, Martin; Karimi, Hamid Reza; Hovland, Geir

    2009-01-01

    converge to zero despite the uncertainties in the system according to the Barbalat lemma. The resulting controllers are able to take into account the interval uncertainties in Coulomb friction parameters and in the internal leakage parameters in the cylinders. Two adaptation laws are obtained by using......The complex dynamics that characterize hydraulic systems make it difficult for the control design to achieve prescribed goals in an efficient manner. In this paper, we present the design and analysis of a robust nonlinear controller for a nonlinear hydraulic-mechanical (NHM) system. The system...... consists of an electrohydraulic servo valve and two hydraulic cylinders. Specifically, by considering a part of the dynamics of the NHM system as a norm-bounded uncertainty, two adaptive controllers are developed based on the backstepping technique that ensure the tracking error signals asymptotically...

  18. Robust observer-based adaptive fuzzy sliding mode controller

    Science.gov (United States)

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

    In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

  19. Nonlinear mode decomposition: a noise-robust, adaptive decomposition method.

    Science.gov (United States)

    Iatsenko, Dmytro; McClintock, Peter V E; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool-nonlinear mode decomposition (NMD)-which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques-which, together with the adaptive choice of their parameters, make it extremely noise robust-and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  20. Robustness via Run-Time Adaptation of Contingent Plans

    Science.gov (United States)

    Bresina, John L.; Washington, Richard; Norvig, Peter (Technical Monitor)

    2000-01-01

    In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.

  1. Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

    Science.gov (United States)

    Samaras, C.; Cook, L.

    2015-12-01

    Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

  2. Distributed reinforcement learning for adaptive and robust network intrusion response

    Science.gov (United States)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  3. Robust image registration using adaptive coherent point drift method

    Science.gov (United States)

    Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong

    2016-04-01

    Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.

  4. Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame

    KAUST Repository

    Chaoui, Hicham

    2017-01-10

    In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory to achieve accurate tracking and robustness to higher uncertainties. Unlike other controllers, the proposed strategy does not require electrical transducers and hence, no explicit currents loop regulation is needed, which yields a simplified control scheme. But, this limits the machine\\'s operation range since it results in a higher energy consumption. Therefore, a modified reference frame is also proposed in this paper to decrease the machine\\'s consumption. To better assess the performance of the new reference frame, comparison against its original counterpart is carried-out under the same conditions. Moreover, the stability of the closed-loop control scheme is guaranteed by a Lyapunov theorem. Simulation and experimental results for numerous situations highlight the effectiveness of the proposed controller in standstill, transient, and steady-state conditions.

  5. A queuing-theory-based interval-fuzzy robust two-stage programming model for environmental management under uncertainty

    Science.gov (United States)

    Sun, Y.; Li, Y. P.; Huang, G. H.

    2012-06-01

    In this study, a queuing-theory-based interval-fuzzy robust two-stage programming (QB-IRTP) model is developed through introducing queuing theory into an interval-fuzzy robust two-stage (IRTP) optimization framework. The developed QB-IRTP model can not only address highly uncertain information for the lower and upper bounds of interval parameters but also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. Moreover, it can reflect uncertainties in queuing theory problems. The developed method has been applied to a case of long-term municipal solid waste (MSW) management planning. Interval solutions associated with different waste-generation rates, different waiting costs and different arriving rates have been obtained. They can be used for generating decision alternatives and thus help managers to identify desired MSW management policies under various economic objectives and system reliability constraints.

  6. Improved Robust Adaptive Control of a Fluidized Bed Combustor for Sewage Sludge

    Institute of Scientific and Technical Information of China (English)

    MENGHong-Xia; JIAYing-Min

    2005-01-01

    This paper presents a robust model reference adaptive control scheme to deal with uncertain time delay in the dynamical model of a fluidized bed combustor for sewage sludge. The theoretical analysis and simulation results show that the proposed scheme can guarantee not only stability and robustness, but also the adaptive decoupling performance of the system.

  7. Robust identification of local adaptation from allele frequencies.

    Science.gov (United States)

    Günther, Torsten; Coop, Graham

    2013-09-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.

  8. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations

    Science.gov (United States)

    Egbert, Matthew D.; Pérez-Mercader, Juan

    2016-01-01

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism’s internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving “interoceptively,” i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579

  9. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations.

    Science.gov (United States)

    Egbert, Matthew D; Pérez-Mercader, Juan

    2016-01-08

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism's internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving "interoceptively," i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms.

  10. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations.

    Science.gov (United States)

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations.

  11. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations

    Science.gov (United States)

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations.

  12. Short- and long-term biomarkers for bacterial robustness: a framework for quantifying correlations between cellular indicators and adaptive behavior.

    Directory of Open Access Journals (Sweden)

    Heidy M W den Besten

    Full Text Available The ability of microorganisms to adapt to changing environments challenges the prediction of their history-dependent behavior. Cellular biomarkers that are quantitatively correlated to stress adaptive behavior will facilitate our ability to predict the impact of these adaptive traits. Here, we present a framework for identifying cellular biomarkers for mild stress induced enhanced microbial robustness towards lethal stresses. Several candidate-biomarkers were selected by comparing the genome-wide transcriptome profiles of our model-organism Bacillus cereus upon exposure to four mild stress conditions (mild heat, acid, salt and oxidative stress. These candidate-biomarkers--a transcriptional regulator (activating general stress responses, enzymes (removing reactive oxygen species, and chaperones and proteases (maintaining protein quality--were quantitatively determined at transcript, protein and/or activity level upon exposure to mild heat, acid, salt and oxidative stress for various time intervals. Both unstressed and mild stress treated cells were also exposed to lethal stress conditions (severe heat, acid and oxidative stress to quantify the robustness advantage provided by mild stress pretreatment. To evaluate whether the candidate-biomarkers could predict the robustness enhancement towards lethal stress elicited by mild stress pretreatment, the biomarker responses upon mild stress treatment were correlated to mild stress induced robustness towards lethal stress. Both short- and long-term biomarkers could be identified of which their induction levels were correlated to mild stress induced enhanced robustness towards lethal heat, acid and/or oxidative stress, respectively, and are therefore predictive cellular indicators for mild stress induced enhanced robustness. The identified biomarkers are among the most consistently induced cellular components in stress responses and ubiquitous in biology, supporting extrapolation to other microorganisms

  13. Robust Adaptive Exponential Synchronization of Stochastic Perturbed Chaotic Delayed Neural Networks with Parametric Uncertainties

    Directory of Open Access Journals (Sweden)

    Yang Fang

    2014-01-01

    Full Text Available This paper investigates the robust adaptive exponential synchronization in mean square of stochastic perturbed chaotic delayed neural networks with nonidentical parametric uncertainties. A robust adaptive feedback controller is proposed based on Gronwally’s inequality, drive-response concept, and adaptive feedback control technique with the update laws of nonidentical parametric uncertainties as well as linear matrix inequality (LMI approach. The sufficient conditions for robust adaptive exponential synchronization in mean square of uncoupled uncertain stochastic chaotic delayed neural networks are derived in terms of linear matrix inequalities (LMIs. The effect of nonidentical uncertain parameter uncertainties is suppressed by the designed robust adaptive feedback controller rapidly. A numerical example is provided to validate the effectiveness of the proposed method.

  14. A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks.

    Science.gov (United States)

    Faydasicok, Ozlem; Arik, Sabri

    2013-08-01

    The main problem with the analysis of robust stability of neural networks is to find the upper bound norm for the intervalized interconnection matrices of neural networks. In the previous literature, the major three upper bound norms for the intervalized interconnection matrices have been reported and they have been successfully applied to derive new sufficient conditions for robust stability of delayed neural networks. One of the main contributions of this paper will be the derivation of a new upper bound for the norm of the intervalized interconnection matrices of neural networks. Then, by exploiting this new upper bound norm of interval matrices and using stability theory of Lyapunov functionals and the theory of homomorphic mapping, we will obtain new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slope-bounded activation functions. The results obtained in this paper will be shown to be new and they can be considered alternative results to previously published corresponding results. We also give some illustrative and comparative numerical examples to demonstrate the effectiveness and applicability of the proposed robust stability condition.

  15. Adaptive robust controller based on integral sliding mode concept

    Science.gov (United States)

    Taleb, M.; Plestan, F.

    2016-09-01

    This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

  16. Global Robust Stability of Switched Interval Neural Networks with Discrete and Distributed Time-Varying Delays of Neural Type

    Directory of Open Access Journals (Sweden)

    Huaiqin Wu

    2012-01-01

    Full Text Available By combing the theories of the switched systems and the interval neural networks, the mathematics model of the switched interval neural networks with discrete and distributed time-varying delays of neural type is presented. A set of the interval parameter uncertainty neural networks with discrete and distributed time-varying delays of neural type are used as the individual subsystem, and an arbitrary switching rule is assumed to coordinate the switching between these networks. By applying the augmented Lyapunov-Krasovskii functional approach and linear matrix inequality (LMI techniques, a delay-dependent criterion is achieved to ensure to such switched interval neural networks to be globally asymptotically robustly stable in terms of LMIs. The unknown gain matrix is determined by solving this delay-dependent LMIs. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.

  17. Robust adaptive neural network control with supervisory controller

    Institute of Scientific and Technical Information of China (English)

    张天平; 梅建东

    2004-01-01

    The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.

  18. Adaptive differential evolution a robust approach to multimodal problem optimization

    CERN Document Server

    Zhang, Jingqiao; Zhang, Jingqiao

    2009-01-01

    The fundamental theme of this book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. The book offers real-world insights into a variety of large-scale complex industrial applications.

  19. Robust Blind Adaptive Channel Equalization in Chaotic Communication Systems

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jia-Shu

    2006-01-01

    Based on the bounded property and statistics of chaotic signal and the idea of set-membership identification,we propose a set-membership generalized least mean square (SM-GLMS) algorithm with variable step size for blind adaptive channel equalization in chaotic communication systems. The steady state performance of the proposed SM-GLMS algorithm is analysed, and comparison with an extended Kalman filter (EKF)-based adaptive algorithm and variable gain least mean square (VG-LMS) algorithm is performed for blind adaptive channel equalization. Simulations show that the proposed SM-GLMS algorithm can provide more significant steady state performance improvement than the EKF-based adaptive algorithm and VG-LMS algorithm.

  20. Two-Stage Robust Security-Constrained Unit Commitment with Optimizable Interval of Uncertain Wind Power Output

    Directory of Open Access Journals (Sweden)

    Dayan Sun

    2017-01-01

    Full Text Available Because wind power spillage is barely considered, the existing robust unit commitment cannot accurately analyze the impacts of wind power accommodation on on/off schedules and spinning reserve requirements of conventional generators and cannot consider the network security limits. In this regard, a novel double-level robust security-constrained unit commitment formulation with optimizable interval of uncertain wind power output is firstly proposed in this paper to obtain allowable interval solutions for wind power generation and provide the optimal schedules for conventional generators to cope with the uncertainty in wind power generation. The proposed double-level model is difficult to be solved because of the invalid dual transform in solution process caused by the coupling relation between the discrete and continuous variables. Therefore, a two-stage iterative solution method based on Benders Decomposition is also presented. The proposed double-level model is transformed into a single-level and two-stage robust interval unit commitment model by eliminating the coupling relation, and then this two-stage model can be solved by Benders Decomposition iteratively. Simulation studies on a modified IEEE 26-generator reliability test system connected to a wind farm are conducted to verify the effectiveness and advantages of the proposed model and solution method.

  1. Robust Adaptive Beamforming Based on Worst-Case and Norm Constraint

    Directory of Open Access Journals (Sweden)

    Hongtao Li

    2015-01-01

    Full Text Available A novel robust adaptive beamforming based on worst-case and norm constraint (RAB-WC-NC is presented. The proposed beamforming possesses superior robustness against array steering vector (ASV error with finite snapshots by using the norm constraint and worst-case performance optimization (WCPO techniques. Simulation results demonstrate the validity and superiority of the proposed algorithm.

  2. Weighted Robust Adaptive Filtering in Krein Space and Its Application in Active Noise Control

    NARCIS (Netherlands)

    Jayawardhana, Bayu; Yuan, Shuqing; Xie, Lihua

    2002-01-01

    Robust adaptive filtering ensures the minimization of the transfer function from the disturbance to the estimation error and thus, guarantees the robustness against the worst-case disturbance in the system. However, a more general approach will be given in this paper hy employing frequency weighting

  3. Short intervals induce superior training adaptations compared with long intervals in cyclists - an effort-matched approach.

    Science.gov (United States)

    Rønnestad, B R; Hansen, J; Vegge, G; Tønnessen, E; Slettaløkken, G

    2015-04-01

    The purpose of this study was to compare the effects of 10 weeks of effort-matched short intervals (SI; n = 9) or long intervals (LI; n = 7) in cyclists. The high-intensity interval sessions (HIT) were performed twice a week interspersed with low-intensity training. There were no differences between groups at pretest. There were no differences between groups in total volume of both HIT and low-intensity training. The SI group achieved a larger relative improvement in VO(2max) than the LI group (8.7% ± 5.0% vs 2.6% ± 5.2%), respectively, P ≤ 0.05). Mean effect size (ES) of the relative improvement in all measured parameters, including performance measured as mean power output during 30-s all-out, 5-min all-out, and 40-min all-out tests revealed a moderate-to-large effect of SI training vs LI training (ES range was 0.86-1.54). These results suggest that the present SI protocol induces superior training adaptations on both the high-power region and lower power region of cyclists' power profile compared with the present LI protocol. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Adaptive Introspection and Deployment for Robust Long Duration Autonomy

    Science.gov (United States)

    2014-09-30

    Duration Autonomy Nathan Michael, Sebastian Scherer Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA, 15213-3890 phone: (412) 268...7816 fax: (412) 268-1338 email: nmichael@cmu.edu, scherer@cmu.edu Award Number: N000141310821 LONG-TERM GOALS Long duration autonomy ...integrative experimental framework toward evaluating the approaches developed through the first two tasks. Task 1: Introspection for Robust Autonomy

  5. Robust and Adaptive MicroRNA-Mediated Incoherent Feedforward Motifs

    Institute of Scientific and Technical Information of China (English)

    XU Feng-Dan; LIU Zeng-Rong; ZHANG Zhi-Yong; SHEN Jian-Wei

    2009-01-01

    We integrate transcriptional and post-transcriptional regulation into microRNA-mediated incoherent feedforward motifs and analyse their dynamical behaviour and functions. The analysis show that the behaviour of the system is almost uninfluenced by the varying input in certain ranges and by introducing of delay and noise. The results indicate that microRNA-mediated incoherent feedforward motifs greatly enhance the robustness of gene regulation.

  6. Decentralized Robust Adaptive Output Feedback Stabilization for Interconnected Nonlinear Systems with Uncertainties

    Directory of Open Access Journals (Sweden)

    Qiang Yang

    2016-01-01

    Full Text Available Based on adaptive nonlinear damping, a novel decentralized robust adaptive output feedback stabilization comprising a decentralized robust adaptive output feedback controller and a decentralized robust adaptive observer is proposed for a large-scale interconnected nonlinear system with general uncertainties, such as unknown nonlinear parameters, bounded disturbances, unknown nonlinearities, unmodeled dynamics, and unknown interconnections, which are nonlinear function of not only states and outputs but also unmodeled dynamics coming from other subsystems. In each subsystem, the proposed stabilization only has two adaptive parameters, and it is not needed to generate an additional dynamic signal or estimate the unknown parameters. Under certain assumptions, the proposed scheme guarantees that all the dynamic signals in the interconnected nonlinear system are bounded. Furthermore, the system states and estimate errors can approach arbitrarily small values by choosing the design parameters appropriately large. Finally, simulation results illustrated the effectiveness of the proposed scheme.

  7. Robust Adaptive Photon Tracing using Photon Path Visibility

    DEFF Research Database (Denmark)

    Hachisuka, Toshiya; Jensen, Henrik Wann

    2011-01-01

    We present a new adaptive photon tracing algorithm which can handle illumination settings that are considered difficult for photon tracing approaches such as outdoor scenes, close-ups of a small part of an illuminated region, and illumination coming through a small gap. The key contribution in our...... algorithm is the use of visibility of photon path as the importance function which ensures that our sampling algorithm focuses on paths that are visible from the given viewpoint. Our sampling algorithm builds on two recent developments in Markov chain Monte Carlo methods: adaptive Markov chain sampling...... and replica exchange. Using these techniques, each photon path is adaptively mutated and it explores the sampling space efficiently without being stuck at a local peak of the importance function. We have implemented this sampling approach in the progressive photon mapping algorithm which provides visibility...

  8. An Adaptive Fuzzy Control Approach for the Robust Tracking of a MEMS Gyroscope Sensor

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2011-11-01

    Full Text Available In this paper, a direct adaptive fuzzy control using a supervisory compensator is designed for the robust tracking of a MEMS gyroscope sensor. The parameters of the membership functions are adjusted according to the designed adaptive law for the purpose of tracking a reference trajectory. A fuzzy controller that can approximate the unknown nonlinear function and compensate the system

  9. Transient scenarios for robust climate change adaptation illustrated for water manegement in the Netherlands

    NARCIS (Netherlands)

    Haasnoot, M.; Schellekens, J.; Beersma, J.; Middelkoop, H.; Kwadijk, J.C.J.

    2015-01-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for loca

  10. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands

    NARCIS (Netherlands)

    Haasnoot, M.; Schellekens, J.; Beersma, J.J.; Middelkoop, H.; Kwadijk, J.C.J.

    2015-01-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for loca

  11. Adaptive Robust Tracking Control of Pressure Trajectory Based on Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    CAO Jian; ZHU Xiaocong; TAO Guoliang; YAO Bin

    2009-01-01

    When adaptive robust control(ARC) strategy based on backstepping design is applied in pneumatic servo control, accurate pressure tracking in motion is especially necessary for both force and position trajectories tracking of rodless pneumatic cylinders, and therefore an adaptive robust pressure controller is developed in this paper to improve the tracking accuracy of pressure trajectory in the chamber when the pneumatic cylinder is moving. In the proposed adaptive robust pressure controller, off-line fitting of the orifice area and on-line parameter estimation of the flow coefficient are utilized to have improved model compensation, and meanwhile robust feedback and Kalman filter are used to have strong robustness against uncertain nonlinearities, parameter fluctuations and noise. Research results demonstrate that the adaptive robust pressure controller could not only track various pressure trajectories accurately even when the pneumatic cylinder is moving, but also obtain very smooth control input, which indicates the effectiveness of adaptive model compensation. Especially when a step pressure trajectory is tracked under the condition of the movement of a rodless pneumatic cylinder, maximum tracking error of ARC is 4.46 kPa and average tracking error is 0.99 kPa, and steady-state error of ARC could achieve 0.84 kPa, which is very close to the measurement accuracy of pressure transducer.

  12. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  13. Adaptive robust control of nonholonomic systems with stochastic disturbances

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper deals with nonholonomic systems in chained form with unknown covariance stochastic disturbances. The objective is to design the almost global adaptive asymptotical controllers in probability u0 and u1 for the systems by using discontinuous control. A switching control law u0 is designed to almost globally asymptotically stabilize the state x0 in both the singular x0 (t0)=0 case and the non-singular x0 (t0)≠0 case. Then the state scaling technique is introduced for the discontinuous feedback into the (x1, x2, …, xn)-subsystem. Thereby, by using backstepping technique the global adaptive asymptotical control law u1 has been presented for (x1, x2, …, xn) -subsystem for both different u0 in non-singular x0 (t0)≠0 case and the singular case x0 (t0)=0. The control algorithm validity is proved by simulation.

  14. Robust Adaptive Control via Neural Linearization and Compensation

    Directory of Open Access Journals (Sweden)

    Roberto Carmona Rodríguez

    2012-01-01

    Full Text Available We propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure the stability of neural identification. Then four types of compensator are addressed. The stability of closed-loop system is also proven.

  15. Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

    Directory of Open Access Journals (Sweden)

    Zhonghua Wu

    2017-01-01

    Full Text Available This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller.

  16. Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

    Science.gov (United States)

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-01-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

  17. Design of Robust Optimal Fixed Structure Controller Using Self Adaptive Differential Evolution

    Science.gov (United States)

    Joe Amali, S. Miruna; Baskar, S.

    This paper presents a design of robust optimal fixed structure controller for systems with uncertainties and disturbance using Self Adaptive Differential Evolution (SaDE) algorithm. PID controller and second order polynomial structure are considered for fixed structure controller. The design problem is formulated as minimization of maximum value of real part of the poles subject to the robust stability criteria and load disturbance attenuation criteria. The performance of the proposed method is demonstrated with a test system. SaDE self adapts the trial vector generation strategy and crossover rate (CR) value during evolution. Self adaptive Penalty (SP) method is used for constraint handling. The results are compared with constrained PSO and mixed Deterministic/Randomized algorithms. It is shown experimentally that the SaDE adapts automatically to the best strategy and CR value. Performance of the SaDE-based controller is superior to other methods in terms of success rate, robust stability, and disturbance attenuation.

  18. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands

    OpenAIRE

    Haasnoot, M.; Schellekens, J; Beersma, J.J.; Middelkoop, H.; J. C. J. Kwadijk

    2015-01-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for local or regional decision making on climate adaptation are static 'endpoint' projections. This paper describes the development and use of transient (time-dependent) scenarios by means of a case on wat...

  19. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly...... dependent of the operating point, which is characterised by the speed and load. If the requirements to the controller performance is large, then it is difficult to maintain specified controller performance with a fixed controller, because of the open loop variations. An auto-tuner based on least squares......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...

  20. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly...... dependent of the operating point, which is characterised by the speed and load. If the requirements to the controller performance is large, then it is difficult to maintain specified controller performance with a fixed controller, because of the open loop variations. An auto-tuner based on least squares......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...

  1. Robust Adaptive Stabilization of Nonholonomic Mobile Robots with Bounded Disturbances

    Directory of Open Access Journals (Sweden)

    Gang Chen

    2014-01-01

    Full Text Available The stabilization problem of nonholonomic mobile robots with unknown system parameters and environmental disturbances is investigated in this paper. Considering the dynamic model and the kinematic model of mobile robots, the transverse function approach is adopted to construct an additional control parameter, so that the closed-loop system is not underactuated. Then the adaptive backstepping method and the parameter projection technique are applied to design the controller to stabilize the system. At last, simulation results demonstrate the effectiveness of our proposed controller schemes.

  2. Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

    Science.gov (United States)

    Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  3. Improved robust stabilization method for linear systems with interval time-varying input delays by using Wirtinger inequality.

    Science.gov (United States)

    Liu, Yuzhi; Li, Muguo

    2015-05-01

    This paper investigates the robust stabilization problem for uncertain linear systems with interval time-varying delays. By constructing novel Lyapunov-Krasovskii functionals and developing delay-partitioning approaches, some delay-dependent stability criteria are derived based on an improved Wirtinger׳s inequality and the reciprocally convex method. The proposed methods have improved the stability conditions without increasing much computational complexity. A state feedback controller design approach is also presented based on the proposed criteria. Numerical examples are finally given to illustrate the effectiveness of the proposed method.

  4. Delay-dependent robust H-infinity filtering for uncertain linear systems with time-varying interval delay

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This paper proposed a design method for delay-dependent robust H-infinity filter of linear systems with uncertainty and time-varying interval delay.The proposed method was shown to be much simpler than existing ones while giving significant improvement to the existing results.The key step in the method was to construct a special type of Lyapunov functional for the filter design problem.Unlike the existing techniques,the proposed method employed neither free weighting matrices nor any model transformation,le...

  5. Delay-Dependent Robust Exponential Stability for Uncertain Neutral Stochastic Systems with Interval Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Weihua Mao

    2012-01-01

    Full Text Available This paper discusses the mean-square exponential stability of uncertain neutral linear stochastic systems with interval time-varying delays. A new augmented Lyapunov-Krasovskii functional (LKF has been constructed to derive improved delay-dependent robust mean-square exponential stability criteria, which are forms of linear matrix inequalities (LMIs. By free-weight matrices method, the usual restriction that the stability conditions only bear slow-varying derivative of the delay is removed. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.

  6. A methodology for adaptable and robust ecosystem services assessment

    Science.gov (United States)

    Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

    2014-01-01

    Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

  7. Noise-induced interspike interval correlations and spike train regularization in spike-triggered adapting neurons

    CERN Document Server

    Urdapilleta, Eugenio

    2016-01-01

    Spike generation in neurons produces a temporal point process, whose statistics is governed by intrinsic phenomena and the external incoming inputs to be coded. In particular, spike-evoked adaptation currents support a slow temporal process that conditions spiking probability at the present time according to past activity. In this work, we study the statistics of interspike interval correlations arising in such non-renewal spike trains, for a neuron model that reproduces different spike modes in a small adaptation scenario. We found that correlations are stronger as the neuron fires at a particular firing rate, which is defined by the adaptation process. When set in a subthreshold regime, the neuron may sustain this particular firing rate, and thus induce correlations, by noise. Given that, in this regime, interspike intervals are negatively correlated at any lag, this effect surprisingly implies a reduction in the variability of the spike count statistics at a finite noise intensity.

  8. Noise-induced interspike interval correlations and spike train regularization in spike-triggered adapting neurons

    Science.gov (United States)

    Urdapilleta, Eugenio

    2016-09-01

    Spike generation in neurons produces a temporal point process, whose statistics is governed by intrinsic phenomena and the external incoming inputs to be coded. In particular, spike-evoked adaptation currents support a slow temporal process that conditions spiking probability at the present time according to past activity. In this work, we study the statistics of interspike interval correlations arising in such non-renewal spike trains, for a neuron model that reproduces different spike modes in a small adaptation scenario. We found that correlations are stronger as the neuron fires at a particular firing rate, which is defined by the adaptation process. When set in a subthreshold regime, the neuron may sustain this particular firing rate, and thus induce correlations, by noise. Given that, in this regime, interspike intervals are negatively correlated at any lag, this effect surprisingly implies a reduction in the variability of the spike count statistics at a finite noise intensity.

  9. Robustness

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Rizzuto, Enrico; Narasimhan, Harikrishna

    2012-01-01

    More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of structures......, a theoretical and risk-based framework is presented which facilitates the quantification of robustness, and thus supports the formulation of pre-normative guidelines....

  10. Robust adaptive synchronization of general dynamical networks with multiple delays and uncertainties

    Indian Academy of Sciences (India)

    LU YIMING; HE PING; MA SHU-HUA; LI GUO-ZHI; MOBAYBEN SALEH

    2016-06-01

    In this article, a general complex dynamical network which contains multiple delays and uncertainties is introduced, which contains time-varying coupling delays, time-varying node delay, and uncertainties of both the inner- and outer-coupling matrices. A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose some suitable adaptive synchronization controllers to ensure the robust synchronization of this dynamical network. The numerical simulations of the time-delay Lorenz chaotic system as local dynamical node are provided to observe and verify the viability and productivity of the theoretical research in this paper. Compared to the achievement of previous research, theresearch in this paper seems quite comprehensive and universal.

  11. Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem

    Directory of Open Access Journals (Sweden)

    Xingjian Wang

    2013-01-01

    Full Text Available Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.

  12. Robust Adaptive Fault-Tolerant Tracking Control of Three-Phase Induction Motor

    Directory of Open Access Journals (Sweden)

    Hossein Tohidi

    2014-01-01

    Full Text Available This paper deals with the problem of induction motor tracking control against actuator faults and external disturbances using the linear matrix inequalities (LMIs method and the adaptive method. A direct adaptive fault-tolerant tracking controller design method is developed based on Lyapunov stability theory and a constructive algorithm based on linear matrix inequalities for online tuning of adaptive and state feedback gains to stabilize the closed-loop system in order to reduce the fault effect with disturbance attenuation. Simulation results reveal the merits of proposed robust adaptive fault-tolerant tracking control scheme on an induction motor subjected to actuator faults.

  13. Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics

    Directory of Open Access Journals (Sweden)

    Zhaoxia Peng

    2014-01-01

    Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.

  14. A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

    Science.gov (United States)

    Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

    2015-04-01

    This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation.

  15. Robust adaptive control for uncertain systems with discrete and distributed delays

    Institute of Scientific and Technical Information of China (English)

    Qing ZHU; Shumin FEI; Tao Li; Tianping ZHANG

    2008-01-01

    In this paper,a robust adaptive control scheme is proposed for the stabilization of uncertain linear systems with discrete and distributed delays and bounded peturbaturbations.The uncertainty is assumed to be an unknown continuous function with norm-bounded restriction.The perturbation is sector-bounded.Combining with the liner matrix inequality method,neural networks and adaptive control,the control scheme ensures the exponential stability of the closed-loop system for any admissible uncertainty.

  16. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands

    Science.gov (United States)

    Haasnoot, M.; Schellekens, J.; Beersma, J. J.; Middelkoop, H.; Kwadijk, J. C. J.

    2015-10-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for local or regional decision making on climate adaptation are static ‘endpoint’ projections. This paper describes the development and use of transient (time-dependent) scenarios by means of a case on water management in the Netherlands. Relevant boundary conditions (sea level, precipitation and evaporation) were constructed by generating an ensemble of synthetic time-series with a rainfall generator and a transient delta change method. Climate change impacted river flows were then generated with a hydrological simulation model for the Rhine basin. The transient scenarios were applied in model simulations and game experiments. We argue that there are at least three important assets of using transient scenarios for supporting robust climate adaptation: (1) raise awareness about (a) the implications of climate variability and climate change for decision making and (b) the difficulty of finding proof of climate change in relevant variables for water management; (2) assessment of when to adapt by identifying adaptation tipping points which can then be used to explore adaptation pathways, and (3) identification of triggers for climate adaptation.

  17. Human action classification using adaptive key frame interval for feature extraction

    Science.gov (United States)

    Lertniphonphan, Kanokphan; Aramvith, Supavadee; Chalidabhongse, Thanarat H.

    2016-01-01

    Human action classification based on the adaptive key frame interval (AKFI) feature extraction is presented. Since human movement periods are different, the action intervals that contain the intensive and compact motion information are considered in this work. We specify AKFI by analyzing an amount of motion through time. The key frame is defined to be the local minimum interframe motion, which is computed by using frame differencing between consecutive frames. Once key frames are detected, the features within a segmented period are encoded by adaptive motion history image and key pose history image. The action representation consists of the local orientation histogram of the features during AKFI. The experimental results on Weizmann dataset, KTH dataset, and UT Interaction dataset demonstrate that the features can effectively classify action and can classify irregular cases of walking compared to other well-known algorithms.

  18. Physiological adaptations to interval training and the role of exercise intensity.

    Science.gov (United States)

    MacInnis, Martin J; Gibala, Martin J

    2017-05-01

    Interval exercise typically involves repeated bouts of relatively intense exercise interspersed by short periods of recovery. A common classification scheme subdivides this method into high-intensity interval training (HIIT; 'near maximal' efforts) and sprint interval training (SIT; 'supramaximal' efforts). Both forms of interval training induce the classic physiological adaptations characteristic of moderate-intensity continuous training (MICT) such as increased aerobic capacity (V̇O2 max ) and mitochondrial content. This brief review considers the role of exercise intensity in mediating physiological adaptations to training, with a focus on the capacity for aerobic energy metabolism. With respect to skeletal muscle adaptations, cellular stress and the resultant metabolic signals for mitochondrial biogenesis depend largely on exercise intensity, with limited work suggesting that increases in mitochondrial content are superior after HIIT compared to MICT, at least when matched-work comparisons are made within the same individual. It is well established that SIT increases mitochondrial content to a similar extent to MICT despite a reduced exercise volume. At the whole-body level, V̇O2 max is generally increased more by HIIT than MICT for a given training volume, whereas SIT and MICT similarly improve V̇O2 max despite differences in training volume. There is less evidence available regarding the role of exercise intensity in mediating changes in skeletal muscle capillary density, maximum stroke volume and cardiac output, and blood volume. Furthermore, the interactions between intensity and duration and frequency have not been thoroughly explored. While interval training is clearly a potent stimulus for physiological remodelling in humans, the integrative response to this type of exercise warrants further attention, especially in comparison to traditional endurance training. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

  19. Research of robust adaptive trajectory linearization control based on T-S fuzzy system

    Institute of Scientific and Technical Information of China (English)

    Jiang Changsheng; Zhang Chunyu; Zhu Liang

    2008-01-01

    A robust adaptive trajectory linearization control (RATLC) algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

  20. Robust DTC-SVM Method for Matrix Converter Drives with Model Reference Adaptive Control Scheme

    DEFF Research Database (Denmark)

    Lee, Kyo Beum; Huh, Sunghoi; Sim, Kyung-Hun

    2007-01-01

    strategy using space vector modulations and a deadbeat algorithm in the stator flux reference frame. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a neuro-sliding mode approach based on model reference adaptive control (MRAC). An adaptive observer......This paper presents a new robust DTC-SVM control system for high performance induction motor drives fed by a matrix converter with variable structure - model reference adaptive control scheme (VS-MRAC). It is possible to combine the advantages of matrix converters with the advantages of the DTC...

  1. Global Robust Exponential Stability and Periodic Solutions for Interval Cohen-Grossberg Neural Networks with Mixed Delays

    Directory of Open Access Journals (Sweden)

    Yanke Du

    2013-01-01

    Full Text Available A class of interval Cohen-Grossberg neural networks with time-varying delays and infinite distributed delays is investigated. By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions are established for the existence, uniqueness, and global robust exponential stability of the equilibrium point and the periodic solution to the neural networks. Our results improve some previously published ones. Finally, numerical examples are given to illustrate the feasibility of the theoretical results and further to exhibit that there is a characteristic sequence of bifurcations leading to a chaotic dynamics, which implies that the system admits rich and complex dynamics.

  2. A fast, robust, and simple implicit method for adaptive time-stepping on adaptive mesh-refinement grids

    CERN Document Server

    Benoit, Commercon; Romain, Teyssier

    2014-01-01

    Implicit solvers present strong limitations when used on supercomputing facilities and in particular for adaptive mesh-refinement codes. We present a new method for implicit adaptive time-stepping on adaptive mesh refinement-grids and implementing it in the radiation hydrodynamics solver we designed for the RAMSES code for astrophysical purposes and, more particularly, for protostellar collapse. We briefly recall the radiation hydrodynamics equations and the adaptive time-stepping methodology used for hydrodynamical solvers. We then introduce the different types of boundary conditions (Dirichlet, Neumann, and Robin) that are used at the interface between levels and present our implementation of the new method in the RAMSES code. The method is tested against classical diffusion and radiation hydrodynamics tests, after which we present an application for protostellar collapse. We show that using Dirichlet boundary conditions at level interfaces is a good compromise between robustness and accuracy and that it ca...

  3. Robustness of non-interdependent and interdependent networks against dependent and adaptive attacks

    Science.gov (United States)

    Tyra, Adam; Li, Jingtao; Shang, Yilun; Jiang, Shuo; Zhao, Yanjun; Xu, Shouhuai

    2017-09-01

    Robustness of complex networks has been extensively studied via the notion of site percolation, which typically models independent and non-adaptive attacks (or disruptions). However, real-life attacks are often dependent and/or adaptive. This motivates us to characterize the robustness of complex networks, including non-interdependent and interdependent ones, against dependent and adaptive attacks. For this purpose, dependent attacks are accommodated by L-hop percolation where the nodes within some L-hop (L ≥ 0) distance of a chosen node are all deleted during one attack (with L = 0 degenerating to site percolation). Whereas, adaptive attacks are launched by attackers who can make node-selection decisions based on the network state in the beginning of each attack. The resulting characterization enriches the body of knowledge with new insights, such as: (i) the Achilles' Heel phenomenon is only valid for independent attacks, but not for dependent attacks; (ii) powerful attack strategies (e.g., targeted attacks and dependent attacks, dependent attacks and adaptive attacks) are not compatible and cannot help the attacker when used collectively. Our results shed some light on the design of robust complex networks.

  4. Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

    Science.gov (United States)

    Chen, Tien-Chi; Yu, Chih-Hsien

    2009-07-01

    A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

  5. Modular design of adaptive robust controller for strict-feedback stochastic nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    WANG Jun; XI Hong-sheng; JI Hai-bo; KANG Yu

    2006-01-01

    A modular approach of the estimation-based design in adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters.By using It(o)'s differentiation rule, nonlinear damping and adaptive Backstepping procedure,the input-to-state stable controller of global stabilization in probability is developed,which guarantees that system states are bounded and the system has a robust stabilization.According to Swapping technique,we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed.Transient performance of the system is estimated by the norm of error.Results of simulation show the effectiveness of the control algorithms.The modular design,which has a concise hierarchy,is more flexible and versatile than a Lyapunov-based algorithm.

  6. Decentralized adaptive robust controller design for complex system based on partition of unity

    Institute of Scientific and Technical Information of China (English)

    WANG Wenqing; HAN Chongzhao

    2007-01-01

    A new method for designing decentralized adaptive robust controllers was proposed which focuses on a class of more general uncertain complex systems,using the concept of the partition of unity in differential geometry to deal with system uncertainties.In this method the uncertainty of the system to be controlled was normalized firstly,and then the partition of unity that was subordinated to an open covering of state variables compact set was constructed.Subsequently the approximation was realized by using its property that can approximate nonlinear continuous function with arbitrary precision,and then the decentralized adaptive robust controller of complex systems and adaptive laws of approximate parameter estimation were designed.Compared to existing methods,the proposed algorithm requires simpler assumed conditions and no complicated computations.Simulation result shows that the method is valid.

  7. A Robust Weighted Combination Forecasting Method Based on Forecast Model Filtering and Adaptive Variable Weight Determination

    Directory of Open Access Journals (Sweden)

    Lianhui Li

    2015-12-01

    Full Text Available Medium-and-long-term load forecasting plays an important role in energy policy implementation and electric department investment decision. Aiming to improve the robustness and accuracy of annual electric load forecasting, a robust weighted combination load forecasting method based on forecast model filtering and adaptive variable weight determination is proposed. Similar years of selection is carried out based on the similarity between the history year and the forecast year. The forecast models are filtered to select the better ones according to their comprehensive validity degrees. To determine the adaptive variable weight of the selected forecast models, the disturbance variable is introduced into Immune Algorithm-Particle Swarm Optimization (IA-PSO and the adaptive adjustable strategy of particle search speed is established. Based on the forecast model weight determined by improved IA-PSO, the weighted combination forecast of annual electric load is obtained. The given case study illustrates the correctness and feasibility of the proposed method.

  8. A Bio-Inspired Robust Adaptive Random Search Algorithm for Distributed Beamforming

    CERN Document Server

    Tseng, Chia-Shiang; Lin, Che

    2010-01-01

    A bio-inspired robust adaptive random search algorithm (BioRARSA), designed for distributed beamforming for sensor and relay networks, is proposed in this work. It has been shown via a systematic framework that BioRARSA converges in probability and its convergence time scales linearly with the number of distributed transmitters. More importantly, extensive simulation results demonstrate that the proposed BioRARSA outperforms existing adaptive distributed beamforming schemes by as large as 29.8% on average. This increase in performance results from the fact that BioRARSA can adaptively adjust its sampling stepsize via the "swim" behavior inspired by the bacterial foraging mechanism. Hence, the convergence time of BioRARSA is insensitive to the initial sampling stepsize of the algorithm, which makes it robust against the dynamic nature of distributed wireless networks.

  9. Adaptive Input-Output Linearization Technique for Robust Speed Control of Brush less DC Motor

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyeong Hwa; Baik, In Cheol; Kim, Hyun Soo; Youn, Myung Joong [Korea Advance Institute of Science and Technology, Taejon (Korea, Republic of)

    1997-06-01

    An adaptive input-output linearization technique for a robust speed control of a brush less DC (BLDC) motor is presented. By using this technique, the nonlinear motor model can be effectively linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions caused by the incomplete linearization. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov`s hyper stability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simulations and experiments. (author). 14 refs., 12 figs., 1 tab.

  10. Adaptive Robust Actuator Fault Accommodation for a Class of Uncertain Nonlinear Systems with Unknown Control Gains

    Directory of Open Access Journals (Sweden)

    Yuefei Wu

    2014-01-01

    Full Text Available An adaptive robust fault tolerant control approach is proposed for a class of uncertain nonlinear systems with unknown signs of high-frequency gain and unmeasured states. In the recursive design, neural networks are employed to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unknown sign of the virtual control direction. By incorporating the switching function σ algorithm, the adaptive backstepping scheme developed in this paper does not require the real value of the actuator failure. It is mathematically proved that the proposed adaptive robust fault tolerant control approach can guarantee that all the signals of the closed-loop system are bounded, and the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples.

  11. Nutritional strategies to support adaptation to high-intensity interval training in team sports.

    Science.gov (United States)

    Gibala, Martin J

    2013-01-01

    Team sports are characterized by intermittent high-intensity activity patterns. Typically, play consists of short periods of very intense or all-out efforts interspersed with longer periods of low-intensity activity. Fatigue is a complex, multi-factorial process, but intense intermittent exercise performance can potentially be limited by reduced availability of substrates stored in skeletal muscle and/or metabolic by-products associated with fuel breakdown. High-intensity interval training (HIT) has been shown to induce adaptations in skeletal muscle that enhance the capacity for both oxidative and non-oxidative metabolism. Nutrient availability is a potent modulator of many acute physiological responses to exercise, including various molecular signaling pathways that are believed to regulate cellular adaptation to training. Several nutritional strategies have also been reported to acutely alter metabolism and enhance intermittent high-intensity exercise performance. However, relatively little is known regarding the effect of chronic interventions, and whether supplementation over a period of weeks or months augments HIT-induced physiological remodeling and promotes greater performance adaptations. Theoretically, a nutritional intervention could augment HIT adaptation by improving energy metabolism during exercise, which could facilitate greater total work and an enhanced chronic training stimulus, or promoting some aspect of the adaptive response during recovery, which could lead to enhanced physiological adaptations over time.

  12. The Involvement of Centralized and Distributed Processes in Sub-second Time Interval Adaptation: An ERP Investigation of Apparent Motion.

    Science.gov (United States)

    Kaya, Utku; Yildirim, Fazilet Zeynep; Kafaligonul, Hulusi

    2017-09-09

    Accumulating evidence suggests that the timing of brief stationary sounds affects visual motion perception. Recent studies have shown that auditory time interval can alter apparent motion perception not only through concurrent stimulation but also through brief adaptation. The adaptation aftereffects for auditory time intervals were found to be similar to those for visual time intervals, suggesting the involvement of a central timing mechanism. To understand the nature of cortical processes underlying such aftereffects, we adapted observers to different time intervals by using either brief sounds or visual flashes and examined the evoked activity to the subsequently presented visual apparent motion. Both auditory and visual time interval adaptation led to significant changes in the ERPs elicited by the apparent motion. However, the changes induced by each modality were in the opposite direction. Also, they mainly occurred in different time windows and clustered over distinct scalp sites. The effects of auditory time interval adaptation were centered over parietal and parieto-central electrodes while the visual adaptation effects were mostly over occipital and parieto-occipitial regions. Moreover, the changes were much more salient when sounds were used during the adaptation phase. Taken together, our findings within the context of visual motion point to auditory dominance in the temporal domain and highlight the distinct nature of the sensory processes involved in auditory and visual time interval adaptation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  13. Adaptive integral LOS path following for an unmanned airship with uncertainties based on robust RBFNN backstepping.

    Science.gov (United States)

    Zheng, Zewei; Zou, Yao

    2016-11-01

    This paper investigates the path following control problem for an unmanned airship in the presence of unknown wind and uncertainties. The backstepping technique augmented by a robust adaptive radial basis function neural network (RBFNN) is employed as the main control framework. Based on the horizontal dynamic model of the airship, an improved adaptive integral line-of-sight (LOS) guidance law is first proposed, which suits any parametric paths. The guidance law calculates the desired yaw angle and estimates the wind. Then the controller is extended to cope with the airship yaw tracking and velocity control by resorting to the augmented backstepping technique. The uncertainties of the dynamics are compensated by using the robust RBFNNs. Each robust RBFNN utilizes an nth-order smooth switching function to combine a conventional RBFNN with a robust control. The conventional RBFNN dominates in the neural active region, while the robust control retrieves the transient outside the active region, so that the stability range can be widened. Stability analysis shows that the controlled closed-loop system is globally uniformly ultimately bounded. Simulations are provided to validate the effectiveness of the proposed control approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  14. A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

    Science.gov (United States)

    Chen, Xianshun; Feng, Liang; Ong, Yew Soon

    2012-07-01

    In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

  15. Robust Adaptive Control Design for Rotorcraft Unmanned Aerial Vehicles Based on Sliding Mode Approach

    Institute of Scientific and Technical Information of China (English)

    郭建川; 鲜斌

    2014-01-01

    This paper presents a nonlinear robust control design method for a generic rotorcraft unmanned aerial ve-hicle (RUAV). The control objective is to let the RUAV track some pre-defined time-varying position and heading trajectories. The proposed controller employs feedback linearization process to realize the dynamic decoupling control and applies adaptive sliding mode control to compensate for the parametric uncertainties and external disturbances. The global asymptotical stability is proved via stability analysis. Compared with the cascaded controller, the proposed controller demonstrates a superior tracking performance and robustness through numerical simulation in the presence of parametric uncertainties and unknown disturbances.

  16. Attitude Analysis and Robust Adaptive Backstepping Sliding Mode Control of Spacecrafts Orbiting Irregular Asteroids

    Directory of Open Access Journals (Sweden)

    Chunhui Liang

    2014-01-01

    Full Text Available Attitude stability analysis and robust control algorithms for spacecrafts orbiting irregular asteroids are investigated in the presence of model uncertainties and external disturbances. Rigid spacecraft nonlinear attitude models are considered and detailed attitude stability analysis of spacecraft subjected to the gravity gradient torque in an irregular central gravity field is included in retrograde orbits and direct orbits using linearized system model. The robust adaptive backstepping sliding mode control laws are designed to make the attitude of the spacecrafts stabilized and responded accurately to the expectation in the presence of disturbances and parametric uncertainties. Numerical simulations are included to illustrate the spacecraft performance obtained using the proposed control laws.

  17. Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

    Directory of Open Access Journals (Sweden)

    Zhonghua Wu

    2017-02-01

    Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

  18. Fast and robust online adaptive planning in stereotactic MR-guided adaptive radiation therapy (SMART) for pancreatic cancer.

    Science.gov (United States)

    Bohoudi, O; Bruynzeel, A M E; Senan, S; Cuijpers, J P; Slotman, B J; Lagerwaard, F J; Palacios, M A

    2017-08-12

    To implement a robust and fast stereotactic MR-guided adaptive radiation therapy (SMART) online strategy in locally advanced pancreatic cancer (LAPC). SMART strategy for plan adaptation was implemented with the MRIdian system (ViewRay Inc.). At each fraction, OAR (re-)contouring is done within a distance of 3cm from the PTV surface. Online plan re-optimization is based on robust prediction of OAR dose and optimization objectives, obtained by building an artificial neural network (ANN). Proposed limited re-contouring strategy for plan adaptation (SMART3CM) is evaluated by comparing 50 previously delivered fractions against a standard (re-)planning method using full-scale OAR (re-)contouring (FULLOAR). Plan quality was assessed using PTV coverage (V95%, Dmean, D1cc) and institutional OAR constraints (e.g. V33Gy). SMART3CM required a significant lower number of optimizations than FULLOAR (4 vs 18 on average) to generate a plan meeting all objectives and institutional OAR constraints. PTV coverage with both strategies was identical (mean V95%=89%). Adaptive plans with SMART3CM exhibited significant lower intermediate and high doses to all OARs than FULLOAR, which also failed in 36% of the cases to adhere to the V33Gy dose constraint. SMART3CM approach for LAPC allows good OAR sparing and adequate target coverage while requiring only limited online (re-)contouring from clinicians. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Friction compensation for low velocity control of hydraulic flight motion simulator: A simple adaptive robust approach

    Institute of Scientific and Technical Information of China (English)

    Yao Jianyong; Jiao Zongxia; Han Songshan

    2013-01-01

    Low-velocity tracking capability is a key performance of flight motion simulator (FMS),which is mainly affected by the nonlinear friction force.Though many compensation schemes with ad hoc friction models have been proposed,this paper deals with low-velocity control without friction model,since it is easy to be implemented in practice.Firstly,a nonlinear model of the FMS middle frame,which is driven by a hydraulic rotary actuator,is built.Noting that in the low velocity region,the unmodeled friction force is mainly characterized by a changing-slowly part,thus a simple adaptive law can be employed to learn this changing-slowly part and compensate it.To guarantee the boundedness of adaptation process,a discontinuous projection is utilized and then a robust scheme is proposed.The controller achieves a prescribed output tracking transient performance and final tracking accuracy in general while obtaining asymptotic output tracking in the absence of modeling errors.In addition,a saturated projection adaptive scheme is proposed to improve the globally learning capability when the velocity becomes large,which might make the previous proposed projection-based adaptive law be unstable.Theoretical and extensive experimental results are obtained to verify the high-performance nature of the proposed adaptive robust control strategy.

  20. Robust Adaptive Neural Control of a Class of MIMO Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    HU Tingliang; ZHU Jihong; SUN Zengqi

    2007-01-01

    In this paper we present a robust adaptive control for a class of uncertain continuous time multiple input multiple output (MIMO) nonlinear systems. Multiple multi-layer neural networks are employed to approximate the uncertainty of the nonlinear functions,and robustifying control terms are used to compensate for approximation errors.All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis so that, under appropriate assumptions, semiglobal stability of the closed - loop system is guaranteed, and the tracking error asymptotically converges to zero. Simulations performed on a two-link robot manipulator illustrate the approach and its performance.

  1. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method.

  2. Robust synchronization of chaotic non-autonomous systems using adaptive-feedback control

    Energy Technology Data Exchange (ETDEWEB)

    Lei Youming [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)]. E-mail: leiyouming@nwpu.edu.cn; Xu Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Shen Jianwei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

    2007-01-15

    In this paper, we apply the simple adaptive-feedback control scheme to synchronize a class of chaotic non-autonomous systems. Based on the invariance principle of differential equations, some generic sufficient conditions for global asymptotic synchronization are obtained. Unlike the usual linear feedback, the variable feedback strength is automatically adapted to completely synchronize two identical systems and simple to implement in practice. As illustrative examples, synchronization of two parametrically excited chaotic pendulums and that of two 4D new systems are considered here. Numerical simulations show the proposed method is effective and robust against the effect of noise.

  3. Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

    Science.gov (United States)

    Du, Bing; Ruan, Chun

    With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

  4. Robust Adaptive Beamforming against Signal Steering Vector Mismatch and Jammer Motion

    Directory of Open Access Journals (Sweden)

    Xiaojun Mao

    2015-01-01

    Full Text Available Since adaptive beamformer suffers from output performance degradation in the presence of interference nonstationarity and signal steering vector mismatch, a novel robust null broadening adaptive beamforming is proposed. The proposed method is realized by the combination of projection transform and diagonal loading techniques. First, a new projection matrix with null broadening ability is constructed and then projects the array received data onto the projection matrix. With the diagonal loading technique, a new sample covariance matrix is obtained. The theoretical analysis shows that the projection transform operation can expand the incident direction of the interference and improve orthogonality between the signal-plus-interference and the noise subspaces; thus the proposed beamformer can effectively broaden the jammer null and enhance the null depth. The analytical expressions of the proposed algorithm are also provided, which are efficient and easily solved. Simulation results are presented and demonstrated that the proposed beamformer can provide strong robustness against signal steering vector mismatch and jammer motion.

  5. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    Science.gov (United States)

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme.

  6. A robust adaptive control with unmodeled dynamic for HVDC transmission systems

    Institute of Scientific and Technical Information of China (English)

    YAN Quan; LI Xing-yuan; WANG Lu; LIU Hong-chao; CHEN Shu-beng

    2006-01-01

    Utilizing the feature of quick response of HVDC to improve the performance of AC/DC system has become the emphasis to be researched.This paper introduces firstly the principle of the robust adaptive control of nonlinear systems with unmodeled dynamics,then developed the robust adaptive additional control of HVDC with unmodeled dynamics of generator in order to improve stability of power system.The additional control of HVDC with unmodeled dynamics only uses the local signals and its design is simple,furthermore it can obviously improve the stability of power system in different operational conditions.Experimental results using the presented concepts obtained on single machine infinite bus model are also included.These results prove the efficiency of the control scheme.The design process of controller provided a new idea to design controller by use of simplified model.

  7. A Robust Adaptive Sliding Mode Control for PMLSM with Variable Velocity Profile Over Wide Range

    Directory of Open Access Journals (Sweden)

    Payam Ghaebi Panah

    2015-07-01

    Full Text Available An adaptive robust variable structure speed controller is designed for wide range of desired velocity control of a Permanent Magnet Linear Synchronous Motor (PMLSM. This is performed for comprehensive nonlinear model of PMLSM including non-idealities such as detent force, parameter uncertainty, unpredicted disturbance and nonlinear friction. The proposed method is based on the robust Sliding Mode Control (SMC in combination with an adaptive strategy for a wide range of velocity. The simulation results are provided for the above mentioned comprehensive model of PMLSM with a variable velocity profile. Moreover, as an evaluation criterion, a Proportional-Integral (PI controller is designed whose parameters are optimally tuned by the Particle Swarm Optimization (PSO algorithm for better comparison.

  8. Robust Adaptive Attitude Control for Airbreathing Hypersonic Vehicle with Attitude Constraints and Propulsive Disturbance

    Directory of Open Access Journals (Sweden)

    Jian Fu

    2015-01-01

    Full Text Available A robust adaptive backstepping attitude control scheme, combined with invariant-set-based sliding mode control and fast-nonlinear disturbance observer, is proposed for the airbreathing hypersonic vehicle with attitude constraints and propulsive disturbance. Based on the positive invariant set and backstepping method, an innovative sliding surface is firstly developed for the attitude constraints. And the propulsive disturbance of airbreathing hypersonic vehicle is described as a differential equation which is motivated by attitude angles in this paper. Then, an adaptive fast-nonlinear disturbance observer for the proposed sliding surface is designed to estimate this kind of disturbance. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis method under the developed robust attitude control scheme. Finally, simulation results are given to illustrate the effectiveness of the proposed attitude control scheme.

  9. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    Science.gov (United States)

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used.

  10. Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions

    CERN Document Server

    Kloster, Kyle

    2016-01-01

    Local community detection, the problem of identifying a set of relevant nodes nearby a small set of input seed nodes, is an important graph primitive with a wealth of applications and research activity. Recent approaches include using local spectral information, graph diffusions, and random walks to determine a community from input seeds. As networks grow to billions of nodes and exhibit diverse structures, it is important that community detection algorithms are not only efficient, but also robust to different structural features. Toward this goal, we explore pre-processing techniques and modifications to existing local methods aimed at improving the scalability and robustness of algorithms related to community detection. Experiments show that our modifications improve both speed and quality of existing methods for locating ground truth communities, and are more robust across graphs and communities of varying sizes, densities, and diameters. Our subgraph extraction method uses adaptively selected PageRank par...

  11. Reducing the width of confidence intervals for the difference between two population means by inverting adaptive tests.

    Science.gov (United States)

    O'Gorman, Thomas W

    2016-08-08

    In the last decade, it has been shown that an adaptive testing method could be used, along with the Robbins-Monro search procedure, to obtain confidence intervals that are often narrower than traditional confidence intervals. However, these confidence interval limits require a great deal of computation and some familiarity with stochastic search methods. We propose a method for estimating the limits of confidence intervals that uses only a few tests of significance. We compare these limits to those obtained by a lengthy Robbins-Monro stochastic search and find that the proposed method is nearly as accurate as the Robbins-Monro search. Adaptive confidence intervals that are produced by the proposed method are often narrower than traditional confidence intervals when the distributions are long-tailed, skewed, or bimodal. Moreover, the proposed method of estimating confidence interval limits is easy to understand, because it is based solely on the p-values from a few tests of significance.

  12. Robust distributed control of spacecraft formation flying with adaptive network topology

    Science.gov (United States)

    Shasti, Behrouz; Alasty, Aria; Assadian, Nima

    2017-07-01

    In this study, the distributed six degree-of-freedom (6-DOF) coordinated control of spacecraft formation flying in low earth orbit (LEO) has been investigated. For this purpose, an accurate coupled translational and attitude relative dynamics model of the spacecraft with respect to the reference orbit (virtual leader) is presented by considering the most effective perturbation acceleration forces on LEO satellites, i.e. the second zonal harmonic and the atmospheric drag. Subsequently, the 6-DOF coordinated control of spacecraft in formation is studied. During the mission, the spacecraft communicate with each other through a switching network topology in which the weights of its graph Laplacian matrix change adaptively based on a distance-based connectivity function between neighboring agents. Because some of the dynamical system parameters such as spacecraft masses and moments of inertia may vary with time, an adaptive law is developed to estimate the parameter values during the mission. Furthermore, for the case that there is no knowledge of the unknown and time-varying parameters of the system, a robust controller has been developed. It is proved that the stability of the closed-loop system coupled with adaptation in network topology structure and optimality and robustness in control is guaranteed by the robust contraction analysis as an incremental stability method for multiple synchronized systems. The simulation results show the effectiveness of each control method in the presence of uncertainties and parameter variations. The adaptive and robust controllers show their superiority in reducing the state error integral as well as decreasing the control effort and settling time.

  13. Guidance and adaptive-robust attitude & orbit control of a small information satellite

    Science.gov (United States)

    Somov, Ye.; Butyrin, S.; Somov, S.; Somova, T.; Testoyedov, N.; Rayevsky, V.; Titov, G.; Yakimov, Ye.; Ovchinnikov, A.; Mathylenko, M.

    2017-01-01

    We consider a small information satellite which may be placed on an orbit with altitude from 600 up to 1000 km. The satellite attitude and orbit control system contains a strap-down inertial navigation system, cluster of four reaction wheels, magnetic driver and a correcting engine unit with eight electro-reaction engines. We study problems on design of algorithms for spatial guidance, in-flight identification and adaptive-robust control of the satellite motion on sun-synchronous orbit.

  14. Robust Penalty Adaptive Model Predictive Control (PAMPC) of constrained, underdamped, non-collocated systems

    OpenAIRE

    Dutta, Abhishek; Ionescu, Clara-Mihaela; Loccufier, Mia; De Keyser, Robain

    2016-01-01

    This paper investigates the control challenges posed by noncollocated mechatronic systems and motivates the need for a model-based control technique towards such systems. A novel way of online constraint handling by penalty adaptation (PAMPC) is proposed and shown to be of particular relevance towards robust control of underdamped, noncollocated systems by exploiting the structure of such systems. Further, a new tunneling approach is proposed for PAMPC to maintain feasibility under uncertaint...

  15. Robust Nearfield Wideband Beamforming Design Based on Adaptive-Weighted Convex Optimization

    Directory of Open Access Journals (Sweden)

    Guo Ye-Cai

    2017-01-01

    Full Text Available Nearfield wideband beamformers for microphone arrays have wide applications in multichannel speech enhancement. The nearfield wideband beamformer design based on convex optimization is one of the typical representatives of robust approaches. However, in this approach, the coefficient of convex optimization is a constant, which has not used all the freedom provided by the weighting coefficient efficiently. Therefore, it is still necessary to further improve the performance. To solve this problem, we developed a robust nearfield wideband beamformer design approach based on adaptive-weighted convex optimization. The proposed approach defines an adaptive-weighted function by the adaptive array signal processing theory and adjusts its value flexibly, which has improved the beamforming performance. During each process of the adaptive updating of the weighting function, the convex optimization problem can be formulated as a SOCP (Second-Order Cone Program problem, which could be solved efficiently using the well-established interior-point methods. This method is suitable for the case where the sound source is in the nearfield range, can work well in the presence of microphone mismatches, and is applicable to arbitrary array geometries. Several design examples are presented to verify the effectiveness of the proposed approach and the correctness of the theoretical analysis.

  16. A robust adaptive sampling method for faster acquisition of MR images.

    Science.gov (United States)

    Vellagoundar, Jaganathan; Machireddy, Ramasubba Reddy

    2015-06-01

    A robust adaptive k-space sampling method is proposed for faster acquisition and reconstruction of MR images. In this method, undersampling patterns are generated based on magnitude profile of a fully acquired 2-D k-space data. Images are reconstructed using compressive sampling reconstruction algorithm. Simulation experiments are done to assess the performance of the proposed method under various signal-to-noise ratio (SNR) levels. The performance of the method is better than non-adaptive variable density sampling method when k-space SNR is greater than 10dB. The method is implemented on a fully acquired multi-slice raw k-space data and a quality assurance phantom data. Data reduction of up to 60% is achieved in the multi-slice imaging data and 75% is achieved in the phantom imaging data. The results show that reconstruction accuracy is improved over non-adaptive or conventional variable density sampling method. The proposed sampling method is signal dependent and the estimation of sampling locations is robust to noise. As a result, it eliminates the necessity of mathematical model and parameter tuning to compute k-space sampling patterns as required in non-adaptive sampling methods. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Adaptive Kalman Filter Based on Adjustable Sampling Interval in Burst Detection for Water Distribution System

    Directory of Open Access Journals (Sweden)

    Doo Yong Choi

    2016-04-01

    Full Text Available Rapid detection of bursts and leaks in water distribution systems (WDSs can reduce the social and economic costs incurred through direct loss of water into the ground, additional energy demand for water supply, and service interruptions. Many real-time burst detection models have been developed in accordance with the use of supervisory control and data acquisition (SCADA systems and the establishment of district meter areas (DMAs. Nonetheless, no consideration has been given to how frequently a flow meter measures and transmits data for predicting breaks and leaks in pipes. This paper analyzes the effect of sampling interval when an adaptive Kalman filter is used for detecting bursts in a WDS. A new sampling algorithm is presented that adjusts the sampling interval depending on the normalized residuals of flow after filtering. The proposed algorithm is applied to a virtual sinusoidal flow curve and real DMA flow data obtained from Jeongeup city in South Korea. The simulation results prove that the self-adjusting algorithm for determining the sampling interval is efficient and maintains reasonable accuracy in burst detection. The proposed sampling method has a significant potential for water utilities to build and operate real-time DMA monitoring systems combined with smart customer metering systems.

  18. Robust Adaptive Fuzzy Output Tracking Control for a Class of Twin-Roll Strip Casting Systems

    Directory of Open Access Journals (Sweden)

    Yu-Jun Zhang

    2017-01-01

    Full Text Available This paper is concerned with the adaptive fuzzy control problem for a class of twin-roll strip casting systems. By using fuzzy logic systems (FLSs to approximate the compounded nonlinear functions, a novel robust output tracking controller with adaptation laws is designed based on the high gain observer. First, the nonlinear dynamic equations for the roll gap and the molten steel level are constructed, respectively. Then, the mean value theorem is employed to transform the nonaffine nonlinear systems to the corresponding affine nonlinear systems. Moreover, it is also proved that all the closed-loop signals are bounded and the systems output tracking errors can converge to the desired neighborhoods of the origin via the Lyapunov stability analysis. Finally, simulation results, based on semiexperimental system dynamic model and parameters, are worked out to show the effectiveness of the proposed adaptive fuzzy design method.

  19. Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores

    CERN Document Server

    Halim, Felix; Karras, Panagiotis; Yap, Roland H C

    2012-01-01

    Modern business applications and scientific databases call for inherently dynamic data storage environments. Such environments are characterized by two challenging features: (a) they have little idle system time to devote on physical design; and (b) there is little, if any, a priori workload knowledge, while the query and data workload keeps changing dynamically. In such environments, traditional approaches to index building and maintenance cannot apply. Database cracking has been proposed as a solution that allows on-the-fly physical data reorganization, as a collateral effect of query processing. Cracking aims to continuously and automatically adapt indexes to the workload at hand, without human intervention. Indexes are built incrementally, adaptively, and on demand. Nevertheless, as we show, existing adaptive indexing methods fail to deliver workload-robustness; they perform much better with random workloads than with others. This frailty derives from the inelasticity with which these approaches interpret...

  20. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

  1. A robust adaptive nonlinear fault-tolerant controller via norm estimation for reusable launch vehicles

    Science.gov (United States)

    Hu, Chaofang; Gao, Zhifei; Ren, Yanli; Liu, Yunbing

    2016-11-01

    In this paper, a reusable launch vehicle (RLV) attitude control problem with actuator faults is addressed via the robust adaptive nonlinear fault-tolerant control (FTC) with norm estimation. Firstly, the accurate tracking task of attitude angles in the presence of parameter uncertainties and external disturbances is considered. A fault-free controller is proposed using dynamic surface control (DSC) combined with fuzzy adaptive approach. Furthermore, the minimal learning parameter strategy via norm estimation technique is introduced to reduce the multi-parameter adaptive computation burden of fuzzy approximation of the lump uncertainties. Secondly, a compensation controller is designed to handle the partial loss fault of actuator effectiveness. The unknown maximum eigenvalue of actuator efficiency loss factors is estimated online. Moreover, stability analysis guarantees that all signals of the closed-loop control system are semi-global uniformly ultimately bounded. Finally, illustrative simulations show the effectiveness of the proposed method.

  2. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

  3. Cross-coupling integral adaptive robust posture control of a pneumatic parallel platform

    Institute of Scientific and Technical Information of China (English)

    左赫; 陶国良

    2016-01-01

    A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-based controller designed. The pneumatic muscles were controlled by three proportional position valves, and the air cylinder was controlled by a proportional pressure valve. As the forward kinematics of this structure had no analytical solution, the control strategy should be designed in joint space. A cross-coupling integral adaptive robust controller (CCIARC) which combined cross-coupling control strategy and traditional adaptive robust control (ARC) theory was developed by back-stepping method to accomplish trajectory tracking control of the parallel platform. The cross-coupling part of the controller stabilized the length error in joint space as well as the synchronization error, and the adaptive robust control part attenuated the adverse effects of modelling error and disturbance. The force character of the pneumatic muscles was difficult to model precisely, so the on-line recursive least square estimation (RLSE) method was employed to modify the model compensation. The projector mapping method was used to condition the RLSE algorithm to bound the parameters estimated. An integral feedback part was added to the traditional robust function to reduce the negative influence of the slow time-varying characteristic of pneumatic muscles and enhance the ability of trajectory tracking. The stability of the controller designed was proved through Laypunov’s theory. Various contrast controllers were designed to testify the newly designed components of the CCIARC. Extensive experiments were conducted to illustrate the performance of the controller.

  4. Effects of Short-Interval and Long-Interval Swimming Protocols on Performance, Aerobic Adaptations, and Technical Parameters: A Training Study.

    Science.gov (United States)

    Dalamitros, Athanasios A; Zafeiridis, Andreas S; Toubekis, Argyris G; Tsalis, George A; Pelarigo, Jailton G; Manou, Vasiliki; Kellis, Spiridon

    2016-10-01

    Dalamitros, AA, Zafeiridis, AS, Toubekis, AG, Tsalis, GA, Pelarigo, JG, Manou, V, and Kellis, S. Effects of short-interval and long-interval swimming protocols on performance, aerobic adaptations, and technical parameters: A training study. J Strength Cond Res 30(10): 2871-2879, 2016-This study compared 2-interval swimming training programs of different work interval durations, matched for total distance and exercise intensity, on swimming performance, aerobic adaptations, and technical parameters. Twenty-four former swimmers were equally divided to short-interval training group (INT50, 12-16 × 50 m with 15 seconds rest), long-interval training group (INT100, 6-8 × 100 m with 30 seconds rest), and a control group (CON). The 2 experimental groups followed the specified swimming training program for 8 weeks. Before and after training, swimming performance, technical parameters, and indices of aerobic adaptations were assessed. ΙΝΤ50 and ΙΝΤ100 improved swimming performance in 100 and 400-m tests and the maximal aerobic speed (p ≤ 0.05); the performance in the 50-m swim did not change. Posttraining V[Combining Dot Above]O2max values were higher compared with pretraining values in both training groups (p ≤ 0.05), whereas peak aerobic power output increased only in INT100 (p ≤ 0.05). The 1-minute heart rate and blood lactate recovery values decreased after training in both groups (p training in both groups (p ≤ 0.05); no changes were observed in stroke rate after training. Comparisons between groups on posttraining mean values, after adjusting for pretraining values, revealed no significant differences between ΙΝΤ50 and ΙΝΤ100 for all variables; however, all measures were improved vs. the respective values in the CON (p training.

  5. Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

    Science.gov (United States)

    Zhang, Qichao; Zhao, Dongbin; Wang, Ding

    2016-10-18

    In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

  6. Pressure observer based adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic muscles

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system,and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO)coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.

  7. Assistance using adaptive oscillators: robustness to errors in the identification of the limb parameters.

    Science.gov (United States)

    Rinderknecht, Mike Domenik; Delaloye, Fabien André; Crespi, Alessandro; Ronsse, Renaud; Ijspeert, Auke Jan

    2011-01-01

    This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify. © 2011 IEEE

  8. Robust Fixed Point Transformations in Adaptive Control Using Local Basin of Attraction

    Directory of Open Access Journals (Sweden)

    József K. Tar

    2009-03-01

    Full Text Available A further step towards a novel approach to adaptive nonlinear control developedat Budapest Tech in the past few years is reported. This approach obviates the use of thecomplicated Lyapunov function technique that normally provides global stability ofconvergence at the costs of both formal and essential restrictions, by applying Cauchysequences of local, bounded basin of attraction in an iterative control that is free of suchrestrictions. Its main point is the creation of a robust iterative sequence that only slightlydepends on the features of the controlled system and mainly is determined be the controlparameters applied. It is shown that as far as its operation is considered the proposedmethod can be located between the robust Variable Structure / Sliding Mode and theadaptive Slotine-Li control in the case of robots or other Classical Mechanical Systems.The operation of these method is comparatively analyzed for a wheel + connected masssystem in which this latter component is “stabilized” along one of the spokes of the wheelin the radial direction by an elastic spring. The robustness of these methods is alsoinvestigated againts unknown external disturbances of quite significant amplitudes. Thenumerical simulations substantiate the superiority of the robust fixed point transformationsin the terms of accuracy, simplicity, and smoothness of the control signals applied.

  9. Fuzzy adaptive robust control for space robot considering the effect of the gravity

    Directory of Open Access Journals (Sweden)

    Qin Li

    2014-12-01

    Full Text Available Space robot is assembled and tested in gravity environment, and completes on-orbit service (OOS in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control (FARC strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative (PD controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

  10. Fuzzy adaptive robust control for space robot considering the effect of the gravity

    Institute of Scientific and Technical Information of China (English)

    Qin Li; Liu Fucai; Liang Lihuan; Gao Jingfang

    2014-01-01

    Space robot is assembled and tested in gravity environment, and completes on-orbit service (OOS) in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control (FARC) strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative (PD) controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

  11. Robust Adaptive Beamforming for Multiple Signals of Interest with Cycle Frequency Error

    Directory of Open Access Journals (Sweden)

    Huang Chia-Cheng

    2010-01-01

    Full Text Available This paper deals with the problem of robust adaptive array beamforming by exploiting the signal cyclostationarity. Recently, a novel cyclostationarity-exploiting beamforming method has been proposed by J.-H. Lee and C.-C. Huang (2009 for dealing with the situation of multiple signals of interest (SOI based on the LS-SCORE algorithm. This method is referred to as the multiple LS-SCORE (MLS-SCORE algorithm. However, the MLS-SCORE algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequencies of the SOIs. In this paper, we evaluate the performance of the MLS-SCORE algorithm in the presence of cycle frequency error (CFE. The output SINR of an adaptive beamforming using the MLS-SCORE algorithm deteriorates like a function as the number of data snapshots increases. To tackle this difficulty, we present an efficient method to find an appropriate estimate for each of the cycle frequencies of the SOIs iteratively to achieve robust adaptive beamforming against the CFE. Simulation results for showing the effectiveness of the proposed method are provided.

  12. Adaptive robust vibration control with input shaping as a flexible maneuver strategy

    Energy Technology Data Exchange (ETDEWEB)

    Sung, Yoon Gyeoung [KAERI, Taejon (Korea, Republic of)

    1999-11-01

    An adaptive robust control is presented for the vibration reduction of a flexible spacecraft by combining the input shaping technique with the sliding-mode control. The combined approach appears to be robust in the presence of a severe disturbance and an unknown parameter which will be estimated by on-line least-square method. As a maneuver strategy, it is found that a synthesized trajectory with a combination of low-frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid-body trajectory alone which many researchers have employed. The feasibility of the vibration control approach is demonstrated by applying it to a benchmark problem in aerospace. For the applications of the proposed technique to realistic flexible spacecraft systems, several requirements are discussed such as mode stabilization and enormously large system order.

  13. Robust Adaptive Sliding Mode Consensus of Multiagent Systems with Perturbed Communications and Actuators

    Directory of Open Access Journals (Sweden)

    Xiao-Zheng Jin

    2013-01-01

    Full Text Available This paper deals with the asymptotic consensus problem for a class of multiagent systems with time-varying additive actuator faults and perturbed communications. The L2 performance of systems is also considered in the consensus controller designs. The upper and lower bounds of faults and perturbations in actuators and communications and controller gains are assumed to be unknown but can be estimated by designing some indirect adaptive laws. Based on the information from the adaptive estimation mechanism, the distributed robust adaptive sliding mode controllers are constructed to automatically compensate for the effects of faults and perturbations and to achieve any given level of L2 gain attenuation from external disturbance to consensus errors. Through Lyapunov functions and adaptive schemes, the asymptotic consensus of resulting adaptive multiagent system can be achieved with a specified performance criterion in the presence of perturbed communications and actuators. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of F-18 aircraft.

  14. Hormonal and Physiological Adaptations to High-Intensity Interval Training in Professional Male Canoe Polo Athletes.

    Science.gov (United States)

    Sheykhlouvand, Mohsen; Khalili, Erfan; Agha-Alinejad, Hamid; Gharaat, Mohammadali

    2016-03-01

    This study compared the effects of 2 different high-intensity interval training (HIIT) programs in professional male canoe polo athletes. Responses of peak oxygen uptake (VO2peak), ventilatory threshold (VT), peak and mean anaerobic power output (PPO and MPO), blood volume, and hormonal adaptations to HIIT were examined. Male athletes (n = 21, age: 24 ± 3 years; height: 181 ± 4 cm; mass: 85 ± 6 kg; and body fat: 12.9 ± 2.7%) were randomly assigned to one of 3 groups (N = 7): (a) (G1) interval paddling with variable volume (6, 7, 8, 9, 9, 9, 8, 7, 6 repetitions per session from first to ninth session, respectively) × 60 second at lowest velocity that elicited VO2peak (vVO2peak), 1:3 work to recovery ratio; (b) (G2) interval paddling with variable intensity (6 × 60 second at 100, 110, 120, 130, 130, 130, 120, 110, 100% vVO2peak from first to ninth session, respectively, 1:3 work to recovery); and (c) (GCON) the control group performed three 60 minutes paddling sessions (75% vVO2peak) per week for 3 weeks. High-intensity interval training resulted in significant (except as shown) increases compared with pretest, in VO2peak (G1 = +8.8% and G2 = +8.5%), heart rate at VT (b·min) (G1 = +9.7% and G2 = +5.9%) and (%maximum) (G1 = +6.9%; p = 0.29 and G2 = +6.5%), PPO (G1 = +9.7% and G2 = +12.2%), MPO (G1 = +11.1%; p = 0.29 and G2 = +16.2%), total testosterone (G1 = +29.4% and G2 = +16.7%), total testosterone/cortisol ratio (G1 = +40.9% and G2 = +28.1%), and mean corpuscular hemoglobin (G1 = +1.7% and G2 = +1.3%). No significant changes were found in GCON. High-intensity interval paddling may improve both aerobic and anaerobic performances in professional male canoe polo athletes under the conditions of this study.

  15. Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter.

    Science.gov (United States)

    Zeghlache, Samir; Benslimane, Tarak; Bouguerra, Abderrahmen

    2017-09-14

    In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter. The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller. Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Robust adaptive fuzzy control for a class of perturbed pure-feedback nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    Jianjiang YU; Tianping ZHANG; Haijun GU

    2004-01-01

    A new design scheme of direct adaptive fuzzy controller for a class of perturbed pure-feedback nonlinear systems is proposed. The design is based on backstepping and the approximation capability of the first type fuzzy systems. A continuous robust term is adopted to minif-y the influence of modeling errors or disturbances. By introducing the modified integral-type Lyapunov function, the approach is able to avoid the requirement of the upper bound of the first time derivation of the high frequency control gain. Through theoretical analysis, the closed-loop control system is proven to be semi-globally uniformly ultimately bounded, with tracking error converging to a residual set.

  17. Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting

    DEFF Research Database (Denmark)

    Xu, Man; Pinson, Pierre; Lu, Zongxiang

    2016-01-01

    swiftly and also achieve a better trade-off between robustness against noisy data and time adaptivity. A case study based on a real-world dataset validates the properties of the proposed regression method. Results show that the new method could flexibly respond to abnormal data at different lead times...... of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady-state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because...

  18. DESIGN OF ROBUST COMMAND TO LINE-OF-SIGHT GUIDANCE LAW: A FUZZY ADAPTIVE APPROACH

    Directory of Open Access Journals (Sweden)

    ESMAIL SADEGHINASAB

    2016-11-01

    Full Text Available In this paper, the design of command to line-of-sight (CLOS missile guidance law is addressed. Taking a three dimensional guidance model, the tracking control problem is formulated. To solve the target tracking problem, the feedback linearization controller is first designed. Although such control scheme possesses the simplicity property, but it presents the acceptable performance only in the absence of perturbations. In order to ensure the robustness properties against model uncertainties, a fuzzy adaptive algorithm is proposed with two parts including a fuzzy (Mamdani system, whose rules are constructed based on missile guidance, and a so-called rule modifier to compensate the fuzzy rules, using the negative gradient method. Compared with some previous works, such control strategy provides a faster time response without large control efforts. The performance of feedback linearization controller is also compared with that of fuzzy adaptive strategy via various simulations.

  19. Adaptive robust dissipative designs on straight path control for underactuated ships

    Institute of Scientific and Technical Information of China (English)

    Li Tieshan; Yang Yansheng; Hong Biguang

    2006-01-01

    An adaptive robust control algorithm for ship straight path control system in the presence of both modeling uncertainties and the bounded disturbances is proposed. Motivated by the backstepping approach, the algorithm is developed by using the dissipation theory, such that the resulting closed-loop system is both strictly dissipative and asymptotically adaptively stable for all admissible uncertainties. Also, it is able to steer an underactuated ship along a prescribed straight path with ultimate bounds under external disturbances induced by wave, wind and ocean current. When there are no disturbances, the straight path control can be implemented in a locally asymptotically stable manner. Simulation results on an ocean-going training ship ‘YULONG’ are presented to validate the effectiveness of the algorithm.

  20. Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance training in humans.

    Science.gov (United States)

    Burgomaster, Kirsten A; Howarth, Krista R; Phillips, Stuart M; Rakobowchuk, Mark; Macdonald, Maureen J; McGee, Sean L; Gibala, Martin J

    2008-01-01

    Low-volume 'sprint' interval training (SIT) stimulates rapid improvements in muscle oxidative capacity that are comparable to levels reached following traditional endurance training (ET) but no study has examined metabolic adaptations during exercise after these different training strategies. We hypothesized that SIT and ET would induce similar adaptations in markers of skeletal muscle carbohydrate (CHO) and lipid metabolism and metabolic control during exercise despite large differences in training volume and time commitment. Active but untrained subjects (23 +/- 1 years) performed a constant-load cycling challenge (1 h at 65% of peak oxygen uptake (.VO(2peak)) before and after 6 weeks of either SIT or ET (n = 5 men and 5 women per group). SIT consisted of four to six repeats of a 30 s 'all out' Wingate Test (mean power output approximately 500 W) with 4.5 min recovery between repeats, 3 days per week. ET consisted of 40-60 min of continuous cycling at a workload that elicited approximately 65% (mean power output approximately 150 W) per day, 5 days per week. Weekly time commitment (approximately 1.5 versus approximately 4.5 h) and total training volume (approximately 225 versus approximately 2250 kJ week(-1)) were substantially lower in SIT versus ET. Despite these differences, both protocols induced similar increases (P < 0.05) in mitochondrial markers for skeletal muscle CHO (pyruvate dehydrogenase E1alpha protein content) and lipid oxidation (3-hydroxyacyl CoA dehydrogenase maximal activity) and protein content of peroxisome proliferator-activated receptor-gamma coactivator-1alpha. Glycogen and phosphocreatine utilization during exercise were reduced after training, and calculated rates of whole-body CHO and lipid oxidation were decreased and increased, respectively, with no differences between groups (all main effects, P < 0.05). Given the markedly lower training volume in the SIT group, these data suggest that high-intensity interval training is a time

  1. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

    Directory of Open Access Journals (Sweden)

    Haiying Zhao

    2016-07-01

    Full Text Available Visual odometry (VO estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD, to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms.

  2. Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

    Science.gov (United States)

    Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.

    1996-01-01

    Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

  3. Speech Waveform Compression Using Robust Adaptive Voice Activity Detection for Nonstationary Noise

    Directory of Open Access Journals (Sweden)

    Hsiao-Chun Wu

    2008-03-01

    Full Text Available The voice activity detection (VAD is crucial in all kinds of speech applications. However, almost all existing VAD algorithms suffer from the nonstationarity of both speech and noise. To combat this difficulty, we propose a new voice activity detector, which is based on the Mel-energy features and an adaptive threshold related to the signal-to-noise ratio (SNR estimates. In this paper, we first justify the robustness of the Bayes classifier using the Mel-energy features over that using the Fourier spectral features in various noise environments. Then, we design an algorithm using the dynamic Mel-energy estimator and the adaptive threshold, which depends on the SNR estimates. In addition, a realignment scheme is incorporated to correct the sparse-and-spurious noise estimates. Numerous simulations are carried out to evaluate the performance of our proposed VAD method and the comparisons are made with a couple of existing representative schemes, namely, the VAD using the likelihood ratio test with Fourier spectral energy features and that based on the enhanced time-frequency parameters. Three types of noises, namely, white noise (stationary, babble noise (nonstationary, and vehicular noise (nonstationary were artificially added by the computer for our experiments. As a result, our proposed VAD algorithm significantly outperforms other existing methods as illustrated by the corresponding receiver operating characteristics (ROC curves. Finally, we demonstrate one of the major applications, namely, speech waveform compression associated with our new robust VAD scheme and quantify the effectiveness in terms of compression efficiency.

  4. Simple robust control laws for robot manipulators. Part 1: Non-adaptive case

    Science.gov (United States)

    Wen, J. T.; Bayard, D. S.

    1987-01-01

    A new class of exponentially stabilizing control laws for joint level control of robot arms is introduced. It has been recently recognized that the nonlinear dynamics associated with robotic manipulators have certain inherent passivity properties. More specifically, the derivation of the robotic dynamic equations from the Hamilton's principle gives rise to natural Lyapunov functions for control design based on total energy considerations. Through a slight modification of the energy Lyapunov function and the use of a convenient lemma to handle third order terms in the Lyapunov function derivatives, closed loop exponential stability for both the set point and tracking control problem is demonstrated. The exponential convergence property also leads to robustness with respect to frictions, bounded modeling errors and instrument noise. In one new design, the nonlinear terms are decoupled from real-time measurements which completely removes the requirement for on-line computation of nonlinear terms in the controller implementation. In general, the new class of control laws offers alternatives to the more conventional computed torque method, providing tradeoffs between robustness, computation and convergence properties. Furthermore, these control laws have the unique feature that they can be adapted in a very simple fashion to achieve asymptotically stable adaptive control.

  5. Adaptive robust stabilisation for a class of uncertain nonlinear time-delay dynamical systems

    Science.gov (United States)

    Wu, Hansheng

    2013-02-01

    The problem of adaptive robust stabilisation is considered for a class of uncertain nonlinear dynamical systems with multiple time-varying delays. It is assumed that the upper bounds of the nonlinear delayed state perturbations are unknown and that the time-varying delays are any non-negative continuous and bounded functions which do not require that their derivatives have to be less than one. In particular, it is only required that the nonlinear uncertainties, which can also include time-varying delays, are bounded in any non-negative nonlinear functions which are not required to be known for the system designer. For such a class of uncertain nonlinear time-delay systems, a new method is presented whereby a class of continuous memoryless adaptive robust state feedback controllers with a rather simpler structure is proposed. It is also shown that the solutions of uncertain nonlinear time-delay systems can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, as an application, an uncertain nonlinear time-delay ecosystem with two competing species is given to demonstrate the validity of the results.

  6. Robust adaptive fuzzy neural tracking control for a class of unknown chaotic systems

    Indian Academy of Sciences (India)

    Abdurahman Kadir; Xing-Yuan Wang; Yu-Zhang Zhao

    2011-06-01

    In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal controller. The FNNI is used for online estimation of the controlled system dynamics by tuning the parameters of fuzzy neural network (FNN). The Gaussian function, a specific example of radial basis function, is adopted here as a membership function. So, the tuning parameters include the weighting factors in the consequent part and the means and variances of the Gaussian membership functions in the antecedent part of fuzzy implications. To tune the parameters online, the back-propagation (BP) algorithm is developed. The robust controller is used to guarantee the stability and to control the performance of the closed-loop adaptive system, which is achieved always. Finally, simulation results show that the AFNC can achieve favourable tracking performances.

  7. Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system.

    Science.gov (United States)

    Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai

    2009-06-01

    In this paper, a robust dynamic sliding mode control system (RDSMC) using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a magnetic levitation system considering the uncertainties. First, a dynamic model of the magnetic levitation system is derived. Then, a proportional-integral-derivative (PID)-type sliding-mode control system (SMC) is adopted for tracking of the reference trajectories. Moreover, a new PID-type dynamic sliding-mode control system (DSMC) is proposed to reduce the chattering phenomenon. However, due to the hardware being limited and the uncertainty bound being unknown of the switching function for the DSMC, an RDSMC is proposed to improve the control performance and further increase the robustness of the magnetic levitation system. In the RDSMC, an RENN estimator is used to estimate an unknown nonlinear function of lumped uncertainty online and replace the switching function in the hitting control of the DSMC directly. The adaptive learning algorithms that trained the parameters of the RENN online are derived using Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher order terms in Taylor series. Finally, some experimental results of tracking the various periodic trajectories demonstrate the validity of the proposed RDSMC for practical applications.

  8. Robust Adaptive Sliding Mode Control for Generalized Function Projective Synchronization of Different Chaotic Systems with Unknown Parameters

    Directory of Open Access Journals (Sweden)

    Xiuchun Li

    2013-01-01

    Full Text Available When the parameters of both drive and response systems are all unknown, an adaptive sliding mode controller, strongly robust to exotic perturbations, is designed for realizing generalized function projective synchronization. Sliding mode surface is given and the controlled system is asymptotically stable on this surface with the passage of time. Based on the adaptation laws and Lyapunov stability theory, an adaptive sliding controller is designed to ensure the occurrence of the sliding motion. Finally, numerical simulations are presented to verify the effectiveness and robustness of the proposed method even when both drive and response systems are perturbed with external disturbances.

  9. A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

    Science.gov (United States)

    Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

    2013-05-01

    This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

  10. View-invariant human action recognition via robust locally adaptive multi-view learning

    Institute of Scientific and Technical Information of China (English)

    Jia-geng FENG; Jun XIAO

    2015-01-01

    Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition;e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e.,>60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6%improvement in recognition accuracy on the three datasets.

  11. Robust adaptive control for a nonholonomic mobile robot with unknown parameters

    Institute of Scientific and Technical Information of China (English)

    Jinbo WU; Guohua XU; Zhouping YIN

    2009-01-01

    A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.

  12. Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

    Science.gov (United States)

    Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

    2015-11-01

    Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

  13. Climate Change Impacts on Transportation; Groundwater Elevation, Road Performance, and Robust Adaptation

    Science.gov (United States)

    Kirshen, P. H.; Knott, J. F.; Ray, P.; Elshaer, M.; Daniel, J.; Jacobs, J. M.

    2016-12-01

    Transportation climate change vulnerability and adaptation studies have primarily focused on surface-water flooding from sea-level rise (SLR); little attention has been given to the effects of climate change and SLR on groundwater and subsequent impacts on the unbound foundation layers of coastal-road infrastructure. The magnitude of service-life reduction depends on the height of the groundwater in the unbound pavement materials, the pavement structure itself, and the loading. Using a steady-state groundwater model, and a multi-layer elastic pavement evaluation model, the strain changes in the layers can be determined as a function of parameter values and the strain changes translated into failure as measured by number of loading cycles to failure. For a section of a major coastal road in New Hampshire, future changes in sea-level, precipitation, temperature, land use, and groundwater pumping are characterized by deep uncertainty. Parameters that describe the groundwater system such as hydraulic conductivity can be probabilistically described while road characteristics are assumed to be deterministic. To understand the vulnerability of this road section, a bottom-up planning approach was employed over time where the combinations of parameter values that cause failure were determined and their plausibility of their occurring was analyzed. To design a robust adaptation strategy that will function reasonably well in the present and the future given the large number of uncertain parameter values, performance of adaptation options were investigated. Adaptation strategies that were considered include raising the road, load restrictions, increasing pavement layer thicknesses, replacing moisture-sensitive materials with materials that are not moisture sensitive, improving drainage systems, and treatment of the underlying materials.

  14. Research on the Robustness of an Adaptive PID Control of a Kind of Supersonic Missile

    Directory of Open Access Journals (Sweden)

    Gangling Jiao

    2013-01-01

    Full Text Available In this study, the dynamic characteristic of missile system is viewed as a two-loop system, such as inner loop and outer loop and we design an adaptive PID control strategy for the pitch channel linear model of supersonic missile. The robustness of a double PID controller is analyzed by changing the aerodynamic coefficients. The control law is testified to be stable even the aerodynamic coefficients are changed between 0.7 and 1.7 times of its standard value and the control effect is compared with the sliding mode control strategy. Also the advantage and defect of both control strategy are summarized at the end of this study.

  15. Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

    Directory of Open Access Journals (Sweden)

    Yan Ren

    2013-01-01

    Full Text Available A structure mode of virtual compound-axis servo system is proposed to improve the tracking accuracy of the ordinary optoelectric tracking platform. It is based on the structure and principles of compound-axis servo system. A hybrid position control scheme combining the PD controller and feed-forward controller is used in subsystem to track the tracking error of the main system. This paper analyzes the influences of the equivalent disturbance in main system and proposes an adaptive sliding mode robust control method based on the improved disturbance observer. The sliding mode technique helps this disturbance observer to deal with the uncompensated disturbance in high frequency by making use of the rapid switching control value, which is based on the subtle error of disturbance estimation. Besides, the high-frequency chattering is alleviated effectively in this proposal. The effectiveness of the proposal is confirmed by experiments on optoelectric tracking platform.

  16. Biologically inspired control of humanoid robot arms robust and adaptive approaches

    CERN Document Server

    Spiers, Adam; Herrmann, Guido

    2016-01-01

    This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approaches proposed here promote human-like motion with better exploitation of the robot’s physical structure. This also benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models. The operational-space method of robot control forms the basis of many of the techniqu...

  17. Adaptive-robust Control of a Smart Beam with Support Excitation Using Piezoelectric Layers

    Directory of Open Access Journals (Sweden)

    Mohammad Azadi

    2013-04-01

    Full Text Available In this paper, vibrations of a beam with support excitation and a tip mass are suppressed using piezoelectric layers. The beam is fixed to a motion support from one end and the other end is free with an attached mass. The beam is considered as an Euler-Bernoulli beam. The governing equations of motion are derived based on the generalized function theory and Lagrange-Rayleigh-Ritz technique. An adaptive-robust control scheme is applied to control the vibrations of the beam. The mathematical modelling of the beam with control algorithm is derived and in purpose to study the effect of the amount of tip mass, size and location of the piezoelectric layers and the type of the support excitation on the beam vibrations, the system is simulated. Finally, the results of simulation are presented.

  18. ISS-based robust adaptive fuzzy algorithm for maintaining a ship's track

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper focuses on the problem of linear track keeping for marine surface vessels.The influence exerted by sea currents on the kinematic equation of ships is considered first.The input-to-state stability (ISS) theory used to verify the system is input-to-state stable.Combining the Nussbaum gain with backstepping techniques, a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system.It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded.Consequently, a ship's linear track-keeping control can be implemented.Simulation results using Dalian Maritime University's ocean-going training ship 'YULONG' are presented to validate the effectiveness of the proposed algorithm.

  19. On Building Immersive Audio Applications Using Robust Adaptive Beamforming and Joint Audio-Video Source Localization

    Directory of Open Access Journals (Sweden)

    Beracoechea JA

    2006-01-01

    Full Text Available This paper deals with some of the different problems, strategies, and solutions of building true immersive audio systems oriented to future communication applications. The aim is to build a system where the acoustic field of a chamber is recorded using a microphone array and then is reconstructed or rendered again, in a different chamber using loudspeaker array-based techniques. Our proposal explores the possibility of using recent robust adaptive beamforming techniques for effectively estimating the original sources of the emitting room. A joint audio-video localization method needed in the estimation process as well as in the rendering engine is also presented. The estimated source signal and the source localization information drive a wave field synthesis engine that renders the acoustic field again at the receiving chamber. The system performance is tested using MUSHRA-based subjective tests.

  20. Biologically Inspired Design Principles for Scalable, Robust, Adaptive, Decentralized Search and Automated Response (RADAR)

    CERN Document Server

    Moses, Melanie

    2010-01-01

    Distributed search problems are ubiquitous in Artificial Life (ALife). Many distributed search problems require identifying a rare and previously unseen event and producing a rapid response. This challenge amounts to finding and removing an unknown needle in a very large haystack. Traditional computational search models are unlikely to find, nonetheless, appropriately respond to, novel events, particularly given data distributed across multiple platforms in a variety of formats and sources with variable and unknown reliability. Biological systems have evolved solutions to distributed search and response under uncertainty. Immune systems and ant colonies efficiently scale up massively parallel search with automated response in highly dynamic environments, and both do so using distributed coordination without centralized control. These properties are relevant to ALife, where distributed, autonomous, robust and adaptive control is needed to design robot swarms, mobile computing networks, computer security system...

  1. Combination synchronization of time-delay chaotic system via robust adaptive sliding mode control

    Indian Academy of Sciences (India)

    AYUB KHAN; SHIKHA

    2017-06-01

    In this paper, the methodology to achieve combination synchronization of time-delay chaotic system via robust adaptive sliding mode control is introduced. The methodology is implemented by taking identical time-delayLorenz chaotic system. The selection of switching surface and the design of control law is also discussed, which is an important issue. By utilizing rigorous mathematical theory, sufficient condition is drawn for the stability of error dynamics based on Lyapunov stability theory. Theoretical results are supported with the numerical simulations. The complexity of this methodology is useful to strengthen the security of communication. The hidden message can be partitioned into several parts loaded in two master systems to improve the accuracy of communication.

  2. Combination synchronization of time-delay chaotic system via robust adaptive sliding mode control

    Science.gov (United States)

    Khan, Ayub; Shikha

    2017-06-01

    In this paper, the methodology to achieve combination synchronization of time-delay chaotic system via robust adaptive sliding mode control is introduced. The methodology is implemented by taking identical time-delay Lorenz chaotic system. The selection of switching surface and the design of control law is also discussed, which is an important issue. By utilizing rigorous mathematical theory, sufficient condition is drawn for the stability of error dynamics based on Lyapunov stability theory. Theoretical results are supported with the numerical simulations. The complexity of this methodology is useful to strengthen the security of communication. The hidden message can be partitioned into several parts loaded in two master systems to improve the accuracy of communication.

  3. Robust adaptive control of spacecraft proximity maneuvers under dynamic coupling and uncertainty

    Science.gov (United States)

    Sun, Liang; Huo, Wei

    2015-11-01

    This paper provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results.

  4. Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities

    CERN Document Server

    Eriksson, Brian; Singh, Aarti; Nowak, Robert

    2011-01-01

    Hierarchical clustering based on pairwise similarities is a common tool used in a broad range of scientific applications. However, in many problems it may be expensive to obtain or compute similarities between the items to be clustered. This paper investigates the hierarchical clustering of N items based on a small subset of pairwise similarities, significantly less than the complete set of N(N-1)/2 similarities. First, we show that if the intracluster similarities exceed intercluster similarities, then it is possible to correctly determine the hierarchical clustering from as few as 3N log N similarities. We demonstrate this order of magnitude savings in the number of pairwise similarities necessitates sequentially selecting which similarities to obtain in an adaptive fashion, rather than picking them at random. We then propose an active clustering method that is robust to a limited fraction of anomalous similarities, and show how even in the presence of these noisy similarity values we can resolve the hierar...

  5. Robust adaptive neural control of uncertain pure-feedback nonlinear systems

    Science.gov (United States)

    Sun, Gang; Wang, Dan; Peng, Zhouhua; Wang, Hao; Lan, Weiyao; Wang, Mingxin

    2013-05-01

    In this paper, a robust adaptive neural control design approach is presented for a class of uncertain pure-feedback nonlinear systems. To reduce the complexity of the both controller structure and computation, only one neural network is used to approximate the lumped unknown function of the system at the last step of the recursive design process. By this approach, the complexity growing problem existing in conventional methods can be eliminated completely. Stability analysis shows that all the closed-loop system signals are uniformly ultimately bounded, and the steady state tracking error can be made arbitrarily small by appropriately choosing control parameters. Simulation results demonstrate the effectiveness and merits of the proposed approach.

  6. Robust Adaptive Beamforming Based on Steering Vector Estimation via Semidefinite Programming Relaxation

    CERN Document Server

    Khabbazibasmenj, Arash; Hassanien, Aboulnasr

    2010-01-01

    We develop a new approach to robust adaptive beamforming in the presence of signal steering vector errors. Since the signal steering vector is known imprecisely, its presumed (prior) value is used to find a more accurate estimate of the actual steering vector, which then is used for obtaining the optimal beamforming weight vector. The objective for finding such an estimate of the actual signal steering vector is the maximization of the beamformer output power, while the constraints are the normalization condition and the requirement that the estimate of the steering vector does not converge to an interference steering vector. Our objective and constraints are free of any design parameters of non-unique choice. The resulting optimization problem is a non-convex quadratically constrained quadratic program, which is NP hard in general. However, for our problem we show that an efficient solution can be found using the semi-definite relaxation technique. Moreover, the strong duality holds for the proposed problem ...

  7. Stabilization and regulation of nonlinear systems a robust and adaptive approach

    CERN Document Server

    Chen, Zhiyong

    2015-01-01

    The core of this textbook is a systematic and self-contained treatment of the nonlinear stabilization and output regulation problems. Its coverage embraces both fundamental concepts and advanced research outcomes and includes many numerical and practical examples. Several classes of important uncertain nonlinear systems are discussed. The state-of-the art solution presented uses robust and adaptive control design ideas in an integrated approach which demonstrates connections between global stabilization and global output regulation allowing both to be treated as stabilization problems. Stabilization and Regulation of Nonlinear Systems takes advantage of rich new results to give students up-to-date instruction in the central design problems of nonlinear control, problems which are a driving force behind the furtherance of modern control theory and its application. The diversity of systems in which stabilization and output regulation become significant concerns in the mathematical formulation of practical contr...

  8. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    Science.gov (United States)

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-05-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  9. Uncertain information fusion with robust adaptive neural networks-fuzzy reasoning

    Institute of Scientific and Technical Information of China (English)

    Zhang Yinan; Sun Qingwei; Quan He; Jin Yonggao; Quan Taifan

    2006-01-01

    In practical multi-sensor information fusion systems,there exists uncertainty about the network structure,active state of sensors,and information itself (including fuzziness,randomness,incompleteness as well as roughness,etc). Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.

  10. Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

    Science.gov (United States)

    Tryfonidis, Michail

    It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that

  11. Hypothesis Testing, "p" Values, Confidence Intervals, Measures of Effect Size, and Bayesian Methods in Light of Modern Robust Techniques

    Science.gov (United States)

    Wilcox, Rand R.; Serang, Sarfaraz

    2017-01-01

    The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…

  12. Flight control design using a blend of modern nonlinear adaptive and robust techniques

    Science.gov (United States)

    Yang, Xiaolong

    In this dissertation, the modern control techniques of feedback linearization, mu synthesis, and neural network based adaptation are used to design novel control laws for two specific applications: F/A-18 flight control and reusable launch vehicle (an X-33 derivative) entry guidance. For both applications, the performance of the controllers is assessed. As a part of a NASA Dryden program to develop and flight test experimental controllers for an F/A-18 aircraft, a novel method of combining mu synthesis and feedback linearization is developed to design longitudinal and lateral-directional controllers. First of all, the open-loop and closed-loop dynamics of F/A-18 are investigated. The production F/A-18 controller as well as the control distribution mechanism are studied. The open-loop and closed-loop handling qualities of the F/A-18 are evaluated using low order transfer functions. Based on this information, a blend of robust mu synthesis and feedback linearization is used to design controllers for a low dynamic pressure envelope of flight conditions. For both the longitudinal and the lateral-directional axes, a robust linear controller is designed for a trim point in the center of the envelope. Then by including terms to cancel kinematic nonlinearities and variations in the aerodynamic forces and moments over the flight envelope, a complete nonlinear controller is developed. In addition, to compensate for the model uncertainty, linearization error and variations between operating points, neural network based adaptation is added to the designed longitudinal controller. The nonlinear simulations, robustness and handling qualities analysis indicate that the performance is similar to or better than that for the production F/A-18 controllers. When the dynamic pressure is very low, the performance of both the experimental and the production flight controllers is degraded, but Level I handling qualities are still achieved. A new generation of Reusable Launch Vehicles

  13. Structural and functional robustness of the adaptive-sorting signaling network

    Science.gov (United States)

    Pang, Ning-Ning

    2016-06-01

    A major task of study on ligand discrimination by T cells is the construction of a mechanistic model to account for threshold setting in response to variant ligands interacting with the same T-cell receptors. Recently, Lalanne and Francois in a seminal paper (2013 Phys. Rev. Lett. 110 218102) have addressed this question by constructing minimal core circuits such that the biological outputs can satisfy the essential properties of early T-cell activation. To make this core set of network topology a valuable tool for synthetic biologists to robustly engineer biological circuits, we are motivated to ask a general question: is adaptive response encoded by the proposed circuit topology structurally stable, regardless of the values of the kinetic parameters? This has particularly relevant effects for the network reliability, since failures in ligand discrimination result in either infection or autoimmune diseases. To the best of our knowledge, a rigorous and complete mathematical proof of this issue is still lacking in the literature. In this paper, by giving a rigorous mathematical proof, we have shown that this regulatory circuitry is appropriately designed and the existence, uniqueness, and globally asymptotic attractiveness of the steady state are preserved. Moreover, we further generalize the adaptive sorting module and undertake an extensive analysis on the trade-off between antagonism and sensitivity of T-cell ligand discrimination in various cellular conditions. Notably, the optimal phosphorylation step in which to place the regulatory motif is analytically obtained and numerically confirmed. Finally, relevant experimental facts and biological implications are discussed.

  14. Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection.

    Science.gov (United States)

    Su, Hai; Xing, Fuyong; Yang, Lin

    2016-06-01

    Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96.

  15. Adaptive Robust Sliding Mode Vibration Control of a Flexible Beam Using Piezoceramic Sensor and Actuator: An Experimental Study

    Directory of Open Access Journals (Sweden)

    Ruo Lin Wang

    2014-01-01

    Full Text Available This paper presents an experimental study of an adaptive robust sliding mode control scheme based on the Lyapunov’s direct method for active vibration control of a flexible beam using PZT (lead zirconate titanate sensor and actuator. PZT, a type of piezoceramic material, has the advantages of high reliability, high bandwidth, and solid state actuation and is adopted here in forms of surface-bond patches for vibration control. Two adaptive robust sliding mode controllers for vibration suppression are designed: one uses a discontinuous bang-bang robust compensator and the other uses a smooth compensator with a hyperbolic tangent function. Both controllers guarantee asymptotic stability, as proved by the Lyapunov’s direct method. Experimental results verified the effectiveness and the robustness of both adaptive sliding mode controllers. However, from the experimental results, the bang-bang robust compensator causes small-magnitude chattering because of the discontinuous switching actions. With the smooth compensator, vibration is quickly suppressed and no chattering is induced. Furthermore, the robustness of the controllers is successfully demonstrated with ensured effectiveness in vibration control when masses are added to the flexible beam.

  16. Rest interval duration does not influence adaptations in acid/base transport proteins following 10 wk of sprint-interval training in active women.

    Science.gov (United States)

    McGinley, Cian; Bishop, David J

    2017-05-01

    The removal of protons (H(+)) produced during intense exercise is important for skeletal muscle function, yet it remains unclear how best to structure exercise training to improve muscle pH regulation. We investigated whether 4 wk of work-matched sprint-interval trining (SIT), performed 3 days/wk, with either 1 (Rest-1; n = 7) or 5 (Rest-5; n = 7) min of rest between sprints, influenced adaptations in acid/base transport protein content, nonbicarbonate muscle buffer capacity (βmin vitro), and exercise capacity in active women. Following 1 wk of posttesting, comprising a biopsy, a repeated-sprint ability (RSA) test, and a graded-exercise test, maintenance of adaptations was then studied by reducing SIT volume to 1 day/wk for a further 5 wk. After 4 wk of SIT, there was increased protein abundance of monocarboxylate transporter (MCT)-1, sodium/hydrogen exchanger (NHE)-1, and carbonic anhydrase (CA) XIV for both groups, but rest interval duration did not influence the adaptive response. In contrast, greater improvements in total work performed during the RSA test after 4 wk of SIT were evident for Rest-5 compared with Rest-1 (effect size: 0.51; 90% confidence limits ±0.37), whereas both groups had similarly modest improvements in V̇o2peak When training volume was reduced to 1 day/wk, enhanced acid/base transport protein abundance was maintained, although NHE1 content increased further for Rest-5 only. Finally, our data support intracellular lactate as a signaling molecule for inducing MCT1 expression, but neither lactate nor H(+) accumulation appears to be important signaling factors in MCT4 regulation. Copyright © 2017 the American Physiological Society.

  17. Maximization of the robust stability degree of interval systems by means of a linear controller in the presence of limits

    Science.gov (United States)

    Gayvoronskiy, S. A.; Ezangina, T.; Khozhaev, I.; Gunbo, Lan

    2017-01-01

    The authors of this article developed the technique of combined parametric synthesis of a linear controller on the basis of the coefficient method and the method of mathematical programming capable of ensuring the maximization of the degree of robust stability of a control system. The article also presents the numerical illustration of the PI controller synthesis of the position stabilization system of an underwater object.

  18. Robust adaptive fuzzy tracking control for a class of strict-feedback nonlinear systems based on backstepping technique

    Institute of Scientific and Technical Information of China (English)

    Min WANG; Xiuying WANG; Bing CHEN; Shaocheng TONG

    2007-01-01

    In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.

  19. Adaptation of irrigation networks to climate change: Linking robust design and stakeholder contribution

    Energy Technology Data Exchange (ETDEWEB)

    Granados, A.; Martín-Carrasco, F.J.; García de Jalón, S.; Iglesias, A.

    2015-07-01

    Agriculture is a particularly sensitive sector to the potential impacts of climate change. Thus, irrigation infrastructure is required to be robust to cope with these potential threats. The objective of this research is designing more robust irrigation networks, considering cost and stakeholder contribution. To that end, the investigation was addressed in three phases: a sensitivity analysis to understand the effectiveness of the distinct variables, a cost-effectiveness analysis assessing their efficiency, and a global study of the most efficient variables to provide an insight into their function. The sensitivity analysis indicates that the networks oversized by means of the coefficient of utilisation or the factor of safety, behave better than those oversized via the continuous specific discharge; moreover, the degree of freedom has been shown ineffective. The cost-effectiveness analysis shows that the coefficient of utilisation and the factor of safety are the most efficient variables, as they introduced safety margin oversizing fewer network elements and to a lesser extent than the continuous specific discharge. It also shows that stakeholder contribution, conveyed as a reduction of the degree of freedom, plays an important role in the network’s adaptive capacity to change. The global study of these variables reveals the subtlety of the coefficient of utilisation, which is the variable that better reproduces the farmer behaviour during demand increase scenarios. In conclusion, the results identify the coefficient of utilisation as the variable which provides the safest margins and reveal the importance of stakeholder contribution in absorb the demand increase in a better manner. (Author)

  20. Adaptation of irrigation networks to climate change: Linking robust design and stakeholder contribution

    Directory of Open Access Journals (Sweden)

    Alfredo Granados

    2015-12-01

    Full Text Available Agriculture is a particularly sensitive sector to the potential impacts of climate change. Thus, irrigation infrastructure is required to be robust to cope with these potential threats. The objective of this research is designing more robust irrigation networks, considering cost and stakeholder contribution. To that end, the investigation was addressed in three phases: a sensitivity analysis to understand the effectiveness of the distinct variables, a cost-effectiveness analysis assessing their efficiency, and a global study of the most efficient variables to provide an insight into their function. The sensitivity analysis indicates that the networks oversized by means of the coefficient of utilisation or the factor of safety, behave better than those oversized via the continuous specific discharge; moreover, the degree of freedom has been shown ineffective. The cost-effectiveness analysis shows that the coefficient of utilisation and the factor of safety are the most efficient variables, as they introduced safety margin oversizing fewer network elements and to a lesser extent than the continuous specific discharge. It also shows that stakeholder contribution, conveyed as a reduction of the degree of freedom, plays an important role in the network’s adaptive capacity to change. The global study of these variables reveals the subtlety of the coefficient of utilisation, which is the variable that better reproduces the farmer behaviour during demand increase scenarios. In conclusion, the results identify the coefficient of utilisation as the variable which provides the safest margins and reveal the importance of stakeholder contribution in absorb the demand increase in a better manner.

  1. Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    F. Yıldız Tascikaraoglu

    2014-01-01

    Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.

  2. Robust Adaptation Research in High Mountains: Integrating the Scientific, Social, and Ecological Dimensions of Glacio-Hydrological Change

    Directory of Open Access Journals (Sweden)

    Graham McDowell

    2017-09-01

    Full Text Available Climate-related changes in glacierized watersheds are widely documented, stimulating adaptive responses among the 370 million people living in glacier-influenced watersheds as well as aquatic and riparian ecosystems. The situation denotes important interdependencies between science, society, and ecosystems, yet integrative approaches to the study of adaptation to such changes remain scarce in both the mountain- and non-mountain-focused adaptation scholarship. Using the example of glacio-hydrological change, it is argued here that this analytical limitation impedes the identification, development, and implementation of “successful” adaptations. In response, the paper introduces three guiding principles for robust adaptation research in glaciated mountain regions. Principle 1: Adaptation research should integrate detailed analyses of watershed-specific glaciological and hydro-meteorological conditions; glacio-hydrological changes are context-specific and therefore cannot be assumed to follow idealized trajectories of “peak water”. Principle 2: Adaptation research should consider the complex interplay between glacio-hydrological changes and socio-economic, cultural, and political conditions; responses to environmental changes are non-deterministic and therefore not deducible from hydrological changes alone. Principle 3: Adaptation research should be attentive to interdependencies, feedbacks, and tradeoffs between human and ecological responses to glacio-hydrological change; research that does not evaluate these socio-ecological dynamics may lead to maladaptive adaptation plans. These principles call attention to the linked scientific, social, and ecological dimensions of adaptation, and offer a point of departure for future climate change adaptation research in high mountains.

  3. A multi-layer robust adaptive fault tolerant control system for high performance aircraft

    Science.gov (United States)

    Huo, Ying

    Modern high-performance aircraft demand advanced fault-tolerant flight control strategies. Not only the control effector failures, but the aerodynamic type failures like wing-body damages often result in substantially deteriorate performance because of low available redundancy. As a result the remaining control actuators may yield substantially lower maneuvering capabilities which do not authorize the accomplishment of the air-craft's original specified mission. The problem is to solve the control reconfiguration on available control redundancies when the mission modification is urged to save the aircraft. The proposed robust adaptive fault-tolerant control (RAFTC) system consists of a multi-layer reconfigurable flight controller architecture. It contains three layers accounting for different types and levels of failures including sensor, actuator, and fuselage damages. In case of the nominal operation with possible minor failure(s) a standard adaptive controller stands to achieve the control allocation. This is referred to as the first layer, the controller layer. The performance adjustment is accounted for in the second layer, the reference layer, whose role is to adjust the reference model in the controller design with a degraded transit performance. The upmost mission adjust is in the third layer, the mission layer, when the original mission is not feasible with greatly restricted control capabilities. The modified mission is achieved through the optimization of the command signal which guarantees the boundedness of the closed-loop signals. The main distinguishing feature of this layer is the the mission decision property based on the current available resources. The contribution of the research is the multi-layer fault-tolerant architecture that can address the complete failure scenarios and their accommodations in realities. Moreover, the emphasis is on the mission design capabilities which may guarantee the stability of the aircraft with restricted post

  4. A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple

    Science.gov (United States)

    Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

    2016-11-01

    Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

  5. A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple

    Science.gov (United States)

    Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

    2017-05-01

    Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

  6. Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.

    Science.gov (United States)

    Zhang, Jiong; Dashtbozorg, Behdad; Bekkers, Erik; Pluim, Josien P W; Duits, Remco; Ter Haar Romeny, Bart M

    2016-12-01

    This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations [Formula: see text]. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain [Formula: see text], vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.

  7. High-intensity high-volume swimming induces more robust signaling through PGC-1α and AMPK activation than sprint interval swimming in m. triceps brachii

    DEFF Research Database (Denmark)

    Casuso, Rafael A; Plaza-Díaz, Julio; Ruiz-Ojeda, Francisco J

    2017-01-01

    We aimed to test whether high-intensity high-volume training (HIHVT) swimming would induce more robust signaling than sprint interval training (SIT) swimming within the m. triceps brachii due to lower metabolic and oxidation. Nine well-trained swimmers performed the two training procedures...... on separate randomized days. Muscle biopsies from m. triceps brachii and blood samples were collected at three different time points: a) before the intervention (pre), b) immediately after the swimming procedures (post) and c) after 3 h of rest (3 h). Hydroperoxides, creatine kinase (CK), and lactate...

  8. DSP-based Robust Nonlinear Speed Control of PM Synchronous Motor Using Adaptive and Sliding Mode Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Baik, I.C.; Kim, K.H.; Cho, K.Y.; Youn, M.J. [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1998-04-01

    A DSP-based robust nonlinear speed control of a permanent magnet synchronous motor (PMSM) which is robust to unknown parameter variations and speed measurement error is presented. The model reference adaptive system (MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the Lyapunov stability theory. For the disturbances or quickly varying parameters, a quasi-linearized and decoupled model including the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller. To show the validity of the proposed control scheme, simulations and experimental works are carried out and compared with the conventional control scheme. (author). 19 refs., 14 figs., 6 tabs.

  9. Motion synchronization of dual-cylinder pneumatic servo systems with integration of adaptive robust control and cross-coupling approach

    Institute of Scientific and Technical Information of China (English)

    De-yuan MENG; Guo-liang TAO; Ai-min LI; Wei LI

    2014-01-01

    We investigate motion synchronization of dual-cylinder pneumatic servo systems and develop an adaptive robust synchronization controller. The proposed controller incorporates the cross-coupling technology into the integrated direct/indirect adaptive robust control (DIARC) architecture by feeding back the coupled position errors, which are formed by the trajectory tracking errors of two cylinders and the synchronization error between them. The controller employs an online recursive least squares estimation algorithm to obtain accurate estimates of model parameters for reducing the extent of parametric uncertainties, and uses a robust control law to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. Therefore, asymptotic convergence to zero of both trajectory tracking and synchronization errors can be guaranteed. Experimental results verify the effectiveness of the proposed controller.

  10. VIDEO DENOISING USING SWITCHING ADAPTIVE DECISION BASED ALGORITHM WITH ROBUST MOTION ESTIMATION TECHNIQUE

    Directory of Open Access Journals (Sweden)

    V. Jayaraj

    2010-08-01

    Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.

  11. Robust Adaptive Fuzzy Design for Ship Linear-tracking Control with Input Saturation

    Directory of Open Access Journals (Sweden)

    Yancai Hu

    2017-04-01

    Full Text Available A robust adaptive control approach is proposed for underactuated surface ship linear path-tracking control system based on the backstepping control method and Lyapunov stability theory. By employing T-S fuzzy system to approximate nonlinear uncertainties of the control system, the proposed scheme is developed by combining “dynamic surface control” (DSC and “minimal learning parameter” (MLP techniques. The substantial problems of “explosion of complexity” and “dimension curse” existed in the traditional backstepping technique are circumvented, and it is convenient to implement in applications. In addition, an auxiliary system is developed to deal with the effect of input saturation constraints. The control algorithm avoids the singularity problem of controller and guarantees the stability of the closed-loop system. The tracking error converges to an arbitrarily small neighborhood. Finally, MATLAB simulation results are given from an application case of Dalian Maritime University training ship to demonstrate the effectiveness of the proposed scheme.

  12. Adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic cylinders

    Directory of Open Access Journals (Sweden)

    Ce Shang

    2016-04-01

    Full Text Available Due to the compressibility of air, non-linear characteristics, and parameter uncertainties of pneumatic elements, the position control of a pneumatic cylinder or parallel platform is still very difficult while comparing with the systems driven by electric or hydraulic power. In this article, based on the basic dynamic model and descriptions of thermal processes, a controller integrated with online parameter estimation is proposed to improve the performance of a pneumatic cylinder controlled by a proportional valve. The trajectory tracking error is significantly decreased by applying this method. Moreover, the algorithm is expanded to the problem of posture trajectory tracking for the three-revolute prismatic spherical pneumatic parallel manipulator. Lyapunov’s method is used to give the proof of stability of the controller. Using NI-CompactRio, NI-PXI, and Veristand platform as the realistic controller hardware and data interactive environment, the adaptive robust control algorithm is applied to the physical system successfully. Experimental results and data analysis showed that the posture error of the platform could be about 0.5%–0.7% of the desired trajectory amplitude. By integrating this method to the mechatronic system, the pneumatic servo solutions can be much more competitive in the industrial market of position and posture control.

  13. Robust Adaptive Fuzzy Control for Planetary Rovers While Climbing up Deformable Slopes with Longitudinal Slip

    Directory of Open Access Journals (Sweden)

    Li Zhengcai

    2014-01-01

    Full Text Available Mobility control is one of the most essential parts of planetary rovers’ research and development. The goal of this research is to let the planetary rovers be able to achieve demand of motion from upper level with satisfied control performance under the rough and deformable planetary terrain that often lead to longitudinal slip. The longitudinal slip influences the mobility efficiency obviously, especially on the major deformable slopes. Compared with the past works on normal stiff terrains, properties of soil and interaction between wheels and soil should be considered additionally. Therefore, to achieve the final goal, in this paper, wheel-soil dynamic model for six-wheel planetary rovers while climbing up deformable slopes with longitudinal slip is first built and control based in order to account for slip phenomena. These latter effects are then taken into account within terramechanics theory, relying upon nonlinear control techniques; finally, a robust adaptive fuzzy control strategy with longitudinal slip compensation is developed to reduce the effects induced by slip phenomena and modeling error. Capabilities of this control scheme are demonstrated via full scale simulations carried out with a six-wheel robot moving on sloped deformable terrain, whose real time was computed relying uniquely upon RoSTDyn, a dynamic software.

  14. Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

    Science.gov (United States)

    Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

    2016-03-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

  15. Improving Robustness of Deep Neural Network Acoustic Models via Speech Separation and Joint Adaptive Training

    Science.gov (United States)

    Narayanan, Arun; Wang, DeLiang

    2015-01-01

    Although deep neural network (DNN) acoustic models are known to be inherently noise robust, especially with matched training and testing data, the use of speech separation as a frontend and for deriving alternative feature representations has been shown to improve performance in challenging environments. We first present a supervised speech separation system that significantly improves automatic speech recognition (ASR) performance in realistic noise conditions. The system performs separation via ratio time-frequency masking; the ideal ratio mask (IRM) is estimated using DNNs. We then propose a framework that unifies separation and acoustic modeling via joint adaptive training. Since the modules for acoustic modeling and speech separation are implemented using DNNs, unification is done by introducing additional hidden layers with fixed weights and appropriate network architecture. On the CHiME-2 medium-large vocabulary ASR task, and with log mel spectral features as input to the acoustic model, an independently trained ratio masking frontend improves word error rates by 10.9% (relative) compared to the noisy baseline. In comparison, the jointly trained system improves performance by 14.4%. We also experiment with alternative feature representations to augment the standard log mel features, like the noise and speech estimates obtained from the separation module, and the standard feature set used for IRM estimation. Our best system obtains a word error rate of 15.4% (absolute), an improvement of 4.6 percentage points over the next best result on this corpus. PMID:26973851

  16. Robust a Posteriori Error Control and Adaptivity for Multiscale, Multinumerics, and Mortar Coupling

    KAUST Repository

    Pencheva, Gergina V.

    2013-01-01

    We consider discretizations of a model elliptic problem by means of different numerical methods applied separately in different subdomains, termed multinumerics, coupled using the mortar technique. The grids need not match along the interfaces. We are also interested in the multiscale setting, where the subdomains are partitioned by a mesh of size h, whereas the interfaces are partitioned by a mesh of much coarser size H, and where lower-order polynomials are used in the subdomains and higher-order polynomials are used on the mortar interface mesh. We derive several fully computable a posteriori error estimates which deliver a guaranteed upper bound on the error measured in the energy norm. Our estimates are also locally efficient and one of them is robust with respect to the ratio H/h under an assumption of sufficient regularity of the weak solution. The present approach allows bounding separately and comparing mutually the subdomain and interface errors. A subdomain/interface adaptive refinement strategy is proposed and numerically tested. © 2013 Society for Industrial and Applied Mathematics.

  17. Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

    Science.gov (United States)

    Kun, David William

    Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external

  18. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

    Science.gov (United States)

    Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

    2016-04-01

    Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects

  19. Robust L2-L∞ Filtering of Time-Delay Jump Systems with Respect to the Finite-Time Interval

    Directory of Open Access Journals (Sweden)

    Shuping He

    2011-01-01

    Full Text Available This paper studied the problem of stochastic finite-time boundedness and disturbance attenuation for a class of linear time-delayed systems with Markov jumping parameters. Sufficient conditions are provided to solve this problem. The L2-L∞ filters are, respectively, designed for time-delayed Markov jump linear systems with/without uncertain parameters such that the resulting filtering error dynamic system is stochastically finite-time bounded and has the finite-time interval disturbance attenuation γ for all admissible uncertainties, time delays, and unknown disturbances. By using stochastic Lyapunov-Krasovskii functional approach, it is shown that the filter designing problem is in terms of the solutions of a set of coupled linear matrix inequalities. Simulation examples are included to demonstrate the potential of the proposed results.

  20. A PRACTICAL MODEL OF LOW-VOLUME HIGH-INTENSITY INTERVAL TRAINING INDUCES PERFORMANCE AND METABOLIC ADAPTATIONS THAT RESEMBLE 'ALL-OUT' SPRINT INTERVAL TRAINING

    Directory of Open Access Journals (Sweden)

    Mahdi Bayati

    2011-09-01

    Full Text Available Recently, a novel type of high-intensity interval training known as sprint interval training has demonstrated increases in aerobic and anaerobic performance with very low time commitment. However, this type of training program is unpractical for general populations. The present study compared the impact of a low-volume high-intensity interval training to a "all-out" sprint interval training. Twenty-four active young males were recruited and randomized into three groups: (G1: 3-5 cycling bouts × 30-s all-out with 4 min recovery; G2: 6- 10 cycling bouts × 125% Pmax with 2 min recovery and a non-trained control group. They all performed a VO2max test, a time to exhaustion at Pmax (Tmax and a Wingate test before and after the intervention. Capillary blood lactate was taken at rest, 3, and 20 min after the Wingate trial. Training was performed 3 sessions per week for 4 weeks. In G1, significant improvements (p < 0.05 following training were found in VO2max (9.6%, power at VO2max (12.8%, Tmax (48.4%, peak power output (10.3% and mean power output (17.1%. In G2, significant improvements following training were found in VO2max (9.7%, power at VO2max (16.1%, Tmax (54.2%, peak power output (7.4%; p < 0.05, but mean power output did not change significantly. Blood lactate recovery (20th min significantly decreased in G1 and G2 when compared with pre-testing and the CON group (p < 0.05. In conclusion, the results of the current study agree with earlier work demonstrating the effectiveness of 30-s all-out training program to aerobic and anaerobic adaptations. Of substantial interest is that the low volume high intensity training provides similar results but involves only half the intensity with double the repetitions

  1. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    Science.gov (United States)

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E.; Lo, Yeh-Chi

    2016-04-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  2. An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization

    Directory of Open Access Journals (Sweden)

    Zengke Li

    2016-11-01

    Full Text Available Location-based services (LBS are services offered through a mobile device that take into account a device’s geographical location. To provide position information for these services, location is a key process. GNSS (Global Navigation Satellite System can provide sub-meter accuracy in open-sky areas using satellite signals. However, for indoor and dense urban environments, the accuracy deteriorates significantly because of weak signals and dense multipaths. The situation becomes worse in indoor environments where the GNSS signals are unreliable or totally blocked. To improve the accuracy of indoor positioning for location-based services, an improved WiFi/Pedestrian Dead Reckoning (PDR integrated positioning and navigation system using an adaptive and robust filter is presented. The adaptive filter is based on scenario and motion state recognition and the robust filter is based on the Mahalanobis distance. They are combined and used in the WiFi/PDR integrated system to weaken the effect of gross errors on the dynamic and observation models. To validate their performance in the WiFi/PDR integrated system, a real indoor localization experiment is conducted. The results indicate that the adaptive filter is better able to adapt to the circumstances of the dynamic model by adjusting the covariance of the process noise and the robust Kalman filter is able to mitigate the harmful effect of gross errors from the WiFi positioning.

  3. Physiological and health-related adaptations to low-volume interval training: influences of nutrition and sex.

    Science.gov (United States)

    Gibala, Martin J; Gillen, Jenna B; Percival, Michael E

    2014-11-01

    Interval training refers to the basic concept of alternating periods of relatively intense exercise with periods of lower-intensity effort or complete rest for recovery. Low-volume interval training refers to sessions that involve a relatively small total amount of exercise (i.e. ≤10 min of intense exercise), compared with traditional moderate-intensity continuous training (MICT) protocols that are generally reflected in public health guidelines. In an effort to standardize terminology, a classification scheme was recently proposed in which the term 'high-intensity interval training' (HIIT) be used to describe protocols in which the training stimulus is 'near maximal' or the target intensity is between 80 and 100 % of maximal heart rate, and 'sprint interval training' (SIT) be used for protocols that involve 'all out' or 'supramaximal' efforts, in which target intensities correspond to workloads greater than what is required to elicit 100 % of maximal oxygen uptake (VO2max). Both low-volume SIT and HIIT constitute relatively time-efficient training strategies to rapidly enhance the capacity for aerobic energy metabolism and elicit physiological remodeling that resembles changes normally associated with high-volume MICT. Short-term SIT and HIIT protocols have also been shown to improve health-related indices, including cardiorespiratory fitness and markers of glycemic control in both healthy individuals and those at risk for, or afflicted by, cardiometabolic diseases. Recent evidence from a limited number of studies has highlighted potential sex-based differences in the adaptive response to SIT in particular. It has also been suggested that specific nutritional interventions, in particular those that can augment muscle buffering capacity, such as sodium bicarbonate, may enhance the adaptive response to low-volume interval training.

  4. Towards a robust methodology to assess coastal impacts and adaptation policies for Europe

    Science.gov (United States)

    Vousdoukas, Michalis; Voukouvalas, Evangelos; Mentaschi, Lorenzo; Feyen, Luc

    2016-04-01

    The present contribution aims to present preliminary results from efforts towards (i) the development of the integrated risk assessment tool LISCoAsT for Europe (Large scale Integrated Sea-level and Coastal Assessment Tool); (ii) the assessment of coastal risk along the European coastline in view of climate change; and (iii) the development and application of a robust methodology to evaluate adaptation options for the European coastline under climate change scenarios. The overall approach builds on the disaster risk methodology proposed by the IPCC SREX (2012) report, defining risk as the combination of hazard, exposure and vulnerability. Substantial effort has been put in all the individual components of the risk assessment chain, including: (1) the development of dynamic scenarios of catastrophic coastal hazards (e.g., storm surges, sea-level rise) in view of climate change; (2) quantification, mapping and forecasting exposure and vulnerability in coastal areas; (3) carrying out a bottom-up, highly disaggregated assessment of climate impacts on coastal areas in Europe in view of global warming; (4) estimating the costs and assessing the effectiveness of different adaptation options. Projections indicate that, by the end of this century, sea levels in Europe will rise on average between 45 and 70 cm; while projections of coastal hazard showed that for some European regions, the increased storminess can be an additional significant driver of further risk. Projections of increasing extreme storm surge levels (SSL) were even more pronounced under the business-as-usual RCP8.5 concentration pathway, in particular along the Northern Europe coastline. The above are also reflected in the coastal impact projections, which show a significant increase in the expected annual damage (EAD) from coastal flooding. The present EAD for Europe of 800 million €/year is projected to increase up to 2.4 and 3.2 billion €/year by 2040 under RCP 4.5 and 8.5, respectively, and to 11

  5. Improving short-range ensemble Kalman storm surge forecasting using robust adaptive inflation

    NARCIS (Netherlands)

    Altaf, M.U.; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, I.

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense t

  6. Improving short-range ensemble Kalman storm surge forecasting using robust adaptive inflation

    NARCIS (Netherlands)

    Altaf, M.U.; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, I.

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense t

  7. Integrated Navigation Based on Robust Estimation Outputs of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information

    Institute of Scientific and Technical Information of China (English)

    YANG Yuanxi; GAO Weiguang

    2005-01-01

    An integrated navigation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.

  8. A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

    OpenAIRE

    Hoogerheide, L.F.; Opschoor, A.; Dijk, van, Nico M.

    2012-01-01

    This discussion paper was published in the Journal of Econometrics (2012). Vol. 171(2), 101-120. A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of sequences of importance weighted Expectation Maximization steps in order to efficiently construct a mixture of...

  9. Robust stability analysis for Markovian jumping stochastic neural networks with mode-dependent time-varying interval delay and multiplicative noise

    Institute of Scientific and Technical Information of China (English)

    Zhang Hua-Guang; Fu Jie; Ma Tie-Dong; Tong Shao-Cheng

    2009-01-01

    This paper is concerned with the problem of robust stability for a class of Markovian jumping stochastic neural networks (MJSNNs) subject to mode-dependent time-varying interval delay and state-multiplicative noise.Based on the Lyapunov-Krasovskii functional and a stochastic analysis approach,some new delay-dependent sufficient conditions are obtained in the linear matrix inequality (LMI) format such that delayed MJSNNs are globally asymptotically stable in the mean-square sense for all admissible uncertainties.An important feature of the results is that the stability criteria are dependent on not only the lower bound and upper bound of delay for all modes but also the covariance matrix consisting of the correlation coefficient.Numerical examples are given to illustrate the effectiveness.

  10. ON THE UNCONDITIONAL ROBUST STABILITY FOR THE MULTIDELAYS INTERVAL COEFFICIENT CONTROL SYSTEM%关于多滞后区间系数控制系统的无条件鲁棒稳定

    Institute of Scientific and Technical Information of China (English)

    黎野平; 张少华; 孟培源

    2001-01-01

    In this paper, we are interested in the multigroup multidelays interval coefficient constant and time varying linear continuous control systems, by means of the equi valence method and the differential inequality in the time domain, we obtain someunconditional robust stability results for the multigroup multidelays constant and time varying interval coefficient linear continuous control systems, respectively.

  11. Finite time-Lyapunov based approach for robust adaptive control of wind-induced oscillations in power transmission lines

    Science.gov (United States)

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2016-06-01

    Large amplitude oscillation of the power transmission lines, which is also known as galloping phenomenon, has hazardous consequences such as short circuiting and failure of transmission line. In this article, to suppress the undesirable vibrations of the transmission lines, first the governing equations of transmission line are derived via mode summation technique. Then, due to the occurrence of large amplitude vibrations, nonlinear quadratic and cubic terms are included in the derived linear equations. To suppress the vibrations, arbitrary number of the piezoelectric actuators is assumed to exert the actuation forces. Afterwards, a Lyapunov based approach is proposed for the robust adaptive suppression of the undesirable vibrations in the finite time. To compensate the supposed parametric uncertainties with unknown bands, proper adaption laws are introduced. To avoid the vibration devastating consequences as quickly as possible, appropriate control laws are designed. The vibration suppression in the finite time with supposed adaption and control laws is mathematically proved via Lyapunov finite time stability theory. Finally, to illustrate and validate the efficiency and robustness of the proposed finite time control scheme, a parametric case study with three piezoelectric actuators is performed. It is observed that the proposed active control strategy is more efficient and robust than the passive control methods.

  12. Integrating Robust Decision Making (RDM) and Dynamic Adaptive Policy Pathways (DAPP): Towards a Unified Decision Making Framework under Deep Uncertainty

    Science.gov (United States)

    Kumar, A.; Weijs, S.

    2016-12-01

    With exogenous factors such as climate change, future demand, resource options, technological and economic constraints, water agency plans should be robust and able to be adapted over time to meet agency goals over a wide range of plausible future conditions. A variety of new approaches and computational tools are being put forward to aid decision making under deep uncertainty (DMDU). Robust Decision Making (RDM) and Dynamic Adaptive Policy Pathways (DAPP) are the two frameworks that have been applied recently to a variety of problems. While RDM facilitates the analysis of trade-offs and the iterative learning about a policy problem, DAPP offers a map of possible routes into the future giving insight into future actions that can be taken if the initial actions prove to be insufficient, thus, alleviating the irreversibility of decisions. This paper first investigates into both approaches, and then suggest a way to combine elements from both so as to produce a more unified decision making framework under deep uncertainty. Integrated Resource Plan (IRP) 2013 submitted by British Columbia Hydro and Power Authority (BC Hydro) is considered for the analyses. Main focus is on identification of scenarios that highlight the vulnerabilities of IRP strategies in different state of the world using RDM approach and then employing DAPP to identify demand and climate-related signposts. This work will inform decision makers and stakeholders to adapt robust plans in upcoming IRP 2018.

  13. A Fast and Robust Poisson-Boltzmann Solver Based on Adaptive Cartesian Grids

    Science.gov (United States)

    Boschitsch, Alexander H.; Fenley, Marcia O.

    2011-01-01

    An adaptive Cartesian grid (ACG) concept is presented for the fast and robust numerical solution of the 3D Poisson-Boltzmann Equation (PBE) governing the electrostatic interactions of large-scale biomolecules and highly charged multi-biomolecular assemblies such as ribosomes and viruses. The ACG offers numerous advantages over competing grid topologies such as regular 3D lattices and unstructured grids. For very large biological molecules and multi-biomolecule assemblies, the total number of grid-points is several orders of magnitude less than that required in a conventional lattice grid used in the current PBE solvers thus allowing the end user to obtain accurate and stable nonlinear PBE solutions on a desktop computer. Compared to tetrahedral-based unstructured grids, ACG offers a simpler hierarchical grid structure, which is naturally suited to multigrid, relieves indirect addressing requirements and uses fewer neighboring nodes in the finite difference stencils. Construction of the ACG and determination of the dielectric/ionic maps are straightforward, fast and require minimal user intervention. Charge singularities are eliminated by reformulating the problem to produce the reaction field potential in the molecular interior and the total electrostatic potential in the exterior ionic solvent region. This approach minimizes grid-dependency and alleviates the need for fine grid spacing near atomic charge sites. The technical portion of this paper contains three parts. First, the ACG and its construction for general biomolecular geometries are described. Next, a discrete approximation to the PBE upon this mesh is derived. Finally, the overall solution procedure and multigrid implementation are summarized. Results obtained with the ACG-based PBE solver are presented for: (i) a low dielectric spherical cavity, containing interior point charges, embedded in a high dielectric ionic solvent – analytical solutions are available for this case, thus allowing rigorous

  14. Based on interval type-2 adaptive fuzzy H∞ tracking controller for SISO time-delay nonlinear systems

    Science.gov (United States)

    Lin, Tsung-Chih; Roopaei, Mehdi

    2010-12-01

    In this article, based on the adaptive interval type-2 fuzzy logic, by adjusting weights, centers and widths of proposed fuzzy neural network (FNN), the modeling errors can be eliminated for a class of SISO time-delay nonlinear systems. The proposed scheme has the advantage that can guarantee the H∞ tracking performance to attenuate the lumped uncertainties caused by the unmodelled dynamics, the approximation error and the external disturbances. Moreover, the stability analysis of the proposed control scheme will be guaranteed in the sense that all the states and signals are uniformly bounded and arbitrary small attenuation level. The simulation results are demonstrated to show the effectiveness of the advocated design methodology.

  15. Muscle Adaptations Following Short-Duration Bed Rest with Integrated Resistance, Interval, and Aerobic Exercise

    Science.gov (United States)

    Hackney, Kyle J.; Scott, Jessica M.; Buxton, Roxanne; Redd-Goetchius, Elizabeth; Crowell, J. Brent; Everett, Meghan E.; Wickwire, Jason; Ryder, Jeffrey W.; Bloomberg, Jacob J.; Ploutz-Snyder, Lori L.

    2011-01-01

    Unloading of the musculoskeletal system during space flight results in deconditioning that may impair mission-related task performance in astronauts. Exercise countermeasures have been frequently tested during bed rest (BR) and limb suspension; however, high-intensity, short-duration exercise prescriptions have not been fully explored. PURPOSE: To determine if a high intensity resistance, interval, and aerobic exercise program could protect against muscle atrophy and dysfunction when performed during short duration BR. METHODS: Nine subjects (1 female, 8 male) performed a combination of supine exercises during 2 weeks of horizontal BR. Resistance exercise (3 d / wk) consisted of squat, leg press, hamstring curl, and heel raise exercises (3 sets, 12 repetitions). Aerobic (6 d / wk) sessions alternated continuous (75% VO2 peak) and interval exercise (30 s, 2 min, and 4 min) and were completed on a supine cycle ergometer and vertical treadmill, respectively. Muscle volumes of the upper leg were calculated pre, mid, and post-BR using magnetic resonance imaging. Maximal isometric force (MIF), rate of force development (RFD), and peak power of the lower body extensors were measured twice before BR (averaged to represent pre) and once post BR. ANOVA with repeated measures and a priori planned contrasts were used to test for differences. RESULTS: There were no changes to quadriceps, hamstring, and adductor muscle volumes at mid and post BR time points compared to pre BR (Table 1). Peak power increased significantly from 1614 +/- 372 W to 1739 +/- 359 W post BR (+7.7%, p = 0.035). Neither MIF (pre: 1676 +/- 320 N vs. post: 1711 +/- 250 N, +2.1%, p = 0.333) nor RFD (pre: 7534 +/- 1265 N/ms vs. post: 6951 +/- 1241 N/ms, -7.7%, p = 0.136) were significantly impaired post BR.

  16. OPTIMASI OLSR ROUTING PROTOCOL PADA JARINGAN WIRELESS MESH DENGAN ADAPTIVE REFRESHING TIME INTERVAL DAN ENHANCE MULTI POINT RELAY SELECTING ALGORITHM

    Directory of Open Access Journals (Sweden)

    Faosan Mapa

    2014-01-01

    Full Text Available Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Wireless Mesh Network (WMN adalah suatu konektivitas jaringan yang self-organized, self-configured dan multi-hop. Tujuan dari WMN adalah menawarkan pengguna suatu bentuk jaringan nirkabel yang dapat dengan mudah berkomunikasi dengan jaringan konvensional dengan kecepatan tinggi dan dengan cakupan yang lebih luas serta biaya awal yang minimal. Diperlukan suatu desain protokol routing yang efisien untuk WMN yang secara adaptif dapat mendukung mesh routers dan mesh clients. Dalam tulisan ini, diusulkan untuk mengoptimalkan protokol OLSR, yang merupakan protokol routing proaktif. Digunakan heuristik yang meningkatkan protokol OLSR melalui adaptive refreshing time interval dan memperbaiki metode MPR selecting algorithm. Suatu analisa dalam meningkatkan protokol OLSR melalui adaptive refreshing time interval dan memperbaiki algoritma pemilihan MPR menunjukkan kinerja yang signifikan dalam hal throughput jika dibandingkan dengan protokol OLSR yang asli. Akan tetapi, terdapat kenaikan dalam hal delay. Pada simulasi yang dilakukan dapat disimpulkan bahwa OLSR dapat dioptimalkan dengan memodifikasi pemilihan node MPR berdasarkan cost effective dan penyesuaian waktu interval refreshing hello message sesuai dengan keadaan

  17. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    Science.gov (United States)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

  18. Robust, integrated computational control of NMR experiments to achieve optimal assignment by ADAPT-NMR.

    Science.gov (United States)

    Bahrami, Arash; Tonelli, Marco; Sahu, Sarata C; Singarapu, Kiran K; Eghbalnia, Hamid R; Markley, John L

    2012-01-01

    ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

  19. Robust, integrated computational control of NMR experiments to achieve optimal assignment by ADAPT-NMR.

    Directory of Open Access Journals (Sweden)

    Arash Bahrami

    Full Text Available ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR spectroscopy. With a [(13C,(15N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

  20. Barriers and opportunities for robust decision making approaches to support climate change adaptation in the developing world

    Directory of Open Access Journals (Sweden)

    Ajay Gajanan Bhave

    2016-01-01

    Full Text Available Climate change adaptation is unavoidable, particularly in developing countries where the adaptation deficit is often larger than in developed countries. Robust Decision Making (RDM approaches are considered useful for supporting adaptation decision making, yet case study applications in developing countries are rare. This review paper examines the potential to expand the geographical and sectoral foci of RDM as part of the repertoire of approaches to support adaptation. We review adaptation decision problems hitherto relatively unexplored, for which RDM approaches may have value. We discuss the strengths and weaknesses of different approaches, suggest potential sectors for application and comment on future directions. We identify that data requirements, lack of examples of RDM in actual decision-making, limited applicability for surprise events, and resource constraints are likely to constrain successful application of RDM approaches in developing countries. We discuss opportunities for RDM approaches to address decision problems associated with urban socio-environmental and water-energy-food nexus issues, forest resources management, disaster risk management and conservation management issues. We examine potential entry points for RDM approaches through Environmental Impact Assessments and Strategic Environmental Assessments, which are relatively well established in decision making processes in many developing countries. We conclude that despite some barriers, and with modification, RDM approaches show potential for wider application in developing country contexts.

  1. Robust Adaptive Neural Sliding Mode Approach for Tracking Control of a MEMS Triaxial Gyroscope

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2012-05-01

    Full Text Available In this paper, a neural network adaptive sliding mode control is proposed for an MEMS triaxial gyroscope with unknown system nonlinearities. An input‐output linearization technique is incorporated into the neural adaptive tracking control to cancel the nonlinearities, and the neural network whose parameters are updated from the Lyapunov approach is used to perform the linearization control law. The sliding mode control is utilized to\tcompensate the neural network’s approximation errors. The stability of the closed‐loop system can be guaranteed with the proposed adaptive neural sliding mode control. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive neural sliding mode control scheme.

  2. Robust chaos synchronization based on adaptive fuzzy delayed feedback $\\mathcal{H}_{∞}$ control

    Indian Academy of Sciences (India)

    Choon Ki Ahn

    2012-03-01

    In this paper, we propose a new adaptive $\\mathcal_{∞}$ synchronization strategy, called an adaptive fuzzy delayed feedback $\\mathcal_{∞}$ synchronization (AFDFHS) strategy, for chaotic systems with uncertain parameters and external disturbances. Based on Lyapunov–Krasovskii theory, Takagi–Sugeno (T–S) fuzzy model and adaptive delayed feedback $\\mathcal_{∞}$ control scheme, the AFDFHS controller is presented such that the synchronization error system is asymptotically stable with a guaranteed $\\mathcal_{∞}$ performance. It is shown that the design of the AFDFHS controller with adaptive law can be achieved by solving a linear matrix inequality (LMI), which can be easily facilitated by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed AFDFHS approach.

  3. Performance Evaluation of 2D Adaptive Bilateral Filter For Removal of Noise From Robust Images

    National Research Council Canada - National Science Library

    B.Sridhar; Dr.K.V.V.S.Reddy

    2013-01-01

    .... The variance of range filter can also be adaptive. The filter is applied to improve the sharpens of a gray level and color image by increasing the slope of the edges without producing overshoot or undershoots...

  4. Dynamic adaptive policy pathways: a new method for crafting robust decisions for a deeply uncertain world

    OpenAIRE

    2013-01-01

    A new paradigm for planning under conditions of deep uncertainty has emerged in the literature. According to this paradigm, a planner should create a strategic vision of the future, commit to short-term actions, and establish a framework to guide future actions. A plan that embodies these ideas allows for its dynamic adaptation over time to meet changing circumstances. We propose a method for decisionmaking under uncertain global and regional changes called ‘Dynamic Adaptive Policy Pathways’....

  5. 两种渐消滤波与自适应抗差滤波的综合比较分析%Comparison of Two Fading Filters and Adaptively Robust Filter

    Institute of Scientific and Technical Information of China (English)

    杨元喜; 高为广

    2007-01-01

    Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.

  6. Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure.

    Science.gov (United States)

    Yazdani, Sahar; Haeri, Mohammad

    2017-08-11

    In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well. Copyright © 2017. Published by Elsevier Ltd.

  7. Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.

    Science.gov (United States)

    Fu, Yue; Fu, Jun; Chai, Tianyou

    2015-12-01

    In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.

  8. Robust Adaptive Geometric Tracking Controls on SO(3) with an Application to the Attitude Dynamics of a Quadrotor UAV

    CERN Document Server

    Lee, Taeyoung

    2011-01-01

    This paper provides new results for a robust adaptive tracking control of the attitude dynamics of a rigid body. Both of the attitude dynamics and the proposed control system are globally expressed on the special orthogonal group, to avoid complexities and ambiguities associated with other attitude representations such as Euler angles or quaternions. By designing an adaptive law for the inertia matrix of a rigid body, the proposed control system can asymptotically follow an attitude command without the knowledge of the inertia matrix, and it is extended to guarantee boundedness of tracking errors in the presence of unstructured disturbances. These are illustrated by numerical examples and experiments for the attitude dynamics of a quadrotor UAV.

  9. Noise robust automatic speech recognition with adaptive quantile based noise estimation and speech band emphasizing filter bank

    DEFF Research Database (Denmark)

    Bonde, Casper Stork; Graversen, Carina; Gregersen, Andreas Gregers;

    2005-01-01

    An important topic in Automatic Speech Recognition (ASR) is to reduce the effect of noise, in particular when mismatch exists between the training and application conditions. Many noise robutness schemes within the feature processing domain use as a prerequisite a noise estimate prior...... to the appearance of the speech signal which require noise robust voice activity detection and assumptions of stationary noise. However, both of these requirements are often not met and it is therefore of particular interest to investigate methods like the Quantile Based Noise Estimation (QBNE) mehtod which...... estimates the noise during speech and non-speech sections without the use of a voice activity detector. While the standard QBNE-method uses a fixed pre-defined quantile accross all frequency bands, this paper suggests adaptive QBNE (AQBNE) which adapts the quantile individually to each frequency band...

  10. Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

    KAUST Repository

    Altaf, Muhammad

    2013-08-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense that the estimation error in the H∞ filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H∞-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

  11. Robust Adaptive Tracking Control of a Class of Robot Manipulators with Model Uncertainties

    Directory of Open Access Journals (Sweden)

    G. Solís-Perales

    2012-01-01

    Full Text Available A robust tracking controller for robot manipulators measuring only the angular positions and considering model uncertainties is presented. It is considered that the model is uncertain; that is, the system parameters, nonlinear terms, external perturbations, and the friction effects in each robot joint are considered unknown. The controller is composed by two parts, a linearizing-like control feedback and a high-gain estimator. The main idea is to lump the uncertain terms into a new state which represents the dynamics of the uncertainties. This new state is then estimated in order to be compensated. In this way the resulting controller is robust. A numerical example for a RR robot manipulator is provided, in order to corroborate the results.

  12. Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

    Science.gov (United States)

    Whitacre, James M; Bender, Axel

    2010-06-15

    A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

  13. Robustness of Model Reference Adaptive Schemes with Respect to Modeling Errors.

    Science.gov (United States)

    1982-10-01

    regulation problem global stability properties are no longer guaranteed, but a region of attraction exists for exact adaptive regulation. In the case of... regulation problem and the tracking problem for the example (5.1) to (5.3). - a. Regulation: In the regulation problem expressions (5.8) to (5.10) become r(t...if y>0(1/u). 3Remark 5.2.2: As p- 0, domain D(p) becomes the whole space R , that is the adaptive regulation problem (5.15) to (5.18) is well posed

  14. MRFT-based design of robust and adaptive controllers for gas loop of oil–gas separator

    Directory of Open Access Journals (Sweden)

    Hamdati Al Shehhi

    2015-12-01

    Full Text Available The modified relay feedback test (MRFT, which was recently proposed as a continuous oscillation method for identification of the process parameters and controller tuning, is used for the design of a robust and an adaptive Proportional-Integral (PI controller for a gas loop in the oil–gas separator. The gas normally found in the separator is the natural gas (mostly methane which is contained in crude oil coming from the reservoir. The robust and adaptive PI controllers are developed from analysis of 64 operating modes corresponding to certain ranges of the gas inflow and liquid-level values. It is shown through the developed model and simulations that these operating modes have significant effect on the dynamics of the gas loop. Dynamic properties of the process in each mode are studied through MRFT. The controllers are designed in order to maintain the pressure during the change of the operating conditions. Performance of the designed control system is studied by simulations.

  15. CIRCLE 2 policy brief: Communicate uncertainties- design climate adaptation measures to be flexible and robust

    NARCIS (Netherlands)

    Pelt, van S.C.; Avelar, D.; Swart, R.J.

    2010-01-01

    This policy brief is directed towards funders and managers of climate change impacts and adaptation research programmes as well as policy makers in this area. It notes various challenges in addressing uncertainties in climate change research and policy and provides suggestions on how to address

  16. Robust control of boost PFC converter using adaptive PLL for line synchronization

    DEFF Research Database (Denmark)

    Török, Lajos; Mathe, Laszlo; Munk-Nielsen, Stig

    2013-01-01

    The continuous development of the digital processing technology made advanced control strategies available for switched-mode power-supply applications. This paper presents the study and implementation of an adaptive Phased-Locked Loop (PLL)-based grid-fault tolerant control of a boost PFC converter...

  17. Robustness of Adaptive Control Algorithms in the Presence of Unmodeled Dynamics,

    Science.gov (United States)

    1982-09-01

    result, two possible noch - tt (t (3a) anisms of instability are isolated and discussed. It is argued, that the destabilizing effects in the presence L t [J...to Modeling Errors, Ph.D. Thesis, Dept. of Elec. Eng., Univ. of Illinois at 2. A. uer mad A.S. Norse, *Adaptive Control of Urbana -ahampaign, Report

  18. HIFI-C: a robust and fast method for determining NMR couplings from adaptive 3D to 2D projections.

    Science.gov (United States)

    Cornilescu, Gabriel; Bahrami, Arash; Tonelli, Marco; Markley, John L; Eghbalnia, Hamid R

    2007-08-01

    We describe a novel method for the robust, rapid, and reliable determination of J couplings in multi-dimensional NMR coupling data, including small couplings from larger proteins. The method, "High-resolution Iterative Frequency Identification of Couplings" (HIFI-C) is an extension of the adaptive and intelligent data collection approach introduced earlier in HIFI-NMR. HIFI-C collects one or more optimally tilted two-dimensional (2D) planes of a 3D experiment, identifies peaks, and determines couplings with high resolution and precision. The HIFI-C approach, demonstrated here for the 3D quantitative J method, offers vital features that advance the goal of rapid and robust collection of NMR coupling data. (1) Tilted plane residual dipolar couplings (RDC) data are collected adaptively in order to offer an intelligent trade off between data collection time and accuracy. (2) Data from independent planes can provide a statistical measure of reliability for each measured coupling. (3) Fast data collection enables measurements in cases where sample stability is a limiting factor (for example in the presence of an orienting medium required for residual dipolar coupling measurements). (4) For samples that are stable, or in experiments involving relatively stronger couplings, robust data collection enables more reliable determinations of couplings in shorter time, particularly for larger biomolecules. As a proof of principle, we have applied the HIFI-C approach to the 3D quantitative J experiment to determine N-C' RDC values for three proteins ranging from 56 to 159 residues (including a homodimer with 111 residues in each subunit). A number of factors influence the robustness and speed of data collection. These factors include the size of the protein, the experimental set up, and the coupling being measured, among others. To exhibit a lower bound on robustness and the potential for time saving, the measurement of dipolar couplings for the N-C' vector represents a realistic

  19. 具滞后的区间Lurie型系统的鲁棒绝对稳定性%Robust Absolute Stability of Interval Lurie Type Systems With Time Delay

    Institute of Scientific and Technical Information of China (English)

    孙继涛; 邓飞其; 刘永清

    2001-01-01

    讨论了具滞后的区间非线性Lurie型控制系统的鲁棒绝对稳定性。用区间向量不等式、Lyapunov函数法和Riccati方程法研究了具滞后的区间Lurie型直接控制系统和具滞后的区间Lurie型间接控制系统的鲁棒绝对稳定性,得到了具滞后的区间非线性Lurie型控制系统鲁棒绝对稳定的一些充分条件,并给出了数值例子说明本文结论的有效性。%To deal with the problem of robust absolute stability for interval nonlinear Lurie type control system with time delay. The interval vector inequalities, Lyapunov function and Riccati equation are used to study the robust absolute stability of interval Lurie type direct control system and interval Lurie type indirect control system with time delay, the sufficient conditions of robust absolute stability for interval nonlinear Lurie direct control systems and interval nonlinear Lurie indirect control systems with time delay are respectively given. Example is made to illustrate our results.

  20. Robust Reference Intervals for Serum Kappa and Lambda Free Light Chains from a Multi Centre Study Population from Hyderabad, India: Myeloma Diagnostic Implications.

    Science.gov (United States)

    Mohammed, Noorjahan; Chandran, Priscilla Abraham; Kandregula, Madhavi; Mattaparthi, Ratna Deepika; Gundeti, Sadasivudu; Volturi, Jyotsna; Darapuneni, Radhika; Raju, Sree Bhushan; Dattatreya, Palanki Satya

    2016-01-01

    The International Myeloma Working Group considers the serum free light chain (SFLC) assay to be an adjunct to traditional tests. Apart from the FLC ratio, the absolute values of individual free light chains also are gaining importance as they appear to be more relevant in certain clinical settings. Automated assays are available for their determination. As laboratories put new test systems into use catering to different disease populations, they are required by accreditation and certification bodies to verify or establish performance specifications, including reference intervals (RIs) representative of their population. Our aim was to establish local RIs for SFLC in a multicentre representative healthy population using a robust method. There was no significant relationship between SFLC levels and age, gender and creatinine levels. The 95% RI for κSFLC was 4.81 to 33.86mg/L, for ? SFLC was 5.19 to 23.67mg/L and for κ/?SFLC was 0.36 to 2.33, significantly higher than the values given by the manufacturer. The κ/? SFLC ratio at 2.23, covering 100% of the data, showed 72% sensitivity (95% CI=39.0 - 94.0), 100% specificity (95% CI=71.5 - 100.0), 100% PPV (95% CI=21.5 - 100.0), 95% NPV (95% CI=75.4 - 99.9), and 79% accuracy (95% CI=56.0 - 93.0). In the patient group, kit RI for κ /? SFLC ratio classified 45.5% (n=5) as positive vs 9.1% (n=1) positive by the study RI, while the kit RI for kappa FLC classified 90.9% (n=10) as positive vs 54.5% (n=6) , indicating increased probability of false positive test results with the kit RI when applied to our patient population. Appropriate and specific reference intervals and criteria values result in fewer false-positive and false-negative results which means fewer wrong or missed diagnoses.

  1. Monitoring and robust adaptive control of fed-batch cultures of microorganisms exhibiting overflow metabolism [abstract

    Directory of Open Access Journals (Sweden)

    Vande Wouwer, A.

    2010-01-01

    Full Text Available Overflow metabolism characterizes cells strains that are likely to produce inhibiting by-products resulting from an excess of substrate feeding and a saturated respiratory capacity. The critical substrate level separating the two different metabolic pathways is generally not well defined. Monitoring of this kind of cultures, going from model identification to state estimation, is first discussed. Then, a review of control techniques which all aim at maximizing the cell productivity of fed-batch fermentations is presented. Two main adaptive control strategies, one using an estimation of the critical substrate level as set-point and another regulating the by-product concentration, are proposed. Finally, experimental investigations of an adaptive RST control scheme using the observer polynomial for the regulation of the ethanol concentration in Saccharomyces cerevisiae fed-batch cultures ranging from laboratory to industrial scales, are also presented.

  2. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    Science.gov (United States)

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed.

  3. Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

    2014-07-01

    Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This

  4. Multibeam echosounder data cleaning through a hierarchic adaptive and robust local surfacing

    Science.gov (United States)

    Debese, Nathalie; Moitié, Rodéric; Seube, Nicolas

    2012-09-01

    Multibeam echo sounders (MBES) datasets generally contain sporadic outlier points. The huge volumes of MBES datasets in a hydrographic framework require the use of semi-automatic techniques. In very shallow waters depth, data cleaning becomes a challenging task when potential dangers to navigation have to be carefully checked. The aim of our paper is to attempt this goal by combining two well-known techniques. The seafloor is constructed as an assemblage of surface elements with the help of a robust statistical approach. The local parameters model is a priori chosen, its scale is driven through a quadtree descending approach using subdivision rules based on both statistical and spatio-temporal inferences. Our multi resolution approach provides, with the algorithm outputs, a classification map that notes areas of concern.

  5. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    Directory of Open Access Journals (Sweden)

    Isabelle Bloch

    2007-01-01

    Full Text Available This paper describes a system for optical music recognition (OMR in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  6. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    Science.gov (United States)

    Rossant, Florence; Bloch, Isabelle

    2006-12-01

    This paper describes a system for optical music recognition (OMR) in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  7. Reducing the intensity and volume of interval training diminishes cardiovascular adaptation but not mitochondrial biogenesis in overweight/obese men.

    Science.gov (United States)

    Boyd, J Colin; Simpson, Craig A; Jung, Mary E; Gurd, Brendon J

    2013-01-01

    The purpose of this research was to determine if the adaptations to high intensity interval training (HIT) are mitigated when both intensity and training volume (i.e. exercise energy expenditure) are reduced. 19 overweight/obese, sedentary males (Age: 22.7±3.9 yrs, Body Mass Index: 31.4±2.6 kg/m(2), Waist Circumference: 106.5±6.6 cm) performed 9 sessions of interval training using a 1-min on, 1-min off protocol on a cycle ergometer over three weeks at either 70% (LO) or 100% (HI) peak work rate. Cytochrome oxidase I protein content, cytochrome oxidase IV protein content, and citrate synthase maximal activity all demonstrated similar increases between groups with a significant effect of training for each. β-hydroxyacyl-CoA dehydrogenase maximal activity tended to increase with training but did not reach statistical significance (p = 0.07). Peroxisome proliferator-activated receptor gamma coactivator-1α and silent mating type information regulator 2 homolog 1 protein contents also increased significantly (p = 0.047), while AMP-activated protein kinase protein content decreased following the intervention (p = 0.019). VO2peak increased by 11.0±7.4% and 27.7±4.4% in the LO and HI groups respectively with significant effects of both training (ptraining and a significant difference in the improvement between groups. There were no differences in perceived enjoyment or self-efficacy between groups despite significantly lower affect scores during training in the HI group. While improvements in aerobic capacity and exercise performance were different between groups, changes in oxidative capacity were similar despite reductions in both training intensity and volume.

  8. Head and Neck Margin Reduction With Adaptive Radiation Therapy: Robustness of Treatment Plans Against Anatomy Changes.

    Science.gov (United States)

    van Kranen, Simon; Hamming-Vrieze, Olga; Wolf, Annelisa; Damen, Eugène; van Herk, Marcel; Sonke, Jan-Jakob

    2016-11-01

    We set out to investigate loss of target coverage from anatomy changes in head and neck cancer patients as a function of applied safety margins and to verify a cone beam computed tomography (CBCT)-based adaptive strategy with an average patient anatomy to overcome possible target underdosage. For 19 oropharyngeal cancer patients, volumetric modulated arc therapy treatment plans (2 arcs; simultaneous integrated boost, 70 and 54.25 Gy; 35 fractions) were automatically optimized with uniform clinical target volume (CTV)-to-planning target volume margins of 5, 3, and 0 mm. We applied b-spline CBCT-to-computed tomography (CT) deformable registration to allow recalculation of the dose on modified CT scans (planning CT deformed to daily CBCT following online positioning) and dose accumulation in the planning CT scan. Patients with deviations in primary or elective CTV coverage >2 Gy were identified as candidates for adaptive replanning. For these patients, a single adaptive intervention was simulated with an average anatomy from the first 10 fractions. Margin reduction from 5 mm to 3 mm to 0 mm generally led to an organ-at-risk (OAR) mean dose (Dmean) sparing of approximately 1 Gy/mm. CTV shrinkage was mainly seen in the elective volumes (up to 10%), likely related to weight loss. Despite online repositioning, substantial systematic errors were present (>3 mm) in lymph node CTV, the parotid glands, and the larynx. Nevertheless, the average increase in OAR dose was small: maximum of 1.2 Gy (parotid glands, Dmean) for all applied margins. Loss of CTV coverage >2 Gy was found in 1, 3, and 7 of 73 CTVs, respectively. Adaptive intervention in 0-mm plans substantially improved coverage: in 5 of 7 CTVs (in 6 patients) to 2 Gy in 0-mm plans may be identified early in treatment using dose accumulation. A single intervention with an average anatomy derived from CBCT effectively mitigates discrepancies. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Study on the Robot Robust Adaptive Control Based on Neural Networks

    Institute of Scientific and Technical Information of China (English)

    温淑焕; 王洪瑞; 吴丽艳

    2003-01-01

    Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.

  10. Adaptive robust control of chaotic oscillations in power system with excitation limits

    Institute of Scientific and Technical Information of China (English)

    Wei Du-Qu; Luo Xiao-Shu

    2007-01-01

    With system parameters falling into a certain area, power system with excitation limits experiences complicated chaotic oscillations which threaten the secure and stable operation of power system. In this paper, to control these unwanted chaotic oscillations, a straightforward adaptive chaos controller based on Lyapunov asymptotical stability theory is designed. Since the presented controller does not need to change the controlled system structure and not to use any information of system except the system state variables, the designed controller is simple and desirable.Simulation results show that the proposed control law is very effective. This work is helpful to maintain the power system's security operation.

  11. Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators

    Science.gov (United States)

    Nogueira, Samuel L.; Pazelli, Tatiana F. P. A. T.; Siqueira, Adriano A. G.; Terra, Marco H.

    2013-01-01

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear ℋ∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose. PMID:23598503

  12. Experimental investigation on adaptive robust controller designs applied to constrained manipulators.

    Science.gov (United States)

    Nogueira, Samuel L; Pazelli, Tatiana F P A T; Siqueira, Adriano A G; Terra, Marco H

    2013-04-18

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear H∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose.

  13. Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators

    Directory of Open Access Journals (Sweden)

    Marco H. Terra

    2013-04-01

    Full Text Available In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear H∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose.

  14. Adaptive imaging system with spatial light modulator for robust shape measurement of partially specular objects.

    Science.gov (United States)

    Jeong, Joongki; Kim, Min Young

    2010-12-20

    In imaging systems, when specular surfaces responding sensitively to varying illumination conditions are imaged on groups of CCD pixels using imaging optics, the obtained image usually suffers from pixel saturation, resulting in smearing or blooming phenomena. These problems are then serious obstacles when applying structured light-based optical profiling methods to the shape measurement of general objects with partially specular surfaces. Therefore, this paper combines a phase-based profiling system with an with an adaptive spatial light modulator in the imaging part for measuring the three-dimensional shapes of objects with an advanced dynamic range. The use of a spatial light modulator in front of a CCD camera prevents the image sensor from being saturated, as the pixel transmittance is controlled by monitoring the input images and providing modulator feedback signals over time and space. When using the proposed system, since the projected fringes are effectively imaged on the CCD without any pixel saturation, phase information according to the object's shape can be correctly extracted from non-saturated images. The configuration of the proposed system and transmittance control scheme are explained in detail, plus the performance is verified through a series of experiments, in which phase information was successfully extracted from areas that are not normally measurable due to saturation. Based on the results, the proposed shape measurement system showed a more advanced adaptive dynamic range when compared with a conventional system.

  15. Demonstration of a 17 cm robust carbon fiber deformable mirror for adaptive optics

    Energy Technology Data Exchange (ETDEWEB)

    Ammons, S M; Hart, M; Coughenour, B; Romeo, R; Martin, R; Rademacher, M

    2011-09-12

    Carbon-fiber reinforced polymer (CFRP) composite is an attractive material for fabrication of optics due to its high stiffness-to-weight ratio, robustness, zero coefficient of thermal expansion (CTE), and the ability to replicate multiple optics from the same mandrel. We use 8 and 17 cm prototype CFRP thin-shell deformable mirrors to show that residual CTE variation may be addressed with mounted actuators for a variety of mirror sizes. We present measurements of surface quality at a range of temperatures characteristic of mountaintop observatories. For the 8 cm piece, the figure error of the Al-coated reflective surface under best actuator correction is {approx}43 nm RMS. The 8 cm mirror has a low surface error internal to the outer ring of actuators (17 nm RMS at 20 C and 33 nm RMS at -5 C). Surface roughness is low (< 3 nm P-V) at a variety of temperatures. We present new figure quality measurements of the larger 17 cm mirror, showing that the intra-actuator figure error internal to the outer ring of actuators (38 nm RMS surface with one-third the actuator density of the 8 cm mirror) does not scale sharply with mirror diameter.

  16. Content-adaptive robust error concealment for packet-lossy H.264 video streaming

    Institute of Scientific and Technical Information of China (English)

    LIAO Ning; YAN Dan; QUAN Zi-yi; MEN Ai-dong

    2006-01-01

    In this paper, we present a spatio-temporal post-processing error concealment (EC) algorithm designed initially for a H.264 video-streaming scheme over packet-lossy networks. It aims at optimizing the subjective quality of the restored video under the constraints of low delay and computational complexity, which are critical to real-time applications and portable devices having limited resources. Specifically, it takes into consideration the physical property of motion field in order to achieve more meaningful perceptual video quality, in addition to the improved objective PSNR. Further, a simple bilinear spatial interpolation approach is combined with the improved boundary-match (B-M) based temporal EC approach according to texture and motion activity analysis. Finally, we propose a low complexity temporal EC method based on motion vector interpolation as a replacement of the B-M based approach in the scheme under low-computation requirement, or as a complement to further improve the scheme's performance in applications having enough computation resources. Extensive experiments demonstrated that the proposal features not only better reconstruction, objectively and subjectively, than JM benchmark, but also robustness to different video sequences.

  17. An experimental comparison of proportional-integral, sliding mode, and robust adaptive control for piezo-actuated nanopositioning stages.

    Science.gov (United States)

    Gu, Guo-Ying; Zhu, Li-Min

    2014-05-01

    This paper presents a comparative study of the proportional-integral (PI) control, sliding mode control (SMC), and robust adaptive control (RAC) for applications to piezo-actuated nanopositioning stages without the inverse hysteresis construction. For a fair comparison, the control parameters of the SMC and RAC are selected on the basis of the well-tuned parameters of the PI controller under same desired trajectories and sampling frequencies. The comparative results show that the RAC improves the tracking performance by 17 and 37 times than the PI controller in terms of the maximum tracking error e(m) and the root mean tracking error e(rms), respectively, while the RAC improves the tracking performance by 7 and 9 times than the SMC in terms of e(m) and e(rms), respectively.

  18. RSAD: A Robust Distributed Contention-Based Adaptive Mechanism for IEEE 802.11 Wireless LANs

    Institute of Scientific and Technical Information of China (English)

    Yong Peng; Shi-Duan Cheng; Jun-Liang Chen

    2005-01-01

    Previous researches have shown that Distributed Coordination Function (DCF) access mode of IEEE 802.11 has lower performance in heavy contention environment. Based on the in-depth analysis of IEEE 802.11 DCF, NSAD (New Self-adapt DCF-based protocol) has been proposed to improve system saturation throughput in heavy contention condition.The initial contention window tuning algorithm of NSAD is proved effective in error-free environment. However, problems concerning the exchanging of initial contention window occur in error-prone environment. Based on the analysis of NSAD's performance in error-prone environment, RSAD is proposed to further enhance the performance. Simulation in a more real shadowing error-prone environment is done to compare the performance of NSAD and RSAD and results have shown that RSAD can achieve further performance improvement as expected in the error-prone environment than NSAD (i.e., better goodput and fairness index).

  19. A Robust Neuro_Adaptive Control of Three Link SCARA Robot with Mass Uncertainty

    Directory of Open Access Journals (Sweden)

    Mansooreh Taslimi

    2013-10-01

    Full Text Available The purpose of this paper is design of a neuro-adaptive controller for SCARA mechanical arm. First, a brief description of the work that has been done on similar systems will be presented and then using the Euler - Lagrange, based on kinetic and potential energy of the system, the dynamical equations of system will be calculated. The proposed controller is used to provide a suitable Lyapunov function, expression and comparative law will guarantee the stability of the closed loop system. All signals in the closed loop system are limited and the error signal tends asymptotically to origin. The control system is designed to demonstrate the efficacy of proposed controller on three links SCARA robot is implemented, the results of the controller performance guarantees.

  20. Robustness and Radiation Resistance of the Pale Grass Blue Butterfly from Radioactively Contaminated Areas: A Possible Case of Adaptive Evolution.

    Science.gov (United States)

    Nohara, Chiyo; Hiyama, Atsuki; Taira, Wataru; Otaki, Joji M

    2017-02-11

    The pale grass blue butterfly, Zizeeria maha, has been used to evaluate biological impacts of the Fukushima nuclear accident in March 2011. Here, we examined the possibility that butterflies have adapted to be robust in the contaminated environment. Larvae (n = 2432) were obtained from adult butterflies (n = 20) collected from 7 localities with various contamination levels in May 2012, corresponding to the 7th generation after the accident. When the larvae were reared on non-contaminated host plant leaves from Okinawa, the normality rates of natural exposure without artificial irradiation (as an indication of robustness) were high not only in the least contaminated locality but also in the most contaminated localities. The normality rates were similarly obtained when the larvae were reared on non-contaminated leaves with external irradiation or on contaminated leaves from Fukushima to deliver internal irradiation. The normality rate of natural exposure and that of external or internal exposure were correlated, suggesting that radiation resistance (or susceptibility) likely reflects general state of health. The normality rate of external or internal exposure was divided by the relative normality rate of natural exposure, being defined as the resistance value. The resistance value was the highest in the populations of heavily contaminated localities and was inversely correlated with the distance from the Fukushima Dai-ichi nuclear power plant. These results suggest that the butterfly population might have adapted to the contaminated environment within approximately 1 year after the accident. The present study may partly explain the decrease in mortality and abnormality rates later observed in the contaminated areas. © The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision-Making Framework for Climate Change Adaptation.

    Science.gov (United States)

    Shortridge, Julie E; Guikema, Seth D

    2016-12-01

    There is increasing concern over deep uncertainty in the risk analysis field as probabilistic models of uncertainty cannot always be confidently determined or agreed upon for many of our most pressing contemporary risk challenges. This is particularly true in the climate change adaptation field, and has prompted the development of a number of frameworks aiming to characterize system vulnerabilities and identify robust alternatives. One such methodology is robust decision making (RDM), which uses simulation models to assess how strategies perform over many plausible conditions and then identifies and characterizes those where the strategy fails in a process termed scenario discovery. While many of the problems to which RDM has been applied are characterized by multiple objectives, research to date has provided little insight into how treatment of multiple criteria impacts the failure scenarios identified. In this research, we compare different methods for incorporating multiple objectives into the scenario discovery process to evaluate how they impact the resulting failure scenarios. We use the Lake Tana basin in Ethiopia as a case study, where climatic and environmental uncertainties could impact multiple planned water infrastructure projects, and find that failure scenarios may vary depending on the method used to aggregate multiple criteria. Common methods used to convert multiple attributes into a single utility score can obscure connections between failure scenarios and system performance, limiting the information provided to support decision making. Applying scenario discovery over each performance metric separately provides more nuanced information regarding the relative sensitivity of the objectives to different uncertain parameters, leading to clearer insights on measures that could be taken to improve system robustness and areas where additional research might prove useful. © 2016 Society for Risk Analysis.

  2. Robustness, vulnerability, and adaptive capacity in small-scale social-ecological systems: The Pumpa Irrigation System in Nepal

    Directory of Open Access Journals (Sweden)

    Armando A. Rodriguez

    2010-09-01

    Full Text Available Change in freshwater availability is arguably one of the most pressing issues associated with global change. Agriculture, which uses roughly 70% of the total global freshwater supply, figures prominently among sectors that may be adversely affected by global change. Of specific concern are small-scale agricultural systems that make up nearly 90% of all farming systems and generate 40% of agricultural output worldwide. These systems are experiencing a range of novel shocks, including increased variability in precipitation and competing demands for water and labor that challenge their capacity to maintain agricultural output. This paper employs a robustness-vulnerability trade-off framework to explore the capacity of these small-scale systems to cope with novel shocks and directed change. Motivated by the Pumpa Irrigation System in Nepal, we develop and analyze a simple model of rice-paddy irrigation and use it to demonstrate how institutional arrangements may, in becoming very well tuned to cope with specific shocks and manage particular human interactions associated with irrigated agriculture, generate vulnerabilities to novel shocks. This characterization of robustness-vulnerability trade-off relationships is then used to inform policy options to improve the capacity of small-scale irrigation systems to adapt to changes in freshwater availability.

  3. Biologically-inspired robust and adaptive multi-sensor fusion and active control

    Science.gov (United States)

    Khosla, Deepak; Dow, Paul A.; Huber, David J.

    2009-04-01

    In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space; (2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them; and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt- zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs.

  4. Robust Adaptive Neurocontrol of SISO Nonlinear Systems Preceded by Unknown Deadzone

    Directory of Open Access Journals (Sweden)

    J. Humberto Pérez-Cruz

    2012-01-01

    Full Text Available In this study, the problem of controlling an unknown SISO nonlinear system in Brunovsky canonical form with unknown deadzone input in such a way that the system output follows a specified bounded reference trajectory is considered. Based on universal approximation property of the neural networks, two schemes are proposed to handle this problem. The first scheme utilizes a smooth adaptive inverse of the deadzone. By means of Lyapunov analyses, the exponential convergence of the tracking error to a bounded zone is proven. The second scheme considers the deadzone as a combination of a linear term and a disturbance-like term. Thus, the estimation of the deadzone inverse is not required. By using a Lyapunov-like analyses, the asymptotic converge of the tracking error to a bounded zone is demonstrated. Since this control strategy requires the knowledge of a bound for an uncertainty/disturbance term, a procedure to find such bound is provided. In both schemes, the boundedness of all closed-loop signals is guaranteed. A numerical experiment shows that a satisfactory performance can be obtained by using any of the two proposed controllers.

  5. Robust and adaptive techniques for numerical simulation of nonlinear partial differential equations of fractional order

    Science.gov (United States)

    Owolabi, Kolade M.

    2017-03-01

    In this paper, some nonlinear space-fractional order reaction-diffusion equations (SFORDE) on a finite but large spatial domain x ∈ [0, L], x = x(x , y , z) and t ∈ [0, T] are considered. Also in this work, the standard reaction-diffusion system with boundary conditions is generalized by replacing the second-order spatial derivatives with Riemann-Liouville space-fractional derivatives of order α, for 0 < α < 2. Fourier spectral method is introduced as a better alternative to existing low order schemes for the integration of fractional in space reaction-diffusion problems in conjunction with an adaptive exponential time differencing method, and solve a range of one-, two- and three-components SFORDE numerically to obtain patterns in one- and two-dimensions with a straight forward extension to three spatial dimensions in a sub-diffusive (0 < α < 1) and super-diffusive (1 < α < 2) scenarios. It is observed that computer simulations of SFORDE give enough evidence that pattern formation in fractional medium at certain parameter value is practically the same as in the standard reaction-diffusion case. With application to models in biology and physics, different spatiotemporal dynamics are observed and displayed.

  6. Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis

    CERN Document Server

    Guay, Alain; Lazarova, Stepana

    2011-01-01

    A new test is proposed for the weak white noise null hypothesis. The test is based on an automatic choice of the order for a Box-Pierce or Hong test statistic. The simplest version of the test uses Lobato (2001) or Kuan and Lee (2006) HAC critical values but the procedure is flexible enough to improve the detection properties of any prescribed test. This can allow for instance to calibrate the test for optimal detection of specific alternatives as in Delgado and Velasco (2010a). The data-driven order choice is tailored to give a test which achieves adaptive rate-optimality against several classes of alternatives, namely (i) alternatives with a large enough number of autocorrelation coefficients converging to 0 faster than the parametric rate; (ii) alternatives with a "peak and valley" spectral density function. A simulation experiment leads to prefer the Box-Pierce version of the test, both under the null and the alternative. An application to daily exchange rate returns illustrates the usefulness of the prop...

  7. Adapting to a Changing Colorado River: Making Future Water Deliveries More Reliable Through Robust Management Strategies

    Science.gov (United States)

    Groves, D.; Bloom, E.; Fischbach, J. R.; Knopman, D.

    2013-12-01

    The U.S. Bureau of Reclamation and water management agencies representing the seven Colorado River Basin States initiated the Colorado River Basin Study in January 2010 to evaluate the resiliency of the Colorado River system over the next 50 years and compare different options for ensuring successful management of the river's resources. RAND was asked to join this Basin Study Team in January 2012 to help develop an analytic approach to identify key vulnerabilities in managing the Colorado River basin over the coming decades and to evaluate different options that could reduce this vulnerability. Using a quantitative approach for planning under uncertainty called Robust Decision Making (RDM), the RAND team assisted the Basin Study by: identifying future vulnerable conditions that could lead to imbalances that could cause the basin to be unable to meet its water delivery objectives; developing a computer-based tool to define 'portfolios' of management options reflecting different strategies for reducing basin imbalances; evaluating these portfolios across thousands of future scenarios to determine how much they could improve basin outcomes; and analyzing the results from the system simulations to identify key tradeoffs among the portfolios. This talk will describe RAND's contribution to the Basin Study, focusing on the methodologies used to to identify vulnerabilities for Upper Basin and Lower Basin water supply reliability and to compare portfolios of options. Several key findings emerged from the study. Future Streamflow and Climate Conditions Are Key: - Vulnerable conditions arise in a majority of scenarios where streamflows are lower than historical averages and where drought conditions persist for eight years or more. - Depending where the shortages occur, problems will arise for delivery obligations for the upper river basin and the lower river basin. The lower river basin is vulnerable to a broader range of plausible future conditions. Additional Investments in

  8. Robust adaptive constrained backstepping flight controller design for re-entry reusable launch vehicle under input constraint

    Directory of Open Access Journals (Sweden)

    Qin Zou

    2015-09-01

    Full Text Available A nonlinear constrained controller is designed for a reusable launch vehicle during re-entry phase in the presence of model uncertainty, external disturbance, and input constraint, via combining sliding mode control and adaptive backstepping control. Since the complex coupling between the translational and rotational dynamics of reusable launch vehicle, a control-oriented model derived from rotational dynamic is used for controller design. During the virtual control input design procedure, a dynamic robust term is utilized to compensate for the uncertainty. In addition, a filter is applied to handle “explosion of terms” problem during the actual control input design. To reduce the computational burden, adaptive law is used to evaluate the unknown norm bound of the lumped uncertainty. An auxiliary system is constructed to compensate for the input constraint effect. The stability of the closed-loop system is analyzed based on Lyapunov theory. Simulation results demonstrate the validity of the developed controller in providing stable tracking of the guidance command by numerical simulation on the 6-degree-of-freedom model of reusable launch vehicle.

  9. Low robustness of increasing reservoir capacity for adaptation to climate change: A case study for an agricultural river basin

    Science.gov (United States)

    Kim, Daeha; Eum, Hyung-Il

    2017-04-01

    With growing concerns of the uncertain climate change, investments in water infrastructures are considered as adaptation policies for water managers and stakeholders despite their negative impacts on the environment. Particularly in regions with limited water availability or conflicting demands, building reservoirs and/or augmenting their storage capacity were already adopted for alleviating influences of the climate change. This study provides a probabilistic assessment of climate change impacts on water scarcity in a river system regulated by an agricultural reservoir in South Korea, which already increased its storage capacity for water supply. For the assessment, we developed the climate response functions (CRFs) defined as relationships between bi-decadal system performance indicators (reservoir reliability and vulnerability) and corresponding climatic conditions, using hydrological models with 10,000-year long stochastic generation of daily precipitation and temperatures. The climate change impacts were assessed by plotting 52 downscaled climate projections of general circulation models (GCMs) on the CRFs. Results indicated that augmented reservoir capacity makes the reservoir system more sensitive to changes in long-term averages of precipitation and temperatures despite improved system performances. Increasing reservoir capacity is unlikely to be "no regret" adaptation policy for the river system. On the other hand, converting the planting strategy from transplanting to direct sowing (i.e., a demand control) could be a more robust to bi-decadal climatic changes based on CRFs and thus could be good to be a no-regret policy.

  10. Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model.

    Science.gov (United States)

    Maindal, Helle Terkildsen; Kayser, Lars; Norgaard, Ole; Bo, Anne; Elsworth, Gerald R; Osborne, Richard H

    2016-01-01

    Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

  11. Reducing the intensity and volume of interval training diminishes cardiovascular adaptation but not mitochondrial biogenesis in overweight/obese men.

    Directory of Open Access Journals (Sweden)

    J Colin Boyd

    Full Text Available OBJECTIVE: The purpose of this research was to determine if the adaptations to high intensity interval training (HIT are mitigated when both intensity and training volume (i.e. exercise energy expenditure are reduced. METHODS: 19 overweight/obese, sedentary males (Age: 22.7±3.9 yrs, Body Mass Index: 31.4±2.6 kg/m(2, Waist Circumference: 106.5±6.6 cm performed 9 sessions of interval training using a 1-min on, 1-min off protocol on a cycle ergometer over three weeks at either 70% (LO or 100% (HI peak work rate. RESULTS: Cytochrome oxidase I protein content, cytochrome oxidase IV protein content, and citrate synthase maximal activity all demonstrated similar increases between groups with a significant effect of training for each. β-hydroxyacyl-CoA dehydrogenase maximal activity tended to increase with training but did not reach statistical significance (p = 0.07. Peroxisome proliferator-activated receptor gamma coactivator-1α and silent mating type information regulator 2 homolog 1 protein contents also increased significantly (p = 0.047, while AMP-activated protein kinase protein content decreased following the intervention (p = 0.019. VO2peak increased by 11.0±7.4% and 27.7±4.4% in the LO and HI groups respectively with significant effects of both training (p<0.001 and interaction (p = 0.027. Exercise performance improved by 8.6±7.6% in the LO group and 14.1±4.3% in the HI group with a significant effect of training and a significant difference in the improvement between groups. There were no differences in perceived enjoyment or self-efficacy between groups despite significantly lower affect scores during training in the HI group. CONCLUSIONS: While improvements in aerobic capacity and exercise performance were different between groups, changes in oxidative capacity were similar despite reductions in both training intensity and volume.

  12. Fibre-specific responses to endurance and low volume high intensity interval training: striking similarities in acute and chronic adaptation.

    Directory of Open Access Journals (Sweden)

    Trisha D Scribbans

    Full Text Available The current study involved the completion of two distinct experiments. Experiment 1 compared fibre specific and whole muscle responses to acute bouts of either low-volume high-intensity interval training (LV-HIT or moderate-intensity continuous endurance exercise (END in a randomized crossover design. Experiment 2 examined the impact of a six-week training intervention (END or LV-HIT; 4 days/week, on whole body and skeletal muscle fibre specific markers of aerobic and anaerobic capacity. Six recreationally active men (Age: 20.7 ± 3.8 yrs; VO2peak: 51.9 ± 5.1 mL/kg/min reported to the lab on two separate occasions for experiment 1. Following a muscle biopsy taken in a fasted state, participants completed an acute bout of each exercise protocol (LV-HIT: 8, 20-second intervals at ∼ 170% of VO2peak separated by 10 seconds of rest; END: 30 minutes at ∼ 65% of VO2peak, immediately followed by a muscle biopsy. Glycogen content of type I and IIA fibres was significantly (p<0.05 reduced, while p-ACC was significantly increased (p<0.05 following both protocols. Nineteen recreationally active males (n = 16 and females (n = 3 were VO2peak-matched and assigned to either the LV-HIT (n = 10; 21 ± 2 yrs or END (n = 9; 20.7 ± 3.8 yrs group for experiment 2. After 6 weeks, both training protocols induced comparable increases in aerobic capacity (END: Pre: 48.3 ± 6.0, Mid: 51.8 ± 6.0, Post: 55.0 ± 6.3 mL/kg/min LV-HIT: Pre: 47.9 ± 8.1, Mid: 50.4 ± 7.4, Post: 54.7 ± 7.6 mL/kg/min, fibre-type specific oxidative and glycolytic capacity, glycogen and IMTG stores, and whole-muscle capillary density. Interestingly, only LV-HIT induced greater improvements in anaerobic performance and estimated whole-muscle glycolytic capacity. These results suggest that 30 minutes of END exercise at ∼ 65% VO2peak or 4 minutes of LV-HIT at ∼ 170% VO2peak induce comparable changes in the intra-myocellular environment (glycogen content and signaling activation

  13. Science-society collaboration for robust adaptation planning in water management - The Maipo River Basin in Chile

    Science.gov (United States)

    Ocampo Melgar, Anahí; Vicuña, Sebastián; Gironás, Jorge

    2015-04-01

    The Metropolitan Region (M.R.) in Chile is populated by over 6 million people and supplied by the Maipo River and its large number of irrigation channels. Potential environmental alterations caused by global change will extremely affect managers and users of water resources in this semi-arid basin. These hydro-climatological impacts combined with demographic and economic changes will be particularly complex in the city of Santiago, due to the diverse, counterpoised and equally important existing activities and demands. These challenges and complexities request the implementation of flexible plans and actions to adapt policies, institutions, infrastructure and behaviors to a new future with climate change. Due to the inherent uncertainties in the future, a recent research project entitled MAPA (Maipo Adaptation Plan for its initials in Spanish) has formed a collaborative science-society platform to generate insights into the vulnerabilities, challenges and possible mitigation measures that would be necessary to deal with the potential changes in the M.R. This large stakeholder platform conformed by around 30 public, private and civil society organizations, both at the local and regional level and guided by a Robust Decision Making Framework (RDMF) has identified vulnerabilities, future scenarios, performance indicators and mitigation measures for the Maipo River basin. The RDMF used in this project is the XLRM framework (Lempert et al. 2006) that incorporates policy levers (L), exogenous uncertainties (X), measures of performance standards (M) and relationships (R) in an interlinked process. Both stakeholders' expertise and computational capabilities have been used to create hydrological models for the urban, rural and highland sectors supported also by the Water Evaluation and Planning system software (WEAP). The identification of uncertainties and land use transition trends was used to develop future development scenarios to explore possible water management

  14. High-intensity interval and endurance training are associated with divergent skeletal muscle adaptations in a rodent model of hypertension.

    Science.gov (United States)

    Holloway, Tanya M; Bloemberg, Darin; da Silva, Mayne L; Quadrilatero, Joe; Spriet, Lawrence L

    2015-06-01

    Skeletal muscle is extremely adaptable to a variety of metabolic challenges, as both traditional moderate-intensity endurance (ET) and high-intensity interval training (HIIT) increases oxidative potential in a coordinated manner. Although these responses have been clearly demonstrated in healthy individuals, it remains to be determined whether both produce similar responses in the context of hypertension, one of the most prevalent and costly diseases worldwide. Therefore, in the current study, we used the Dahl sodium-sensitive rat, a model of hypertension, to determine the molecular responses to 4 wk of either ET or HIIT in the red (RG) and white gastrocnemius (WG) muscles. In the RG, both ET and HIIT increased the content of electron transport chain proteins and increased succinate dehydrogenase (SDH) content in type I fibers. Although both intensities of exercise shifted fiber type in RG (increased IIA, decreased IIX), only HIIT was associated with a reduction in endothelial nitric oxide synthase and an increase in HIF-1α proteins. In the WG, both ET and HIIT increased markers of the electron transport chain; however, HIIT decreased SDH content in a fiber-specific manner. ET increased type IIA, decreased IIB fibers, and increased capillarization, while, in contrast, HIIT increased the percentage of IIB fibers, decreased capillary-to-fiber ratios, decreased endothelial nitric oxide synthase, and increased hypoxia inducible factor-1α (HIF-1α) protein. Altogether, these data show that unlike in healthy animals, ET and HIIT have divergent effects in the skeletal muscle of hypertensive rats. This suggests ET may be optimal at improving the oxidative capacity of skeletal muscle in animals with hypertension.

  15. β-Alanine Supplementation Does Not Augment the Skeletal Muscle Adaptive Response to 6 Weeks of Sprint Interval Training.

    Science.gov (United States)

    Cochran, Andrew J R; Percival, Michael E; Thompson, Sara; Gillen, Jenna B; MacInnis, Martin J; Potter, Murray A; Tarnopolsky, Mark A; Gibala, Martin J

    2015-12-01

    Sprint interval training (SIT), repeated bouts of high-intensity exercise, improves skeletal muscle oxidative capacity and exercise performance. β-alanine (β-ALA) supplementation has been shown to enhance exercise performance, which led us to hypothesize that chronic β-ALA supplementation would augment work capacity during SIT and augment training-induced adaptations in skeletal muscle and performance. Twenty-four active but untrained men (23 ± 2 yr; VO2peak = 50 ± 6 mL · kg(-1) · min(-1)) ingested 3.2 g/day of β-ALA or a placebo (PLA) for a total of 10 weeks (n = 12 per group). Following 4 weeks of baseline supplementation, participants completed a 6-week SIT intervention. Each of 3 weekly sessions consisted of 4-6 Wingate tests, i.e., 30-s bouts of maximal cycling, interspersed with 4 min of recovery. Before and after the 6-week SIT program, participants completed a 250-kJ time trial and a repeated sprint test. Biopsies (v. lateralis) revealed that skeletal muscle carnosine content increased by 33% and 52%, respectively, after 4 and 10 weeks of β-ALA supplementation, but was unchanged in PLA. Total work performed during each training session was similar across treatments. SIT increased markers of mitochondrial content, including cytochome c oxidase (40%) and β-hydroxyacyl-CoA dehydrogenase maximal activities (19%), as well as VO2peak (9%), repeated-sprint capacity (5%), and 250-kJ time trial performance (13%), but there were no differences between treatments for any measure (p .05, interaction effects). The training stimulus may have overwhelmed any potential influence of β-ALA, or the supplementation protocol was insufficient to alter the variables to a detectable extent.

  16. The Effects of Sprint Interval vs. Continuous Endurance Training on Physiological and Metabolic Adaptations in Young Healthy Adults

    Directory of Open Access Journals (Sweden)

    Nalcakan Gulbin Rudarli

    2014-12-01

    Full Text Available The purpose of this study was to compare the effects of sprint interval training (SIT and continuous endurance training (CET on selected anthropometric, aerobic, and anaerobic performance indices as well as the blood lipid profile, inflammatory and muscle damage markers in healthy young males. Fifteen recreationally active male volunteers (age: 21.7 ±2.2 years, body mass: 83.0 ±8.0 kg, body height: 1.82 ±0.05 m were divided into two groups according to their initial VO2max levels. Training programs were conducted 3 times per week for 7 weeks. The SIT program consisted of 4-6 Wingate anaerobic sprints with a 4.5 min recovery, while CET consisted of 30-50 min cycling at 60% VO2max. Biochemical, anthropometric and fitness assessments were performed both pre and post-intervention. Significant improvements in VO2max, anaerobic power and capacity, and VO2 utilization during the submaximal workout and significant decreases in body fat and in waist circumference after the intervention occurred in both SIT and CET groups. Significantly greater gross efficiency was measured in the CET group. No differences in the lipid profile or serum levels of inflammatory, myocardial and skeletal muscle damage markers were observed after the training period. The study results agree with the effectiveness of a 30 s all-out training program with a reduced time commitment for anthropometric, aerobic and anaerobic adaptation and eliminate doubts about its safety as a model.

  17. Adaptation of the QT interval to heart rate changes in isolated perfused guinea pig heart: influence of amiodarone and D-sotalol.

    Science.gov (United States)

    Padrini, R; Speranza, G; Nollo, G; Bova, S; Piovan, D; Antolini, R; Ferrari, M

    1997-05-01

    The inadequacy of the QT interval to shorten following heart rate increase is a feature of the inherited long QT syndrome and may have a role in the genesis of the typical arrhythmias associated with this syndrome (torsade des pointes). The aim of our study was to evaluate whether drugs that prolong the QT interval, such as amiodarone and D-sotalol, may also impair the ability of the QT interval to adapt to sudden heart rate changes. Experiments were carried out on isolated perfused guinea pig hearts (Langendorff preparation). Driving frequency was changed, in steps, every two minutes (Hz: 2.5-3-2.5-3.75-2.5-5-2.5), while epicardial ECG was continuously recorded on magnetic tape. QT interval was automatically measured by means of a beat-by-beat analysis program. D-sotalol was added to the perfusion medium at a concentration of 4 micrograms ml-1, while amiodarone was administered, before in vitro evaluation, for seven days (50 mg kg-1 per day, intraperitoneally). In control experiments two phases of QT adaptation were identified: an abrupt QT shortening at the first beat after frequency change (QT1), followed by a gradual, exponential QT shortening that reached a new steady state in about 1 min (half life: 13 sec). The electrical restitution curve (the relation between QT1 and the corresponding diastolic interval) had a rate constant of 57 +/- 8 ms. Neither drug changed the slow component of QT adaptation. However, both drugs increased the ability of QT to shorten upon premature stimulation: D-sotalol by increasing the rate constant of the restitution curve and amiodarone by decreasing the y-intercept. Our results indicate that D-sotalol and amiodarone do not impair QT shortening during tachycardia but, on the contrary, they may favour QT adaptation, thus reducing the likelihood of the potentially lethal 'R on T phenomenon'. This may be an additional mechanism by which these drugs can exert their antifibrillatory action.

  18. A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data.

    Science.gov (United States)

    Silva Filho, Telmo M; Souza, Renata M C R; Prudêncio, Ricardo B C

    2016-08-01

    Some complex data types are capable of modeling data variability and imprecision. These data types are studied in the symbolic data analysis field. One such data type is interval data, which represents ranges of values and is more versatile than classic point data for many domains. This paper proposes a new prototype-based classifier for interval data, trained by a swarm optimization method. Our work has two main contributions: a swarm method which is capable of performing both automatic selection of features and pruning of unused prototypes and a generalized weighted squared Euclidean distance for interval data. By discarding unnecessary features and prototypes, the proposed algorithm deals with typical limitations of prototype-based methods, such as the problem of prototype initialization. The proposed distance is useful for learning classes in interval datasets with different shapes, sizes and structures. When compared to other prototype-based methods, the proposed method achieves lower error rates in both synthetic and real interval datasets.

  19. Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

    Science.gov (United States)

    Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

    2011-12-01

    In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

  20. Physiological and Health-Related Adaptations to Low-Volume Interval Training: Influences of Nutrition and Sex

    OpenAIRE

    Gibala, Martin J.; Gillen, Jenna B.; Michael E Percival

    2014-01-01

    Interval training refers to the basic concept of alternating periods of relatively intense exercise with periods of lower-intensity effort or complete rest for recovery. Low-volume interval training refers to sessions that involve a relatively small total amount of exercise (i.e. ≤10 min of intense exercise), compared with traditional moderate-intensity continuous training (MICT) protocols that are generally reflected in public health guidelines. In an effort to standardize terminology, a cla...

  1. Robust Scientists

    DEFF Research Database (Denmark)

    Gorm Hansen, Birgitte

    2012-01-01

    as the analytical framework for descri bing the complex relationship between academic science and its so called “external” habitat. Although relational skills and adaptability do seem to be at the heart of successful research management, the key to success does not lie with the ability to assimilate to industrial...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...... and industrial intere sts. The paper concludes by stressing the potential danger of policy habitats who have promoted the evolution of robust scientists based on a competitive system where only the fittest survive. Robust scientists, it is argued, have the potential to become a new “invasive species...

  2. Robustez de um controlador adaptativo proposto à perturbações limitadas = Robustness of a proposed adaptive controller to limited disturbances

    Directory of Open Access Journals (Sweden)

    Nardênio Almeida Martins

    2005-01-01

    Full Text Available Este artigo apresenta o projeto de um controlador adaptativo e robusto de robôs manipuladores no espaço de juntas. Uma nova lei de controle adaptativo composta, contendo um termo adicional robusto e que usa o erro de predição e os erros de seguimento para direcionar a estimação de parâmetros é baseada na passividade e no método direto deLyapunov. A convergência e a estabilidade global são mostradas para o algoritmo de controle adaptativo e robusto. Simulações numéricas são fornecidas para demonstrar o desempenho e a robustez do algoritmo proposto.This article presents a robust and adaptive control design for robotmanipulators in joint space coordinates. A new composite adaptive control law, which contains a robust additional term and which uses the prediction error and the tracking errors to drive parameter estimation, is based on passivity and on Lyapunov direct method. Itis shown that global stability and convergence can be achieved for the robust and adaptive control algorithm. Numerical simulations are provided to demonstrate the performance and the robustness of the proposed algorithm.

  3. Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles

    Science.gov (United States)

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-08-01

    A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

  4. Evaluating the need for integrated land use and land cover analysis for robust assessment of climate adaptation and mitigation strategies

    Science.gov (United States)

    Di Vittorio, Alan; Mao, Jiafu; Shi, Xiaoying

    2016-04-01

    LULCC scenarios in earth system simulations to provide robust historical and future projections of carbon and climate, especially when incorporating climate feedbacks on human and environmental systems. More accurate LULCC scenarios will also improve impact and resource sustainability analyses in the context of climate adaptation and mitigation strategies. These new scenarios will need to be developed and implemented as an integrated process with interdependent land use and land cover to adequately incorporate human and environmental drivers of LULCC.

  5. Adaptive path planning for unmanned aerial vehicles based on bi-level programming and variable planning time interval

    Institute of Scientific and Technical Information of China (English)

    Liu Wei; Zheng Zheng; Cai Kaiyuan

    2013-01-01

    This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs' relevant performances,with respect to sensory capability,maneuverability,and flight velocity limit.On the basis of a novel adaptability-involved problem statement,bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization.Additionally,both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability.A discrete-search-based path planning solution,embedded with four optimization strategies,is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces,within which different surface-to-air missiles (SAMs) are deployed.Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner,and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.

  6. Delay-Range-Dependent Global Robust Passivity Analysis of Discrete-Time Uncertain Recurrent Neural Networks with Interval Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Chien-Yu Lu

    2009-01-01

    Full Text Available This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRNNs with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities (LMIs. Two numerical examples are given to illustrate the effectiveness and applicability.

  7. On the Unconditional Robust Stability for the Interval Coefficient Hyperneutral Type Linear Continuous Control System%超中立型区间系数线性连续控制系统的无条件鲁棒镇定

    Institute of Scientific and Technical Information of China (English)

    孟培源; 黎野平

    2001-01-01

    本文利用镇定理论中的等价性和时域中的积分-微分不等式,讨论了超中立区间系数定常、时变线性连续控制系统,获得了若干简洁的无条件鲁棒镇定性结果.%In this paper,we are interested in the hypemeutral typerneutral type interval coefficient constant and time varying linear continuous control systems,by means of the equivalence method and the differential-integral inequality in the time domain.we obtain some unconditional robust stability results for the hypemeutral type constant and time-varying interval coefficient linear continuous control systems,respectively.

  8. Interval ridge regression (iRR) as a fast and robust method for quantitative prediction and variable selection applied to edible oil adulteration.

    Science.gov (United States)

    Jović, Ozren; Smrečki, Neven; Popović, Zora

    2016-04-01

    A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for poil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEPoil (R(2)>0.99).

  9. Short- and Long-Term Biomarkers for Bacterial Robustness: A Framework for Quantifying Correlations between Cellular Indicators and Adaptive Behavior

    NARCIS (Netherlands)

    Besten, den H.M.W.; Arvind, A.; Gaballo, H.M.S.; Moezelaar, R.; Zwietering, M.H.; Abee, T.

    2010-01-01

    The ability of microorganisms to adapt to changing environments challenges the prediction of their history-dependent behavior. Cellular biomarkers that are quantitatively correlated to stress adaptive behavior will facilitate our ability to predict the impact of these adaptive traits. Here, we prese

  10. The Effect of Irrigation Intervals and Intecropped Marjoram (Origanum vulgare with Saffron (Crocus sativus on Possible Cooling Effect of Corms for Climate Change Adaptation

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2013-12-01

    Full Text Available In order to study the effect of irrigation intervals and intecropped marjoram (Origanum vulgare (as a shading crop for reducing the possible effects of soil warming due to climate change on the growth and yield of saffron (Crocus sativus, a field experiment was conducted as split-plot based on randomized complete block design with three replications, during 2008 and 2009 at the Agricultural Research Station of Ferdowsi University of Mashhad, Iran. Three irrigation intervals (every 7, 14, and 21 days and three planting combinations (1:0 (pure stand of saffron, 1:1 (one row of saffron + one row of marjoram, 2:1 (two rows of saffron + one row of marjoram and 3:1 (three rows of saffron + one row of marjoram were allocated to main and sub plots, respectively. Results indicated that the simple effects of irrigation interval and planting combination on the flower number, flower weight and economical yield of saffron were significant (p≤0.01. Also, the interaction effects between irrigation interval and planting combination on the flower number, flower weight and economical yield of saffron were significant (p≤0.01. The highest and the lowest of saffron economical yield were observed in the irrigation intervals with every 14 (0.27 g.m-2 and 7 days (0.09 g.m-2, respectively. Also, the maximum and the minimum economical yield of saffron were observed in 1:1 (0.20 g.m-2 and pure stand of saffron (0.15 g.m-2, respectively. With increasing irrigation intervals, the growth characteristics and economical yield of saffron were enhanced. It seems that the intercropped saffron with marjoram increased the flower number and economical yield of saffron due to decreasing soil temperature which could be regarded as an alternative to the possible effect of soil warming for climate change adaptation.

  11. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    Science.gov (United States)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  12. Robust Approximation to Adaptive Control by Use of Representative Parameter Sets with Particular Reference to Type 1 Diabetes

    Directory of Open Access Journals (Sweden)

    Anthony Shannon

    2006-04-01

    Full Text Available This paper describes an approach to adaptive optimal control in the presence of model parameter calculation difficulties. This has wide application in a variety of biological and biomedical research and clinical problems. To illustrate the techniques, the approach is applied to the development and implementation of a practical adaptive insulin infusion algorithm for use with patients with Type 1 diabetes mellitus.

  13. Interval for the expression of the adaptive response induced by gamma radiation in leucocytes of mouse In vivo; Intervalo para la expresion de la respuesta adaptativa inducida por radiacion gamma en leucocitos de raton In vivo

    Energy Technology Data Exchange (ETDEWEB)

    Mendiola C, M.T.; Morales R, P. [Instituto Nacional de Investigaciones Nucleares, A.P. 18-1027, 11801 Mexico D.F. (Mexico)

    2002-07-01

    The interval between the adaptive gamma radiation dose (0.01 Gy) and challenge (1.0 Gy) capable to induce the maximum expression of the adaptive response in lymphocytes of mouse In vivo. The animals were exposed to the mentioned doses with different intervals among both (1, 1.5, 5 or 18 hr). By means of the unicellular electrophoresis in gel technique, four damage parameters were analysed. The results showed that from the 1 hr interval an adaptive response was produced since in the pretreated organisms with 0.01 Gy the cells present lesser damage than in those not adapted. The maximum response was induced with the intervals between 2.5 and 5 hr and even though it persisted until 18 hr, the effect was reducing. (Author)

  14. STABILITY FOR SEVERAL TYPES OF INTERVAL MATRICES

    Institute of Scientific and Technical Information of China (English)

    NianXiaohong; GaoJintai

    1999-01-01

    The robust stability for some types of tlme-varying interval raatrices and nonlineartime-varying interval matrices is considered and some sufficient conditions for robust stability of such interval matrices are given, The main results of this paper are only related to the verticesset of a interval matrices, and therefore, can be easily applied to test robust stability of interval matrices. Finally, some examples are given to illustrate the results.

  15. A Frequency-Domain Adaptive Filter (FDAF) Prediction Error Method (PEM) Framework for Double-Talk-Robust Acoustic Echo Cancellation

    DEFF Research Database (Denmark)

    Gil-Cacho, Jose M.; van Waterschoot, Toon; Moonen, Marc

    2014-01-01

    In this paper, we propose a new framework to tackle the double-talk (DT) problem in acoustic echo cancellation (AEC). It is based on a frequency-domain adaptive filter (FDAF) implementation of the so-called prediction error method adaptive filtering using row operations (PEM-AFROW) leading...... to the FDAF-PEM-AFROW algorithm. We show that FDAF-PEM-AFROW is by construction related to the best linear unbiased estimate (BLUE) of the echo path. We depart from this framework to show an improvement in performance with respect to other adaptive filters minimizing the BLUE criterion, namely the PEM...

  16. Robust Sensorless Control for Induction Motor Drives Fed by a Matrix Converter with Variable Structure Model Reference Adaptive

    DEFF Research Database (Denmark)

    Kim, Won-Sang; Lee, Kyo-Beum; Huh, Sunghoi;

    2007-01-01

    This paper presents a new robust sensorless control system for high performance induction motor drives fed by a matrix converter with variable structure. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a variable structure approach based...

  17. Robust Multiobjective Controllability of Complex Neuronal Networks.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Du, Wei; Lu, Jianquan; Vasilakos, Athanasios V; Kurths, Jurgen

    2016-01-01

    This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.

  18. (Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

    Science.gov (United States)

    He, Fei; Fromion, Vincent; Westerhoff, Hans V

    2013-11-21

    Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems

  19. Robust and Non-fragile H∞ Control for Nonlinear Descriptor Discrete Interval Systems%非线性广义离散区间系统的鲁棒非脆弱H∞控制

    Institute of Scientific and Technical Information of China (English)

    苏晓明; 刘芳玲

    2012-01-01

    研究一类含有非线性扰动的广义离散区间系统的鲁棒非脆弱H∞控制问题,所研究的非线性扰动满足Lipschitz条件.首先,利用Lyapunov函数理论,研究不确定非线性广义系统的鲁棒H∞控制问题;其次,以线性矩阵不等式(LMI)形式,给出了系统鲁棒非脆弱H∞控制器存在的充分条件,使得对于所有容许不确定性,闭环系统都允许且H∞性能指标满足给定上界.同时,给出状态反馈控制器的设计方法;最后,用数值例子表明了所提出方法的有效性.%The problem of robust and non-fragile H∞ control for a class of descriptor discrete interval systems with nonlinear disturbance was studied,where the nonlinear disturbance satisfies the Lipschitz condition.First of all,based on the theory of Lyapunov function,the robust H∞ control problem of the uncertain nonlinear descriptor system was described;Secondly,a sufficient condition for the existence of robust and non-fragile H∞ controller was given by linear matrix inequality approach,which guarantees that the resulting closedloop descriptor system is admissible and satisfies a prescribed H∞ normbounded constrain for all admissible uncertainties.Meanwhile,the design method of the state feedback controller was proposed.Finally,numerical simulation results indicated the effectiveness of the developed method.

  20. Research on a Nonlinear Robust Adaptive Control Method of the Elbow Joint of a Seven-Function Hydraulic Manipulator Based on Double-Screw-Pair Transmission

    Directory of Open Access Journals (Sweden)

    Gaosheng Luo

    2014-01-01

    Full Text Available A robust adaptive control method with full-state feedback is proposed based on the fact that the elbow joint of a seven-function hydraulic manipulator with double-screw-pair transmission features the following control characteristics: a strongly nonlinear hydraulic system, parameter uncertainties susceptible to temperature and pressure changes of the external environment, and unknown outer disturbances. Combined with the design method of the back-stepping controller, the asymptotic stability of the control system in the presence of disturbances from uncertain systematic parameters and unknown external disturbances was demonstrated using Lyapunov stability theory. Based on the elbow joint of the seven-function master-slave hydraulic manipulator for the 4500 m Deep-Sea Working System as the research subject, a comparative study was conducted using the control method presented in this paper for unknown external disturbances. Simulations and experiments of different unknown outer disturbances showed that (1 the proposed controller could robustly track the desired reference trajectory with satisfactory dynamic performance and steady accuracy and that (2 the modified parameter adaptive laws could also guarantee that the estimated parameters are bounded.

  1. 面向可适应性的稳健性产品平台规划方法%Adaptability-oriented Planning Method for Robust Product Platform

    Institute of Scientific and Technical Information of China (English)

    程贤福

    2015-01-01

    To quickly respond to customers’ individual needs and markets demand diversification, the concept of product platform architecture for adaptability is defined, and an adaptability-oriented planning method for robust product platform is presented. Due to the conceptual consistency on promoting the adaptability to environmental change, considering design changes and improving product quality with low costs, it is therefore natural to unify robust design and adaptable design. In initial phase of product platform plan, the robustness and design adaptability should be considered to avoid rework. The axiomatic design theory is utilized as framework to “zigzaging” mapping between functional requirements and design parameters. According to the analysis on functional requirements, the functional requirements are divided into basic functional requirements, expectable functional requirements and adjunctive functional requirements. The design characteristic parameters are extracted reasonably and the functional requirements matrix and design parameters matrix are established respectively. The grey system theory is made use into robust design of product platform, the platform parameters and variety parameters are identified through the experimental design and analysis of variance for the grey relational grade. Then a two –stage method for robust optimization problem of product family is proposed to determine the best design scenario for product platform and product variety. Finally, an example of flexible product configuration for drum is used to demonstrate the feasibility and practical value of the proposed method.%为更好地快速响应市场的多样化需求,引入面向可适应性的产品平台结构概念。根据稳健设计与可适应设计在提升产品适应外部环境变化的能力、考虑设计变更及以低成本获得高质量产品方面的一致性,提出了面向可适应性的稳健性产品平台规划方法,在产品平台规划初

  2. INTERVAL ROBUST CONTROL FOR NONLINEAR FLAT SYSTEMS

    OpenAIRE

    2013-01-01

    Esta tesis se enfoca principalmente en el control robusto de sistemas no lineales planos. El objetivo principal es determinar una familia de controladores robustos con la finalidad de asegurar el cumplimiento de un conjunto de especificaciones deseadas bajo incertidumbre paramétrica en el proceso. La familia de controladores robustos se determina con un nuevo enfoque de control robusto posibilistico conjuntamente con la teoría de los sistemas planos. Las especificaciones e incertidumbre param...

  3. High-intensity interval training-induced metabolic adaptation coupled with an increase in Hif-1α and glycolytic protein expression.

    Science.gov (United States)

    Abe, Takaaki; Kitaoka, Yu; Kikuchi, Dale Manjiro; Takeda, Kohei; Numata, Osamu; Takemasa, Tohru

    2015-12-01

    It is known that repeated bouts of high-intensity interval training (HIIT) lead to enhanced levels of glycolysis, glycogenesis, and lactate transport proteins in skeletal muscle; however, little is known about the molecular mechanisms underlying these adaptations. To decipher the mechanism leading to improvement of skeletal muscle glycolytic capacity associated with HIIT, we examined the role of hypoxia-inducible factor-1α (Hif-1α), the major transcription factor regulating the expression of genes related to anaerobic metabolism, in the adaptation to HIIT. First, we induced Hif-1α accumulation using ethyl 3,4-dihydroxybenzoate (EDHB) to assess the potential role of Hif-1α in skeletal muscle. Treatment with EDHB significantly increased the protein levels of Hif-1α in gastrocnemius muscles, accompanied by elevated expression of genes related to glycolysis, glycogenesis, and lactate transport. Daily administration of EDHB for 1 wk resulted in elevated glycolytic enzyme activity in gastrocnemius muscles. Second, we examined whether a single bout of HIIT could induce Hif-1α protein accumulation and subsequent increase in the expression of genes related to anaerobic metabolism in skeletal muscle. We observed that the protein levels of Hif-1α and expression of the target genes were elevated 3 h after an acute bout of HIIT in gastrocnemius muscles. Last, we examined the effects of long-term HIIT. We found that long-term HIIT increased the basal levels of Hif-1α as well as the glycolytic capacity in gastrocnemius muscles. Our results suggest that Hif-1α is a key regulator in the metabolic adaptation to high-intensity training.

  4. 一类含非线性扰动的区间变时滞系统鲁棒稳定性判据%Robust Stability Criteria for Systems with Interval Time-varying Delay and Nonlinear Perturbations

    Institute of Scientific and Technical Information of China (English)

    惠俊军; 张合新; 周鑫; 孟飞; 张金生

    2014-01-01

    Interval time delay is an important delay type in practical systems. In such sys-tems, the delay may vary in a range for which the lower bound is not restricted to being zero. In this paper, we consider the robust stability for a class of linear systems with interval time-varying delay and nonlinear perturbations. Based on the delay decomposition approach, both the lower and upper bounds of the interval time-varying delay are proposed. By applying a new Lyapunov-Krasovskii (L-K) functional, and free-weighing matrix approach, a less conservative delay-dependent stability criteria are obtained, which are established in the forms of linear matrix inequalities (LMIs). The main advantage of the method is that more information of the interval delay is employed, and hence yields less conservative. Finally, numerical examples indicate the effectiveness and superiority of the proposed method.%区间时滞是在实际应用当中一类重要的时滞类型。在这类系统当中,时滞往往处于一个变化的区间之内,而时滞的下界不一定为零。本文讨论一类含非线性扰动的区间变时滞系统的稳定性问题。基于时滞分解法,把时滞下界分成两个相等的子区间,通过构造包含时滞区间下界和上界新Lyapunov-Krasovskii (L-K)泛函,结合改进的自由权矩阵技术,建立了线性矩阵不等式(LMI)形式的时滞相关稳定性判据。该方法充分利用了系统的时滞信息,因而具有更低的保守性。数值算例说明了该方法的有效性和优越性。

  5. Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

    Science.gov (United States)

    Bagheri, Pedram; Sun, Qiao

    2016-07-01

    In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers.

  6. Robust Detection and Classification of Regional Seismic Signals Using a Two Mode/Two Stage Cascaded Adaptive Arma (CAARMA) Model

    Science.gov (United States)

    1985-03-01

    adaptive algorithms presented earlier, we will employ the SHARF algorithm. The analysis by * Ljuig [30-31] provides a convergence proof for the RLMS...algo- rithm. Since SHARF is not a gradient search algorithm, the convergence proof relies upon the concept of hyperstability [32-361. A direct form...realization of the transfer function -A A -N B bz + + bNZ A B(z) 0 1 N H(z) = = -_ -I a -N 3.45 a(z 1z a . N z is utilized by both the RLMS and SHARF

  7. Robust DTC Based on Adaptive Fuzzy Control of Double Star Synchronous Machine Drive with Fixed Switching Frequency

    Science.gov (United States)

    Boudana, Djamel; Nezli, Lazhari; Tlemçani, Abdelhalim; Mahmoudi, Mohand Oulhadj; Tadjine, Mohamed

    2012-05-01

    The double star synchronous machine (DSSM) is widely used for high power traction drives. It possesses several advantages over the conventional three phase machine. To reduce the torque ripple the DSSM are supplied with source voltage inverter (VSI). The model of the system DSSM-VSI is high order, multivariable and nonlinear. Further, big harmonic currents are generated. The aim of this paper is to develop a new direct torque adaptive fuzzy logic control in order to control DSSM and minimize the harmonics currents. Simulations results are given to show the effectiveness of our approach.

  8. Robust heart rate estimation using wrist-type photoplethysmographic signals during physical exercise: an approach based on adaptive filtering.

    Science.gov (United States)

    Fallet, Sibylle; Vesin, Jean-Marc

    2017-02-01

    Photoplethysmographic (PPG) signals are easily corrupted by motion artifacts when the subjects perform physical exercise. This paper introduces a two-step processing scheme to estimate heart rate (HR) from wrist-type PPG signals strongly corrupted by motion artifacts. Adaptive noise cancellation, using normalized least-mean-square algorithm, is first performed to attenuate motion artifacts and reconstruct multiple PPG waveforms from different combinations of corrupted PPG waveforms and accelerometer data. An adaptive band-pass filter is then used to track the common instantaneous frequency component (i.e. HR) of the reconstructed PPG waveforms. The proposed HR estimation scheme was evaluated on two datasets, composed of records from running subjects and subjects performing different kinds of arm/forearm movements and resulted in average absolute errors of 1.40  ±  0.60 and 4.28  ±  3.16 beats-per-minute for these two datasets, respectively. Importantly, the proposed method is fully automatic, induces an average estimation delay of 0.93 s, and is therefore suitable for real-time monitoring applications.

  9. Myocardial adaptation to high-intensity (interval) training in previously untrained men with a longitudinal cardiovascular magnetic resonance imaging study (Running Study and Heart Trial).

    Science.gov (United States)

    Scharf, Michael; Schmid, Axel; Kemmler, Wolfgang; von Stengel, Simon; May, Matthias S; Wuest, Wolfgang; Achenbach, Stephan; Uder, Michael; Lell, Michael M

    2015-04-01

    To prospectively evaluate whether short-term high-intensity (interval) training (HI(I)T) induces detectable morphological cardiac changes in previously untrained men in cardiovascular magnetic resonance imaging. Eighty-four untrained volunteers were randomly assigned to a HI(I)T group (n=42; 44.1±4.7 years) or an inactive control group (n=42; 42.3±5.6 years). HI(I)T focused on interval runs (intensity: 95%-105% of individually calculated heart rate at the anaerobic threshold). Before and after 16 weeks, all subjects underwent physiological examination, stepwise treadmill test with blood lactate analysis, and contrast-enhanced cardiovascular magnetic resonance imaging (cine, tagging, and delayed enhancement). Indexed left ventricular (LV) and right ventricular (RV) volume (LV, 77.1±8.5-83.9±8.6; RV, 80.5±8.5-86.6±8.1) and mass (LV, 58.2±6.4-63.4±8.1; RV, 14.8±1.7-16.1±2.1) significantly increased with HI(I)T. Changes in LV and RV morphological parameters with HI(I)T were highly correlated with an increase in maximal aerobic capacity (VO2max) and a decrease in blood lactate concentration at the anaerobic threshold. Mean LV and RV remodeling index of HI(I)T group did not alter with training (0.76 ±0.09 and 0.24±0.10 g/mL, respectively [P=0.97 and P=0.72]), indicating balanced cardiac adaptation. Myocardial circumferential strain decreased after HI(I)T within all 6 basal segments (anteroseptal, P=0.01 and anterolateral, PHeart Association, Inc.

  10. Right ventricular metabolic adaptations to high-intensity interval and moderate-intensity continuous training in healthy middle-aged men.

    Science.gov (United States)

    Heiskanen, Marja A; Leskinen, Tuija; Heinonen, Ilkka H A; Löyttyniemi, Eliisa; Eskelinen, Jari-Joonas; Virtanen, Kirsi; Hannukainen, Jarna C; Kalliokoski, Kari K

    2016-09-01

    Despite the recent studies on structural and functional adaptations of the right ventricle (RV) to exercise training, adaptations of its metabolism remain unknown. We investigated the effects of short-term, high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on RV glucose and fat metabolism. Twenty-eight untrained, healthy 40-55 yr-old-men were randomized into HIIT (n = 14) and MICT (n = 14) groups. Subjects performed six supervised cycle ergometer training sessions within 2 wk (HIIT session: 4-6 × 30 s all-out cycling/4-min recovery; MICT session: 40-60 min at 60% peak O2 uptake). Primary outcomes were insulin-stimulated RV glucose uptake (RVGU) and fasted state RV free fatty acid uptake (RVFFAU) measured by positron emission tomography. Secondary outcomes were changes in RV structure and function, determined by cardiac magnetic resonance. RVGU decreased after training (-22% HIIT, -12% MICT, P = 0.002 for training effect), but RVFFAU was not affected by the training (P = 0.74). RV end-diastolic and end-systolic volumes, respectively, increased +5 and +7% for HIIT and +4 and +8% for MICT (P = 0.002 and 0.005 for training effects, respectively), but ejection fraction mildly decreased (-2% HIIT, -4% MICT, P = 0.034 for training effect). RV mass and stroke volume remained unaltered. None of the observed changes differed between the training groups (P > 0.12 for group × training interaction). Only 2 wk of physical training in previously sedentary subjects induce changes in RV glucose metabolism, volumes, and ejection fraction, which precede exercise-induced hypertrophy of RV.

  11. Robust adaptive integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property

    Science.gov (United States)

    Zhang, Feng; Duan, Guang-Ren

    2014-05-01

    This paper tackles the problem of integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property. Due to the system natural couplings, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment and unknown mass property are taken into account. By solving an equivalent designated trajectory tracking problem via backstepping philosophy, a robust adaptive integrated finite-time control scheme is proposed to enable the spacecraft track command position and attitude in a pre-determined time, despite of external disturbance, unknown mass property and thruster misalignment. The finite-time closed-loop stability is guaranteed within the Lyapunov framework. Two scenario numerical simulations demonstrate the effect of the designed controller.

  12. Robust Control of a Class of Uncertain Fractional-Order Chaotic Systems with Input Nonlinearity via an Adaptive Sliding Mode Technique

    Directory of Open Access Journals (Sweden)

    Xiaomin Tian

    2014-02-01

    Full Text Available In this paper, the problem of stabilizing a class of fractional-order chaotic systems with sector and dead-zone nonlinear inputs is investigated. The effects of model uncertainties and external disturbances are fully taken into account. Moreover, the bounds of both model uncertainties and external disturbances are assumed to be unknown in advance. To deal with the system’s nonlinear items and unknown bounded uncertainties, an adaptive fractional-order sliding mode (AFSM controller is designed. Then, Lyapunov’s stability theory is used to prove the stability of the designed control scheme. Finally, two simulation examples are given to verify the effectiveness and robustness of the proposed control approach.

  13. A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

    Science.gov (United States)

    Ushaq, Muhammad; Fang, Jiancheng

    2013-10-01

    Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be

  14. Resveratrol supplementation does not augment performance adaptations or fibre-type-specific responses to high-intensity interval training in humans.

    Science.gov (United States)

    Scribbans, Trisha D; Ma, Jasmin K; Edgett, Brittany A; Vorobej, Kira A; Mitchell, Andrew S; Zelt, Jason G E; Simpson, Craig A; Quadrilatero, Joe; Gurd, Brendon J

    2014-11-01

    The present study examined the effect of concurrent exercise training and daily resveratrol (RSV) supplementation (150 mg) on training-induced adaptations following low-dose high-intensity interval training (HIIT). Sixteen recreationally active (∼22 years, ∼51 mL·kg(-1)·min(-1)) men were randomly assigned in a double-blind fashion to either the RSV or placebo group with both groups performing 4 weeks of HIIT 3 days per week. Before and after training, participants had a resting muscle biopsy taken, completed a peak oxygen uptake test, a Wingate test, and a submaximal exercise test. A main effect of training (p training (p training: 54.5 ± 1.5 mL·kg(-1)·min(-1), effect size (ES) = 0.93; RSV - pretraining: 49.6 ± 2.2, post-training: 52.3 ± 2.5 mL·kg(-1)·min(-1), ES = 0.50) and Wingate peak power (placebo: pretraining: 747 ± 39, post-training: 809 ± 31 W, ES = 0.84; RSV - pretraining: 679 ± 39, post-training: 691 ± 43 W, ES = 0.12). Fibre-type distribution was unchanged, while a main effect of training (p training was significantly (p training and RSV supplementation may alter the normal training response induced by low-volume HIIT.

  15. Robust Scientists

    DEFF Research Database (Denmark)

    Gorm Hansen, Birgitte

    The concepts of “socially robust knowledge” and “mode 2 knowledge production” (Nowotny 2003, Gibbons et al. 1994) have migrated from STS into research policy practices. Both STS-scholars and policy makers have been known to propomote the idea that the way forward for today’s scientist is to jump...... from the ivory tower and learn how to create high-flying synergies with citizens, corporations and governments. In STS as well as in Danish research policy it has thus been argued that scientists will gain more support and enjoy greater success in their work by “externalizing” their research...... and adapting their interests to the needs of outside actors. However, when studying the concrete strategies of such successful scientists, matters seem a bit more complicated. Based on interviews with a plant biologist working in GMO the paper uses the biological concepts of field participants...

  16. Switching Logic-based Adaptive Robust Control of Nonlinearly Parameterized Uncertain Systems%基于切换逻辑的非线性系统自适应鲁棒控制器设计

    Institute of Scientific and Technical Information of China (English)

    马博军; 方勇纯; 肖潇

    2007-01-01

    In this paper, a switching logic-based adaptive robust control is proposed for a class of nonlinearly parameterized systems (NPS). Specifically, the controller mainly consists of a robust type term to address the system uncertainty, and a switching logic tuning mechanism to update the involved control gain. The constructed controller achieves a global uniformly ultimate boundedness (GUUB) result for the system errors, and simulation results are included to demonstrate the effectiveness of the control law.

  17. Robustness Beamforming Algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Dehghani

    2014-04-01

    Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

  18. Robustness Beamforming Algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Dehghani

    2014-09-01

    Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

  19. Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

    Science.gov (United States)

    Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

    2011-04-01

    This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

  20. Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

    Science.gov (United States)

    Bagherpoor, H M; Salmasi, Farzad R

    2015-07-01

    In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance.

  1. Robust Adaptive PID Controller for a Class of Uncertain Nonlinear Systems: An Application for Speed Tracking Control of an SI Engine

    Directory of Open Access Journals (Sweden)

    Tossaporn Chamsai

    2015-01-01

    Full Text Available The sliding mode control (SMC technique with a first-order low-pass filter (LPF is incorporated with a new adaptive PID controller. It is proposed for tracking control of an uncertain nonlinear system. In the proposed control scheme, the adaptation law is able to update the PID controller online during the control process within a short period. The chattering phenomenon of the SMC can be alleviated by incorporation of a first-order LPF, while the robustness of the control system is similar to that of the sliding mode. In the closed-loop control analysis, the convergence condition in the reaching phase and the existence condition of the sliding mode were analyzed. The stability of the closed-loop control is guaranteed in the sense of Lyapunov’s direct method. The simulations and experimental applications of a speed tracking control of a spark ignition (SI engine via electronic throttle valve control architecture are provided to verify the effectiveness and the feasibility of the proposed control scheme.

  2. On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

    Directory of Open Access Journals (Sweden)

    Mark Frogley

    2013-01-01

    Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

  3. On the Robustness and Prospects of Adaptive BDDC Methods for Finite Element Discretizations of Elliptic PDEs with High-Contrast Coefficients

    KAUST Repository

    Zampini, Stefano

    2016-06-02

    Balancing Domain Decomposition by Constraints (BDDC) methods have proven to be powerful preconditioners for large and sparse linear systems arising from the finite element discretization of elliptic PDEs. Condition number bounds can be theoretically established that are independent of the number of subdomains of the decomposition. The core of the methods resides in the design of a larger and partially discontinuous finite element space that allows for fast application of the preconditioner, where Cholesky factorizations of the subdomain finite element problems are additively combined with a coarse, global solver. Multilevel and highly-scalable algorithms can be obtained by replacing the coarse Cholesky solver with a coarse BDDC preconditioner. BDDC methods have the remarkable ability to control the condition number, since the coarse space of the preconditioner can be adaptively enriched at the cost of solving local eigenproblems. The proper identification of these eigenproblems extends the robustness of the methods to any heterogeneity in the distribution of the coefficients of the PDEs, not only when the coefficients jumps align with the subdomain boundaries or when the high contrast regions are confined to lie in the interior of the subdomains. The specific adaptive technique considered in this paper does not depend upon any interaction of discretization and partition; it relies purely on algebraic operations. Coarse space adaptation in BDDC methods has attractive algorithmic properties, since the technique enhances the concurrency and the arithmetic intensity of the preconditioning step of the sparse implicit solver with the aim of controlling the number of iterations of the Krylov method in a black-box fashion, thus reducing the number of global synchronization steps and matrix vector multiplications needed by the iterative solver; data movement and memory bound kernels in the solve phase can be thus limited at the expense of extra local ops during the setup of

  4. Robust object tracking with adaptive feature selection%基于特征自适应选择的鲁棒跟踪算法

    Institute of Scientific and Technical Information of China (English)

    吴成东; 齐苑辰; 陈东岳

    2014-01-01

    In order to solve the tracking problem of video sequences in real-world scenarios, a robust tracking algorithm based on adaptive feature selection is proposed. Firstly, for the problem that the candidate features of the online AdaBoost algorithm are not robust, a construction mode of the candidate feature pool is proposed, which combines color and pyramid gradient orientation histogram features. Then, for the problem that classifiers are vulnerable to the influence of improper samples during the update, a process of occlusion detection is added at each frame after obtaining the tracking result to avoid the phenomena of drift. Lots of comparison experiments show that the proposed algorithm tracks the object accurately and reliably in realistic videos.%为了解决真实场景下视频目标的跟踪问题,提出一种基于特征自适应选择的鲁棒跟踪算法。首先,针对在线AdaBoost算法特征池特征鲁棒性差的问题,提出一种基于颜色与金字塔梯度方向直方图特征相结合的特征池构造方式;然后,针对分类器在更新过程中容易受到错误样本影响的问题,对每帧跟踪结果增加遮挡检测环节以避免漂移现象的发生。大量的对比实验表明,在真实场景下所提出的方法具有更好的效果。

  5. An Improved Robust Adaptive Control Design for a Class of Neutral Delay Systems%一类中立时滞系统的一种改进的鲁棒自适应控制设计

    Institute of Scientific and Technical Information of China (English)

    孙希明; 孙文安; 赵军

    2006-01-01

    The problem of adaptive robust control is addressed for a class of neutral delay systems.All uncertainties are assumed to be bounded by unknown constants. An improved adaptation law is proposed to estimate the square of these unknown bounds. Then, by making use of the updated values of the squared unknown bounds, an adaptive controller is designed to make the solution of the resultant closed-loop system uniformly ultimately bounded. Furthermore, this method avoids chattering and improves the performance. An example is given to illustrate the effectiveness of this method.

  6. An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

    Science.gov (United States)

    Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

    2017-09-01

    In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

  7. Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

    Science.gov (United States)

    Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

    2016-11-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

  8. Robust model reference adaptive control for a two-dimensional piezo-driven micro-displacement scanning platform based on the asymmetrical Bouc-Wen model

    Directory of Open Access Journals (Sweden)

    Haigen Yang

    2016-11-01

    Full Text Available The hysteresis characteristics resulted from piezoelectric actuators (PAs and the residual vibration in the rapid positioning of a two-dimensional piezo-driven micro-displacement scanning platform (2D-PDMDSP will greatly affect the positioning accuracy and speed. In this paper, in order to improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP, firstly, Utilizing an online hysteresis observer based on the asymmetrical Bouc-Wen model, the PA with the hysteresis characteristics is feedforward linearized and can be used as a linear actuator; secondly, zero vibration and derivative shaping (ZVDS technique is used to eliminate the residual vibration of the 2D-PDMDSP; lastly, the robust model reference adaptive (RMRA control for the 2D-PDMDSP is proposed and explored. The rapid control prototype of the RMRA controller combining the proposed feedforward linearization and ZVDS control for the 2D-PDMDSP with rapid control prototyping technique based on the real-time simulation system is established and experimentally tested, and the corresponding controlled results are compared with those by the PID control method. The experimental results show that the proposed RMRA control method can significantly improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP.

  9. Aplicación de algoritmos de control clásico, adaptable y robusto a sistemas dinámicos de parámetros variables;Classic, adaptable and robust control algorithm application, to variant parameter dynamic system.

    Directory of Open Access Journals (Sweden)

    Orlando – Regalón Anias

    2012-11-01

    Full Text Available Existen múltiples sistemas dinámicos cuyos modelos matemáticos se caracterizan por ser de primer orden yparámetros variables con el tiempo. En estos casos las herramientas clásicas no siempre logran un sistema decontrol que sea estable, posea un buen desempeño dinámico y rechace adecuadamente las perturbaciones, cuandoel modelo de la planta se desvía del nominal, para el cual se realizó el diseño.En este trabajo se evalúa elcomportamiento de tres estrategias de control en presencia de variación de parámetros. Estas son: control clásico,control adaptable y control robusto. Se realiza un estudio comparativo de las mismas en cuanto a complejidad deldiseño, costo computacional de la implementación y sensibilidad ante variaciones en los parámetros y/o presencia dedisturbios. Se llega a conclusiones que permiten disponer de criterios para la elección más adecuada, endependencia de los requerimientos dinámicos que la aplicación demande, así como de los medios técnicos de que sedisponga.Many dynamic systems have first order mathematic models, with time variable parameters. In these cases, theclassical tools do not satisfy at all control system stability, good performance and perturbation rejection, when theplant model differs from the nominal one, for which the controller was designed.In this article, three control strategiesare evaluated in parameter variations and disturbance presence. The strategies are the followings: classical control,adaptive control and robust control. A comparative study is carried out, taking into account the design complexity, thecomputational cost and the sensitivity. The obtained conclusions helps to provide the criterion to choose the mostadequate control strategy, according to the necessary dynamic, as well as the available technical means.

  10. Short and Long Term Effects of High-Intensity Interval Training on Hormones, Metabolites, Antioxidant System, Glycogen Concentration, and Aerobic Performance Adaptations in Rats.

    Science.gov (United States)

    de Araujo, Gustavo G; Papoti, Marcelo; Dos Reis, Ivan Gustavo Masselli; de Mello, Maria A R; Gobatto, Claudio A

    2016-01-01

    The purpose of the study was to investigate the effects of short and long term High-Intensity Interval Training (HIIT) on anaerobic and aerobic performance, creatinine, uric acid, urea, creatine kinase, lactate dehydrogenase, catalase, superoxide dismutase, testosterone, corticosterone, and glycogen concentration (liver, soleus, and gastrocnemius). The Wistar rats were separated in two groups: HIIT and sedentary/control (CT). The lactate minimum (LM) was used to evaluate the aerobic and anaerobic performance (AP) (baseline, 6, and 12 weeks). The lactate peak determination consisted of two swim bouts at 13% of body weight (bw): (1) 30 s of effort; (2) 30 s of passive recovery; (3) exercise until exhaustion (AP). Tethered loads equivalent to 3.5, 4.0, 4.5, 5.0, 5.5, and 6.5% bw were performed in incremental phase. The aerobic capacity in HIIT group increased after 12 weeks (5.2 ± 0.2% bw) in relation to baseline (4.4 ± 0.2% bw), but not after 6 weeks (4.5 ± 0.3% bw). The exhaustion time in HIIT group showed higher values than CT after 6 (HIIT = 58 ± 5 s; CT = 40 ± 7 s) and 12 weeks (HIIT = 62 ± 7 s; CT = 49 ± 3 s). Glycogen (mg/100 mg) increased in gastrocnemius for HIIT group after 6 weeks (0.757 ± 0.076) and 12 weeks (1.014 ± 0.157) in comparison to baseline (0.358 ± 0.024). In soleus, the HIIT increased glycogen after 6 weeks (0.738 ± 0.057) and 12 weeks (0.709 ± 0.085) in comparison to baseline (0.417 ± 0.035). The glycogen in liver increased after HIIT 12 weeks (4.079 ± 0.319) in relation to baseline (2.400 ± 0.416). The corticosterone (ng/mL) in HIIT increased after 6 weeks (529.0 ± 30.5) and reduced after 12 weeks (153.6 ± 14.5) in comparison to baseline (370.0 ± 18.3). In conclusion, long term HIIT enhanced the aerobic capacity, but short term was not enough to cause aerobic adaptations. The anaerobic performance increased in HIIT short and long term compared with CT, without differences between HIIT short and long term. Furthermore, the

  11. SHORT AND LONG TERM EFFECTS OF HIGH-INTENSITY INTERVAL TRAINING ON HORMONES, METABOLITES, ANTIOXIDANT SYSTEM, GLYCOGEN CONCENTRATION AND AEROBIC PERFORMANCE ADAPTATIONS IN RATS

    Directory of Open Access Journals (Sweden)

    Gustavo Gomes De Araujo

    2016-10-01

    Full Text Available The purpose of the study was to investigate the effects of short and long term High-Intensity Interval Training (HIIT on anaerobic and aerobic performance, creatinine, uric acid, urea, creatine kinase, lactate dehydrogenase, catalase, superoxide dismutase, testosterone, corticosterone and glycogen concentration (liver, soleus and gastrocnemius. The Wistar were separated in two groups: HIIT and sedentary/control (CT. The lactate minimum (LM was used to evaluate the aerobic and anaerobic performance (AP (baseline, 6 and 12 wk. The lactate peak determination consisted of two swim bouts at 13% of body weight (bw: 1 30 s of effort; 2 30 s of passive recovery; 3 exercise until exhaustion (AP. Tethered loads equivalent to 3.5, 4.0, 4.5, 5.0, 5.5 and 6.5% bw were performed in incremental phase. The aerobic capacity in HIIT group increased after 12 wk (5.2±0.2 % bw in relation to baseline (4.4±0.2 % bw, but not after 6 wk (4.5±0.3 % bw. The exhaustion time in HIIT group showed higher values than CT after 6 (HIIT= 58±5 s; CT=40±7 s and 12 wk (HIIT=62±7 s; CT=49±3 s. Glycogen (mg/100mg increased in gastrocnemius for HIIT group after 6 wk (0.757±0.076 and 12 wk (1.014±0.157 in comparison to baseline (0.358±0.024. In soleus, the HIIT increased glycogen after 6 wk (0.738±0.057 and 12 wk (0.709±0.085 in comparison to baseline (0.417±0.035. The glycogen in liver increased after HIIT 12 wk (4.079±0.319 in relation to baseline (2.400±0.416. The corticosterone (ng/mL in HIIT increased after 6 wk (529.0±30.5 and reduced after 12 wk (153.6±14.5 in comparison to baseline (370.0±18.3. In conclusion, long term HIIT enhanced the aerobic capacity, but short term (6wk was not enough to cause aerobic adaptations. The anaerobic performance increased in HIIT short and long term compared with CT, without differences between HIIT short and long term. Furthermore, the glycogen super-compensantion increased after short and long term HIIT in comparison to

  12. Robust Adaptive Control of Nonholonomic Systems with Nonlinear Parameterization%含有非线性参数化的非完整系统的鲁棒自适应控制

    Institute of Scientific and Technical Information of China (English)

    王强德; 魏春玲

    2007-01-01

    A global-adaptive state feedback control strategy is presented for a class of nonholonomic systems in chained form with strong nonlinear drifts and unknown nonlinear parameters. A parameter separation technique is introduced to transform the nonlinear parameterization nonholonomic system into a linear-like parameterized nonholonomic system. Then, the feedback domination design is applied to design a global adaptive stabilization controller and a switching strategy is developed to eliminate the phenomenon of uncontrollability. The proposed controller can guarantee that all the system states globally converge to the origin, while other signals remain bounded. Simulation example demonstrates the effectiveness and the robust features of the proposed controller.

  13. interval functions

    Directory of Open Access Journals (Sweden)

    J. A. Chatfield

    1978-01-01

    Full Text Available Suppose N is a Banach space of norm |•| and R is the set of real numbers. All integrals used are of the subdivision-refinement type. The main theorem [Theorem 3] gives a representation of TH where H is a function from R×R to N such that H(p+,p+, H(p,p+, H(p−,p−, and H(p−,p each exist for each p and T is a bounded linear operator on the space of all such functions H. In particular we show that TH=(I∫abfHdα+∑i=1∞[H(xi−1,xi−1+−H(xi−1+,xi−1+]β(xi−1+∑i=1∞[H(xi−,xi−H(xi−,xi−]Θ(xi−1,xiwhere each of α, β, and Θ depend only on T, α is of bounded variation, β and Θ are 0 except at a countable number of points, fH is a function from R to N depending on H and {xi}i=1∞ denotes the points P in [a,b]. for which [H(p,p+−H(p+,p+]≠0 or [H(p−,p−H(p−,p−]≠0. We also define an interior interval function integral and give a relationship between it and the standard interval function integral.

  14. 航天器非线性鲁棒自适应姿态机动控制律%Nonlinear robust adaptive attitude maneuver control law for spacecraft

    Institute of Scientific and Technical Information of China (English)

    王卫杰; 任元; 李怡勇; 罗元

    2015-01-01

    In the presence of uncertainties in the moment of inertia and the external disturbance torque,the nonlinear robust adaptive control law for the control torque and estimation of moment of inertia is designed com-bining the nonlinear backstepping and Lyapunovo stability.In the control law for the control torque,the nonlin-ear damping is added to compensate the external disturbance torque,and the globally uniformly ultimately bounded stability of the system is demonstrated.The nonlinear dynamic coefficient is introduced to increase the dynamic performance of the system,shortening the regulating time after fast attitude maneuver.By Matlab/Simulink programming,the simulation of spacecraft attitude manoeuver control is discussed,and the simulation results demonstrate the effectiveness and feasibility of the proposed controller.%针对存在未知转动惯量和外部干扰力矩的敏捷航天器快速大角度姿态机动问题,结合非线性反步法和 Lyapunovo 稳定性分析方法设计控制力矩和转动惯量估计值的非线性鲁棒自适应控制律。在控制力矩控制律中,加入非线性阻尼项对外部干扰力矩进行补偿,证明了系统的全局一致最终有界稳定性。引入非线性动系数增加系统的动态性能,提高了姿态快速机动后的快速稳定能力。在 Maltlab/Simulink 环境下进行航天器姿态机动控制仿真研究,仿真结果验证了所设计控制器的有效性和可行性。

  15. Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

    Science.gov (United States)

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2015-09-01

    To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

  16. 基于Lagrangian支持向量机的机械手鲁棒自适应控制%Robust adaptive control of robot manipulators using Lagrangian support vector machines

    Institute of Scientific and Technical Information of China (English)

    刘红平

    2015-01-01

    提出了一种基于Lagrangian支持向量机的不确定机械手鲁棒自适应控制方法。Lagrangian支持向量机采用梯度投影法学习机械手系统的未知部分,来对机械手系统进行非线性补偿。根据Lyapunov稳定性理论设计自适应律进一步在线调整支持向量机的参数,并叠加一个滑模控制项,以保证控制系统的稳定性和鲁棒性。对两关节机械手的仿真结果证明了以上控制方法的有效性。%A Lagrangian Support Vector Machine(LSVM)based robust adaptive controller is proposed for the trajectory tracking of robot manipulators. With gradient projection learning method, LSVM is used to compensate for the unknown part of the robot manipulator system. An adaptive law based on the Lyapunov stability theory is designed to further adjust the weights online. Moreover, a robust term is added to guarantee the stability and robustness of the controlled system. The effectiveness of the proposed approach is illustrated by the simulation results on a two-link manipulator.

  17. Robust Adaptive Controller for Robot Manipulator Based on Desired Trajectory Compensation%基于期望轨迹补偿的机器人鲁棒自适应控制

    Institute of Scientific and Technical Information of China (English)

    王延玉; 刘国栋

    2011-01-01

    针对机器人存在的参数不确定性和外扰的问题,提出了一种基于期望轨迹补偿和自适应控制的方法,在传统自适应控制方法的基础上,结合变结构控制方法,设计了一种新的控制策略.该方法采用期望轨迹补偿,离线计算回归矩阵,可以有效节约控制系统在线计算的时间,实时性好,并利用变结构思想补偿非线性摩擦和外界干扰,利用lyapunov直接法分析证明系统可实现全局渐进稳定,而且由于自适应率中不含有不确定项,可以有效解决参数辨识过程中的参数漂移问题,仿真结果也表明,系统估计参数收敛于真实值,并对于系统不确定性和外扰具有较好的鲁棒性.%A robust adaptive controller with guaranteed transient performance under a desired compensation adaptation law is developed for trajectory tracking control of robot manipulator in the presence of parametric uncertainties and external disturbances. With some modifications to the conventional adaptation law, a new control law is redesigned by combining the design methodologies of adaptive control and sliding mode control. The adaptive scheme has best computationally efficient for real-time calculating of the regressor, and compensate nonlinear friction and external disturbances via thought of variable structure. The global asymptotic stability is validated by Lyapunov direct method. Because the adaptation law is robust to uncertainty, the parameter is not contaminated with noise, simulation results show the estimated parameters are converged and the good robust and accuracy are obtained.

  18. Robust Manufacturing Control

    CERN Document Server

    2013-01-01

    This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...

  19. Robust adaptive model predictive filtering algorithm and application to integrated navigation%抗差自适应模型预测滤波及其在组合导航中的应用

    Institute of Scientific and Technical Information of China (English)

    高社生; 宋飞彪; 姜微微

    2011-01-01

    为了提高捷联惯导(sINs)/天文导航(CNS)/合成孔径雷达(SAR)组合导航系统的定位精度,在吸收模型预测滤波和抗差自适应滤波算法优点的基础上,提出了一种新的抗差自适应模型预测滤波算法.该算法首先利用模型预测滤波估计出系统模型误差,并对其进行实时修正,以抑制系统模型误差对导航解算精度的影响;然后利用抗差自适应因子控制观测异常,抑制观测噪声对导航解算精度的影响.将提出的算法应用于SINS/CNS/SAR组合导航系统进行仿真验证,并与抗差自适应滤波进行比较,结果表明,提出的算法得到的姿态误差、速度误差和位置误差分别在[-0.2,+0.2’]、[-0.3 m/s,+0.3 m/s]和[-6 m,+6 m]以内,滤波性能明显优于抗差自适应滤波算法,说明该算法能有效抑制系统模型误差及观测异常对导航解的影响,提高组合导航的解算精度.%In order to improve the navigation positioning accuracy of the strapdown inertial navigation system(SINS)/celestial navigation system(CNS)/synthetic aperture radar(SAR) integrated navigation systems, this paper presents a robust adaptive model predictive filtering algorithm based on the research of model predictive filtering and robust adaptive filtering. First, the algorithm estimates the model error in real-time to correct the system model by model predictive filtering to resist the effects of model errors on solution accuracy of navigation. Then, the algorithm controls the influences of abnormal observation on solution accuracy of navigation by the robust adaptive factor. The proposed algorithm is applied to SINS/CNS/SAR integrated navigation system and compared with the robust adaptive filter. Simulation results demonstrate that the attitude angle error, velocity error and position error obtained by the robust adaptive model predictive filtering are within [-0.2', +0.2'] , [-0.3 m, +0.3m] and [-6m,+6m] respectively; and the filtering performance

  20. Robust Self Tuning Controllers

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad

    1985-01-01

    The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay....

  1. Left ventricular vascular and metabolic adaptations to high-intensity interval and moderate intensity continuous training: a randomized trial in healthy middle-aged men.

    Science.gov (United States)

    Eskelinen, Jari-Joonas; Heinonen, Ilkka; Löyttyniemi, Eliisa; Hakala, Juuso; Heiskanen, Marja A; Motiani, Kumail K; Virtanen, Kirsi; Pärkkä, Jussi P; Knuuti, Juhani; Hannukainen, Jarna C; Kalliokoski, Kari K

    2016-12-01

    High-intensity interval training (HIIT) has become popular, time-sparing alternative to moderate intensity continuous training (MICT), although the cardiac vascular and metabolic effects of HIIT are incompletely known. We compared the effects of 2-week interventions with HIIT and MICT on myocardial perfusion and free fatty acid and glucose uptake. Insulin-stimulated myocardial glucose uptake was decreased by training without any significantly different response between the groups, whereas free fatty acid uptake remained unchanged. Adenosine-stimulated myocardial perfusion responded differently to the training modes (change in mean HIIT: -19%; MICT: +9%; P = 0.03 for interaction) and was correlated with myocardial glucose uptake for the entire dataset and especially after HIIT training. HIIT and MICT induce similar metabolic and functional changes in the heart, although myocardial vascular hyperaemic reactivity is impaired after HIIT, and this should be considered when prescribing very intense HIIT for previously untrained subjects. High-intensity interval training (HIIT) is a time-efficient way of obtaining the health benefits of exercise, although the cardiac effects of this training mode are incompletely known. We compared the effects of short-term HIIT and moderate intensity continuous training (MICT) interventions on myocardial perfusion and metabolism and cardiac function in healthy, sedentary, middle-aged men. Twenty-eight healthy, middle-aged men were randomized to either HIIT or MICT groups (n = 14 in both) and underwent six cycle ergometer training sessions within 2 weeks (HIIT session: 4-6 × 30 s all-out cycling/4 min recovery, MICT session 40-60 min at 60% V̇O2 peak ). Cardiac magnetic resonance imaging (CMRI) was performed to measure cardiac structure and function and positron emission tomography was used to measure myocardial perfusion at baseline and during adenosine stimulation, insulin-stimulated glucose uptake (MGU) and fasting free

  2. Robust Chaos

    CERN Document Server

    Banerjee, S; Grebogi, C; Banerjee, Soumitro; Yorke, James A.; Grebogi, Celso

    1998-01-01

    It has been proposed to make practical use of chaos in communication, in enhancing mixing in chemical processes and in spreading the spectrum of switch-mode power suppies to avoid electromagnetic interference. It is however known that for most smooth chaotic systems, there is a dense set of periodic windows for any range of parameter values. Therefore in practical systems working in chaotic mode, slight inadvertent fluctuation of a parameter may take the system out of chaos. We say a chaotic attractor is robust if, for its parameter values there exists a neighborhood in the parameter space with no periodic attractor and the chaotic attractor is unique in that neighborhood. In this paper we show that robust chaos can occur in piecewise smooth systems and obtain the conditions of its occurrence. We illustrate this phenomenon with a practical example from electrical engineering.

  3. Robust Econometrics

    OpenAIRE

    Čίžek, Pavel; Härdle, Wolfgang Karl

    2006-01-01

    Econometrics often deals with data under, from the statistical point of view, non-standard conditions such as heteroscedasticity or measurement errors and the estimation methods need thus be either adopted to such conditions or be at least insensitive to them. The methods insensitive to violation of certain assumptions, for example insensitive to the presence of heteroscedasticity, are in a broad sense referred to as robust (e.g., to heteroscedasticity). On the other hand, there is also a mor...

  4. Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

    Science.gov (United States)

    Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

    2014-09-01

    This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.

  5. Robust factorization

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Fisker, Rune; Åström, Kalle;

    2002-01-01

    Factorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal...... effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary error function in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features....... These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms...

  6. Assessing the robustness of adaptation decisions in river flood defences to uncertainty in climate impact analysis: A case study on the River Suir, Ireland

    Science.gov (United States)

    Murphy, N.; Murphy, C.

    2009-12-01

    Climate change presents a challenging environment for policy makers and planners as future climate projections are fraught with uncertainty. From the formulation of emissions scenarios, through to the output from Global Climate Models to the regional and then the local scale, uncertainty propagates and increases leading to a cascade of uncertainty (Jones, 2001). The level of flood defences for rivers in Ireland has been built to withstand the 1 in 100 year event based on the historic record. However, stream flow due to climate change is likely to increase by 20% in winter by mid century. The Office of Public Works has therefore revised their projections by adding 20% to the 1 in 100 year event as a design feature of their new flood defences. This poster presents a sensitivity analysis of how various aspects of the climate impact assessment affect the revised level of the 1 in 100 year flood. The River Suir is used as a case study. This poster aims to quantify how different aspects of climate impact assessment uncertainty (GCM, Emissions scenario, impact model) affect the revised level of the 1 in 100 year flood and evaluates if the design of flood defences remains robust to the this uncertainty. Authors. Nuala Murphy Conor Murphy

  7. Real-time detection of small and dim moving objects in IR video sequences using a robust background estimator and a noise-adaptive double thresholding

    Science.gov (United States)

    Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

    2016-10-01

    We developed an algorithm for automatically detecting small and poorly contrasted (dim) moving objects in real-time, within video sequences acquired through a steady infrared camera. The algorithm is suitable for different situations since it is independent of the background characteristics and of changes in illumination. Unlike other solutions, small objects of any size (up to single-pixel), either hotter or colder than the background, can be successfully detected. The algorithm is based on accurately estimating the background at the pixel level and then rejecting it. A novel approach permits background estimation to be robust to changes in the scene illumination and to noise, and not to be biased by the transit of moving objects. Care was taken in avoiding computationally costly procedures, in order to ensure the real-time performance even using low-cost hardware. The algorithm was tested on a dataset of 12 video sequences acquired in different conditions, providing promising results in terms of detection rate and false alarm rate, independently of background and objects characteristics. In addition, the detection map was produced frame by frame in real-time, using cheap commercial hardware. The algorithm is particularly suitable for applications in the fields of video-surveillance and computer vision. Its reliability and speed permit it to be used also in critical situations, like in search and rescue, defence and disaster monitoring.

  8. On robust forecasting of autoregressive time series under censoring

    OpenAIRE

    Kharin, Y.; Badziahin, I.

    2009-01-01

    Problems of robust statistical forecasting are considered for autoregressive time series observed under distortions generated by interval censoring. Three types of robust forecasting statistics are developed; meansquare risk is evaluated for the developed forecasting statistics. Numerical results are given.

  9. On robust forecasting of autoregressive time series under censoring

    OpenAIRE

    Kharin, Y.; Badziahin, I.

    2009-01-01

    Problems of robust statistical forecasting are considered for autoregressive time series observed under distortions generated by interval censoring. Three types of robust forecasting statistics are developed; meansquare risk is evaluated for the developed forecasting statistics. Numerical results are given.

  10. Analysis of Network Information Robustness Considered Adaptive Change Weights%考虑变权重自适应调整的网络信息鲁棒性分析

    Institute of Scientific and Technical Information of China (English)

    刘晋州

    2014-01-01

    BP神经网络加权权重成固化状态,导致信息信任度评价误差较大。提出基于BP神经网络的变权重自适应网络拓扑结构的C2C网络信息信任度评价和鲁棒性分析模型,以营运商可信度、网站信任度和外部环境为一级指标体系构建网络信息评价体系。以12维可信性因素作为输入向量,系统结构以网络信息信任度作为输出,通过调整网络拓扑权重向量设置信任度周期响应加权变量自适应函数,有效降低迭代算法的运算成本。仿真实验表明,采用新的网络信息鲁棒性评价模型能使C2C网站信息评价误差率大幅减低,系统具有较好的健壮稳定性和鲁棒性,能有效促进C2C网络健全运行和发展。%BP neural network weights were weighted into curing condition, it cause the information credibility evaluation er-ror is bigger. Based on variable weights of BP neural network adaptive network topological structure of the C 2C network in-formation credibility evaluation is proposed. With 12 d credibility factors as the input vector, the system structure with cred-ibility as the output of network information, by adjusting the weights of network topology vector set trust cycle response adaptive weighted variables function, and effectively reduce the operation cost of iterative algorithm. Simulation results show that the new network information robustness evaluation model can make the C2C website information evaluation error rate decreased sharply, system has good robust stability and robustness, can effectively promote the C2C network sound op-eration and development.

  11. Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

    Science.gov (United States)

    Shabani, Hikma; Mohamud Ahmed, Musse; Khan, Sheroz; Hameed, Shahab Ahmed; Hadi Habaebi, Mohamed

    2013-12-01

    A smart grid refers to a modernization of the electricity system that brings intelligence, reliability, efficiency and optimality to the power grid. To provide an automated and widely distributed energy delivery, the smart grid will be branded by a two-way flow of electricity and information system between energy suppliers and their customers. Thus, the smart grid is a power grid that integrates data communication networks which provide the collected and analysed data at all levels in real time. Therefore, the performance of communication systems is so vital for the success of smart grid. Merit to the ZigBee/IEEE802.15.4std low cost, low power, low data rate, short range, simplicity and free licensed spectrum that makes wireless sensor networks (WSNs) the most suitable wireless technology for smart grid applications. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In order to improve the performance of communication systems, this paper proposes an optimal throughput and self-adaptability of ZigBee/IEEE802.15.4std for smart grid.

  12. The Crane Robust Control

    Directory of Open Access Journals (Sweden)

    Marek Hicar

    2004-01-01

    Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.

  13. Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans.

    Science.gov (United States)

    Schmidt, Matthew; Lo, Joseph Y; Grzetic, Shelby; Lutzky, Carly; Brizel, David M; Das, Shiva K

    2015-08-01

    Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Knowledge-based radiotherapy (KBRT) plans for each of ten "query" patients were semiautomatically generated by identifying the most similar "match" patient in a database of 103 clinical manually created patient plans. The match patient's plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during

  14. 区间自适应遗传算法在求解马尔可夫状态转移矩阵中的应用%Application of Interval Adaptive Genetic Algorithm to Solving Markov State Transfer Matrix

    Institute of Scientific and Technical Information of China (English)

    朱会霞; 玄登影; 张彩虹; 王福林

    2014-01-01

    将区间自适应遗传算法应用于马尔可夫预测模型状态转移概率矩阵的求解。用马尔可夫预测法对辽宁省农、林、牧、渔各业产值结构进行了研究,与《中国统计年鉴》整理得到的数据比较,具有较高的预测精度,为优化辽宁省农业产值结构提供参考。%An interval adaptive genetic algorithm was applied to solving the state transfer matrix by using Markov prediction model. The Markov prediction model was employed to study structures of production value in agriculture, forestry, animal husbandry and fishery industries in Liaoning province. The obtained results were compared with the data shown in the China Statistical Yearbooks. It is shown that the method has higher prediction precision and provides references for optimizing the structure of agricultural production value in Liaoning province.

  15. How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

    Science.gov (United States)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2015-04-01

    In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the

  16. Interval arithmetic in calculations

    Science.gov (United States)

    Bairbekova, Gaziza; Mazakov, Talgat; Djomartova, Sholpan; Nugmanova, Salima

    2016-10-01

    Interval arithmetic is the mathematical structure, which for real intervals defines operations analogous to ordinary arithmetic ones. This field of mathematics is also called interval analysis or interval calculations. The given math model is convenient for investigating various applied objects: the quantities, the approximate values of which are known; the quantities obtained during calculations, the values of which are not exact because of rounding errors; random quantities. As a whole, the idea of interval calculations is the use of intervals as basic data objects. In this paper, we considered the definition of interval mathematics, investigated its properties, proved a theorem, and showed the efficiency of the new interval arithmetic. Besides, we briefly reviewed the works devoted to interval analysis and observed basic tendencies of development of integral analysis and interval calculations.

  17. Better Confidence Intervals for Importance Sampling

    OpenAIRE

    HALIS SAK; WOLFGANG HÖRMANN; JOSEF LEYDOLD

    2010-01-01

    It is well known that for highly skewed distributions the standard method of using the t statistic for the confidence interval of the mean does not give robust results. This is an important problem for importance sampling (IS) as its final distribution is often skewed due to a heavy tailed weight distribution. In this paper, we first explain Hall's transformation and its variants to correct the confidence interval of the mean and then evaluate the performance of these methods for two numerica...

  18. Adaptive Robust Attitude Control of Spacecraft Based on Trajectory Tracking%基于轨迹跟踪的航天器姿态自适应鲁棒控制

    Institute of Scientific and Technical Information of China (English)

    周端; 郭毓; 陈庆伟; 胡维礼

    2013-01-01

    In order to implement the rapid attitude maneuvering control of flexible spacecrafts in large-angle mobility mode in the presence of inertia uncertainties and external disturbances in space, inspired by the model of cell membrane discharge, an adaptive robust attitude controller is proposed. In the investigation, first, the kinematics and dynamics of flexible spacecraft are analyzed. Then, an robust control law, which is based on the pre-planned attitude trajectory and is adaptive to uncertain inertia, is put forward to improve the rapid attitude maneuvering performance and suppress the vibration of flexible panels. Finally, to avoid the degradation of pointing accuracy and stability due to the attitude jump during the maneuvering, an improved adaptive robust controller is designed based on the dynamic model of cell membrane discharge. It is proved that the proposed controller guarantees the asymptotical stability of the closed-loop system. Moreover, under bounded inertia estimation errors, uniformly-ultimate bounded tracking errors can be obtained with the controller. Simulation results verify the effectiveness of the proposed controller.%针对存在不确定惯量和空间环境干扰的挠性航天器姿态大角度快速机动控制问题,提出了一种受细胞膜放电模型启发的自适应鲁棒姿态控制器设计方法.首先,为了快速完成姿态机动任务,并尽可能少激发挠性帆板振动,在挠性航天器运动学和动力学分析的基础上,提出了基于预先规划姿态运动轨迹且对不确定惯量具有自适应能力的自适应鲁棒控制器.在此基础上,为了改善机动过程中姿态跳变使系统指向精度和稳定度变差的问题,基于细胞膜放电的动力学模型设计了一种改进型自适应鲁棒控制器.所提出的控制器能够保证闭环系统渐进稳定;当惯量估计误差有界时,对于任意初始跟踪误差,该控制器可以保证姿态跟踪误差一致终值有界.仿真结

  19. 基于不确定逼近的机械手自适应鲁棒预测控制%Adaptive robust predictive control for robotic manipulator based on uncertain parameter approximation

    Institute of Scientific and Technical Information of China (English)

    陈志旺; 薛佳伟

    2012-01-01

    针对具有参数不确定性和未知外部干扰的机械手轨迹跟踪问题提出了一种多输入多输出自适应鲁棒预测控制方法.首先根据机械手模型设计非线性鲁棒预测控制律,并在控制律中引入监督控制项;然后利用函数逼近的方法逼近控制律中因模型不确定性以及外部干扰引起的未知项.理论证明了所设计的控制律能够使机械手无静差跟踪期望的关节角轨迹.仿真验证了本文设计方法的有效性.%A multi-input-multi-output adaptive robust predictive control method is presented to solve the trajectory tracking problem of robotic manipulator system with uncertain parameters and unknown external disturbances. A nonlinear robust predictive controller is first designed for the robotic manipulator system, and then a supervisory control is added to the controller. The function approximation is employed to approximate the unknown terms in the predictive control law caused by uncertain system model and external disturbances. It is proved that the proposed controller can make robotic manipulator track the desired joint angle trajectory without static error. Simulation results show the effectiveness of the method.

  20. Indirect adaptive robust predictive control of robotic manipulators based on uncertain parameter approximation%基于不确定逼近的机械手间接自适应鲁棒预测控制

    Institute of Scientific and Technical Information of China (English)

    李桂秋; 陈志旺

    2012-01-01

    In order to make the robotic manipulator system track well and have strong disturbance-opposing ability under the circumstance of parametric uncertainty and external disturbance, an indirect adaptive robust predictive control method was presented. The nonlinear robust predictive controller was designed based on the robotic manipulator system. Then, the cubic spline functions controller was constructed to approximate the unknown terms in the predictive control law caused by system model uncertainties. And the D-controller was added into the control law to inhibit the external disturbance. It is proved that the proposed controller can make the tracking error converge to the origin. The simulation results show the effectiveness of the method.%为了使机械手系统在含有模型不确定项时具有良好的跟踪性能和较强的抗干扰能力,提出了一种间接自适应鲁棒预测控制.首先,针对机械手模型设计出非线性鲁棒预测控制器;然后,基于三次样条函数逼近控制律中因模型不确定性产生的未知项,并在控制律中引入一个D-控制项抑制外部干扰.理论证明了所设计的控制器能够使跟踪误差收敛到原点.仿真验证了所提方法的有效性.

  1. An Interval Type-2 Fuzzy Neural Network Control on Two-Axis Motion System

    Directory of Open Access Journals (Sweden)

    Ye Xiaoting

    2013-11-01

    Full Text Available In this paper, an interval type-2 fuzzy neural network (IT2FNN control system is proposed to control a two-axis motion system, which is composed of two permanent magnet linear synchronous motors. The IT2FNN control system, which combines the merits of an interval type-2 fuzzy logic system and a neural network, is developed to approximate an unknown dynamic function. Moreover, adaptive learning algorithms that can train the parameters of the IT2FNN online are derived using the Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties. To relax the requirement for the value of the lumped uncertainty in the robust controller, an adaptive lumped uncertainty estimation law is also investigated. The proposed control algorithms are implemented. From the simulated and experimental results, the contour tracking performance of the two-axis motion control system is significantly improved and the robustness can be obtained as well using the proposed IT2FNN control system.    

  2. 飞翼无人机的一种鲁棒自适应控制律设计方法%A Robust Adaptive Control Law Design Method for Flying-Wing UAV

    Institute of Scientific and Technical Information of China (English)

    李卫星; 李秀娟; 李春涛; 杨艺

    2014-01-01

    针对飞翼无人机纵向全包线飞行时非线性特性明显和操纵效率变化显著的问题,采用鲁棒伺服 LQR ( RSLQR)与L1自适应相结合的综合自适应控制方法( RSLQR-L1),以C倡(加速度、角速率)为被控变量,设计了飞翼无人机纵向飞行控制系统。结合无人机实际飞行控制品质需求,采用RSLQR方法,设计无人机纵向主控制器;在RSLQR控制器的基本结构上扩展设计L1自适应输出反馈补偿控制器。在系统阐述RSLQR-L1综合自适应控制原理和设计方法的基础上,通过数值仿真验证了控制结构的先进性和鲁棒性,满足了飞翼无人机的控制要求。%To solve the problems of nonlinearity and obviously changed manipulating efficiency in flight of UAV,a longitudinal control law is designed for a Flying-wing UAV,which is the integrating of Robustness Servomechanism Linear Quadratic Regulator ( RSLQR ) and L1 adaptive control method .The controlled variable is chosen as C*,which is a combination of longitudinal acceleration and pitch rate .The baseline controller is based on RSLQR method to fit the control requirement of the UAV .The controller is augmented by L1 adaptive output feedback structure to maintain the desired close-loop system characteristics in the presence of the aerodynamic uncertainties and the significant change of the elevator coefficient caused by the transformation of flight state .This paper summarizes the theory,the design,simulation testing and flight test results using a RSLQR-L1 method,which validates the performance and the robustness of the designed control system.

  3. Neural Adaptive Robust Control of Space Manipulator under Different Gravity Environment%不同重力环境下空间机械臂神经自适应鲁棒控制

    Institute of Scientific and Technical Information of China (English)

    刘福才; 高娟娟; 王芳

    2013-01-01

    Considering change of gravity items from ground alignment under gravity environment to space applications under microgravity environment, a neural network adaptive robust control strategy is proposed for end control of space manipulator, so as to achieve the on-orbit tasks in space under microgravity environment for the space manipulator adjusted on the ground under gravity environment. The control scheme uses neural networks to approach the gravity items of system model on line. Approach errors and system uncertainties can be compensated by using an adaptive robust controller. The control strategy can not depend on the model, avoids the complex calculations of the regression matrix and the estimation of unknown parameter and reduces the computational complexity. The control scheme can guarantee the stability of closed loop system and the asymptotic convergence of tracking errors based on the Lyapunov theory. The simulation results show that the controller is effective in control accuracy for end control of space manipulator under different gravity environments, and has important value for theoretical research and engineering application.%针对空间机械臂从地面装调到空间应用过程中重力项的变化问越,提出了一种神经网络自适应鲁俸补偿控制策略用于空间机械臂的末端控制,从而实现在地面重力环境下装调好的空间机械臂在空间微重力环境下实现在轨操控任务.通过神经网络在线建模来逼近系统模型中变化的重力项,逼近误差及系统的不确定性通过自适应鲁棒控制器来补偿.该控制策略不依赖于系统的模型,避免了回归矩阵的复杂计算及未知参数的估计,降低了计算量.基于李亚普诺夫理论证明了闭环系统的渐近稳定性.仿真结果表明该控制器对不同重力环境下空间机械臂的末端控制均能达到较高的控制精度,具有重要的理论研究和工程应用价值.

  4. 基于软件接收机技术的低载噪比信号自适应鲁棒锁相环研究%Adaptively Robust Phase Lock Loop for Low C/N Carrier Tracking in a GPS Software Receiver

    Institute of Scientific and Technical Information of China (English)

    苗剑峰; 陈武; 孙永荣; 刘建业

    2011-01-01

    An important issue in GPS applications is how to track GPS (global positioning system) signal precisely and continuously under low carrier-to-noise ratio (C/N). In this paper, an adaptively robust filter based low C/N carrier phase lock loop (PLL) is developed under a GPS software receiver platform. Considering the effect of low C/N carrier signal on the traditional tracking loop, a parallel correlation tracking loop is established. A linear optimal estimator is designed to deal with the dependent noises in kinematics model and measurements. Furthermore, an adaptively robust filter is designed based on a three segment function adjust factor. When received signals are under favorable conditions, the performance of the new filter is very similar to a standard Kalman filter. For a practical weak carrier tracking, this new enhanced PLL intelligently tunes the loop parameters according to the total phase jitter analysis. It successfully resists the outliers and dynamic model errors by adaptively balancing the influence of updated dynamic model state and the measurements. The robustness and efficiency of the new filter is demonstrated by some real data testing experiments. The results verify that the standard deviation of the phase errors with this adaptively robust phase tracking loop can reach 0.01 cycles with satellite C/N ratios around 24 dB-Hz, which improves the performance significantly.

  5. Robust automated knowledge capture.

    Energy Technology Data Exchange (ETDEWEB)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  6. Intervals in evolutionary algorithms for global optimization

    Energy Technology Data Exchange (ETDEWEB)

    Patil, R.B.

    1995-05-01

    Optimization is of central concern to a number of disciplines. Interval Arithmetic methods for global optimization provide us with (guaranteed) verified results. These methods are mainly restricted to the classes of objective functions that are twice differentiable and use a simple strategy of eliminating a splitting larger regions of search space in the global optimization process. An efficient approach that combines the efficient strategy from Interval Global Optimization Methods and robustness of the Evolutionary Algorithms is proposed. In the proposed approach, search begins with randomly created interval vectors with interval widths equal to the whole domain. Before the beginning of the evolutionary process, fitness of these interval parameter vectors is defined by evaluating the objective function at the center of the initial interval vectors. In the subsequent evolutionary process the local optimization process returns an estimate of the bounds of the objective function over the interval vectors. Though these bounds may not be correct at the beginning due to large interval widths and complicated function properties, the process of reducing interval widths over time and a selection approach similar to simulated annealing helps in estimating reasonably correct bounds as the population evolves. The interval parameter vectors at these estimated bounds (local optima) are then subjected to crossover and mutation operators. This evolutionary process continues for predetermined number of generations in the search of the global optimum.

  7. Big Boss Interval Games

    NARCIS (Netherlands)

    Alparslan-Gok, S.Z.; Brânzei, R.; Tijs, S.H.

    2008-01-01

    In this paper big boss interval games are introduced and various characterizations are given. The structure of the core of a big boss interval game is explicitly described and plays an important role relative to interval-type bi-monotonic allocation schemes for such games. Specifically, each element

  8. Robustness of Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2011-01-01

    robust design as well as strategies for maintaining the robustness of existing structures throughout their service life. This paper describes an overall theoretical framework for assessing robustness of structures developed within WG1 “Robustness of structures”. Robustness can be defined in different......An important aspect of the COST Action TU0601 “Robustness of structures” concerns the development of a theoretically sound basis for the assessment of robustness and acceptance criteria for structural robustness which can form the basis for development of practical relevant methods for ensuring...

  9. 自适应采样间隔的无线传感器网络多目标跟踪算法%Multi-target tracking algorithm based on adaptive sampling interval in wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    王建平; 赵高丽; 胡孟杰; 陈伟

    2014-01-01

    Multi-target tracking is a hot topic of current research on wireless sensor networks (WSN ). Based on adaptive sampling interval,we propose a multi-target tracking algorithm in order to save energy consumption and prevent tracking lost for WSN.We contrast the targets moving model by using the position metadata,and predicte the targets moving status based on extended Kalman filter (EKF).we adopt the probability density function (PDF )of the estimated targets to establish the tracking cluster.By defining the tracking center,we use Markov distance to quantify the election process of the main node (MN).We comput targets impact strength through the targets importance and the distance to MN node, and then use it to build tracking algorithm.We do the simulation experiment based on MATLAB,and the experiment results show that the proposed algorithm can accurate predict the trajectory of the targets,and adjust the sampling interval while the targets were moving.By analyzing the experiments data,we know that the proposed algorithm can improve the tracking precision and save the energy consumption of WSN obviously.%多目标跟踪是无线传感器网络当前研究的热点问题。针对多目标跟踪存在耗能较大,跟踪丢失等问题,提出了一种自适应采样间隔的多目标跟踪算法。采用跟踪目标的定位元数据来对目标的运动模式进行建模。基于扩展的卡尔曼滤波器来预测跟踪目标状态,采用预测目标定位的概率密度函数构建跟踪簇。通过定义跟踪目标中心,基于马氏距离来量化主节点 MN 的选举过程。通过跟踪目标重要性和其与MN之间的距离来量化目标的影响强度,并以此构建自适应采样间隔的多目标跟踪算法。基于MATLAB进行了仿真实验,实验结果显示,本文设计的跟踪算法能准确预测目标的运动轨迹,能随着运动目标的状态实时采用自适应的采样间隔。通过数据分析得知,本

  10. Analysis and Synthesis of Robust Data Structures

    Science.gov (United States)

    1990-08-01

    1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into

  11. The interval ordering problem

    CERN Document Server

    Dürr, Christoph; Spieksma, Frits C R; Nobibon, Fabrice Talla; Woeginger, Gerhard J

    2011-01-01

    For a given set of intervals on the real line, we consider the problem of ordering the intervals with the goal of minimizing an objective function that depends on the exposed interval pieces (that is, the pieces that are not covered by earlier intervals in the ordering). This problem is motivated by an application in molecular biology that concerns the determination of the structure of the backbone of a protein. We present polynomial-time algorithms for several natural special cases of the problem that cover the situation where the interval boundaries are agreeably ordered and the situation where the interval set is laminar. Also the bottleneck variant of the problem is shown to be solvable in polynomial time. Finally we prove that the general problem is NP-hard, and that the existence of a constant-factor-approximation algorithm is unlikely.

  12. Methods for robustness programming

    NARCIS (Netherlands)

    Olieman, N.J.

    2008-01-01

    Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition

  13. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm......, for which three point forecasting methods are considered as input. The probabilistic forecasts generated are evaluated based on their reliability and sharpness, while compared to forecasts based on quantile regression and the climatology benchmark. The operational application of adapted resampling...

  14. Planning with Robust (L)RTDP

    OpenAIRE

    Buffet, Olivier; Aberdeen, Douglas

    2004-01-01

    Stochastic Shortest Path problems (SSPs), a subclass of Markov Decision Problems (MDPs), can be efficiently dealt with using Real-Time Dynamic Programming (RTDP). Yet, MDP models are often uncertain (obtained through statistics or guessing). The usual approach is robust planning: searching for the best policy under the worst model. This paper shows how RTDP can be made robust in the common case where transition probabilities are known to lie in a given interval.

  15. The robust regulation problem with robust stability

    NARCIS (Netherlands)

    Cevik, M.K.K.; Schumacher, J.M.

    1999-01-01

    Among the most common purposes of control are the tracking of reference signals and the rejection of disturbance signals in the face of uncertainties. The related design problem is called the `robust regulation problem'. Here we investigate the trade-off between the robust regulation constraint and

  16. Interval Scheduling: A Survey

    NARCIS (Netherlands)

    Kolen, A.W.J.; Lenstra, J.K.; Papadimitriou, C.H.; Spieksma, F.C.R.

    2007-01-01

    In interval scheduling, not only the processing times of the jobs but also their starting times are given. This article surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability o

  17. Estimating duration intervals

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); B.L.K. Vroomen (Björn)

    2003-01-01

    textabstractDuration intervals measure the dynamic impact of advertising on sales. More precise, the p per cent duration interval measures the time lag between the advertising impulse and the moment that p per cent of its effect has decayed. In this paper, we derive an expression for the duration

  18. Simultaneous Interval Graphs

    CERN Document Server

    Jampani, Krishnam Raju

    2010-01-01

    In a recent paper, we introduced the simultaneous representation problem (defined for any graph class C) and studied the problem for chordal, comparability and permutation graphs. For interval graphs, the problem is defined as follows. Two interval graphs G_1 and G_2, sharing some vertices I (and the corresponding induced edges), are said to be `simultaneous interval graphs' if there exist interval representations R_1 and R_2 of G_1 and G_2, such that any vertex of I is mapped to the same interval in both R_1 and R_2. Equivalently, G_1 and G_2 are simultaneous interval graphs if there exist edges E' between G_1-I and G_2-I such that G_1 \\cup G_2 \\cup E' is an interval graph. Simultaneous representation problems are related to simultaneous planar embeddings, and have applications in any situation where it is desirable to consistently represent two related graphs, for example: interval graphs capturing overlaps of DNA fragments of two similar organisms; or graphs connected in time, where one is an updated versi...

  19. Interval-Valued Model Level Fuzzy Aggregation-Based Background Subtraction.

    Science.gov (United States)

    Chiranjeevi, Pojala; Sengupta, Somnath

    2016-07-29

    In a recent work, the effectiveness of neighborhood supported model level fuzzy aggregation was shown under dynamic background conditions. The multi-feature fuzzy aggregation used in that approach uses real fuzzy similarity values, and is robust for low and medium-scale dynamic background conditions such as swaying vegetation, sprinkling water, etc. The technique, however, exhibited some limitations under heavily dynamic background conditions, as features have high uncertainty under such noisy conditions and these uncertainties were not captured by real fuzzy similarity values. Our proposed algorithm is particularly focused toward improving the detection under heavy dynamic background conditions by modeling uncertainties in the data by interval-valued fuzzy set. In this paper, real-valued fuzzy aggregation has been extended to interval-valued fuzzy aggregation by considering uncertainties over real similarity values. We build up a procedure to calculate the uncertainty that varies for each feature, at each pixel, and at each time instant. We adaptively determine membership values at each pixel by the Gaussian of uncertainty value instead of fixed membership values used in recent fuzzy approaches, thereby, giving importance to a feature based on its uncertainty. Interval-valued Choquet integral is evaluated using interval similarity values and the membership values in order to calculate interval-valued fuzzy similarity between model and current. Adequate qualitative and quantitative studies are carried out to illustrate the effectiveness of the proposed method in mitigating heavily dynamic background situations as compared to state-of-the-art.

  20. Contrasting Diversity Values: Statistical Inferences Based on Overlapping Confidence Intervals

    Science.gov (United States)

    MacGregor-Fors, Ian; Payton, Mark E.

    2013-01-01

    Ecologists often contrast diversity (species richness and abundances) using tests for comparing means or indices. However, many popular software applications do not support performing standard inferential statistics for estimates of species richness and/or density. In this study we simulated the behavior of asymmetric log-normal confidence intervals and determined an interval level that mimics statistical tests with P(α) = 0.05 when confidence intervals from two distributions do not overlap. Our results show that 84% confidence intervals robustly mimic 0.05 statistical tests for asymmetric confidence intervals, as has been demonstrated for symmetric ones in the past. Finally, we provide detailed user-guides for calculating 84% confidence intervals in two of the most robust and highly-used freeware related to diversity measurements for wildlife (i.e., EstimateS, Distance). PMID:23437239

  1. Robustness Analysis for Value-Freezing Signal Temporal Logic

    Directory of Open Access Journals (Sweden)

    L. Brim

    2013-08-01

    Full Text Available In our previous work we have introduced the logic STL*, an extension of Signal Temporal Logic (STL that allows value freezing. In this paper, we define robustness measures for STL* by adapting the robustness measures previously introduced for Metric Temporal Logic (MTL. Furthermore, we present an algorithm for STL* robustness computation, which is implemented in the tool Parasim. Application of STL* robustness analysis is demonstrated on case studies.

  2. Advances in Adaptive Control Methods

    Science.gov (United States)

    Nguyen, Nhan

    2009-01-01

    This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

  3. INTERVAL OBSERVER FOR A BIOLOGICAL REACTOR MODEL

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2014-05-01

    Full Text Available The method of an interval observer design for nonlinear systems with parametric uncertainties is considered. The interval observer synthesis problem for systems with varying parameters consists in the following. If there is the uncertainty restraint for the state values of the system, limiting the initial conditions of the system and the set of admissible values for the vector of unknown parameters and inputs, the interval existence condition for the estimations of the system state variables, containing the actual state at a given time, needs to be held valid over the whole considered time segment as well. Conditions of the interval observers design for the considered class of systems are shown. They are: limitation of the input and state, the existence of a majorizing function defining the uncertainty vector for the system, Lipschitz continuity or finiteness of this function, the existence of an observer gain with the suitable Lyapunov matrix. The main condition for design of such a device is cooperativity of the interval estimation error dynamics. An individual observer gain matrix selection problem is considered. In order to ensure the property of cooperativity for interval estimation error dynamics, a static transformation of coordinates is proposed. The proposed algorithm is demonstrated by computer modeling of the biological reactor. Possible applications of these interval estimation systems are the spheres of robust control, where the presence of various types of uncertainties in the system dynamics is assumed, biotechnology and environmental systems and processes, mechatronics and robotics, etc.

  4. Robust Object Tracking Based on Adaptive and Incremental Subspace Learning%基于增量子空间自适应决策的目标跟踪

    Institute of Scientific and Technical Information of China (English)

    仝小敏; 张艳宁; 杨涛

    2011-01-01

    基于增量子空间的目标跟踪算法多数不加选择地将检测到的目标作为模板训练的样本,并以固定频率更新模板,这种无反馈闭环机制使得算法在目标外观模型发生变化、光照变化等复杂条件下难以鲁棒跟踪目标,一旦跟踪失败很难从错误中恢复.为此,我们提出一种反馈闭环跟踪算法,在增量子空间粒子滤波跟踪框架下,引入跟踪状态判决作为后续模板更新依据.通过判决反馈信息选择合适的样本适时更新模板,有效克服目标外观模型的变化,持续跟踪目标.实验结果表明,由于引入跟踪状态判决,在目标外观变化、光照变化等情况下,本算法能够以与环境相适应的频率及时更新模板,提高跟踪精度,实验结果验证了本文算法的鲁棒性和有效性.%The traditional target tracking algorithm usually trains the template with detected samples and updates the template at a fixed frequency. This close-loop mechanism lacks feedback and often makes it impossible to track targets robustly when target appearance or illumination changes. Besides, it can not recover from tracking failure easily. Therefore, we propose a feedback-loop tracking framework by bringing in the tracking state judgement. In this framework, the tracking state judgement works as the basis of the following template updating. According to the tracking state judgement, we can choose suitable samples to update the template at appropriate time so as to track targets continuously. Experimental results show that our method can get the current template immediately and correctly due to the tracking state judgement and decision mechanism. We can upate the template at an adaptive frequency and meanwhile track targets correctly even in the case of target appearance or illumination changing.

  5. Step Detection Robust against the Dynamics of Smartphones

    Directory of Open Access Journals (Sweden)

    Hwan-hee Lee

    2015-10-01

    Full Text Available A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms.

  6. Robustness in Railway Operations (RobustRailS)

    DEFF Research Database (Denmark)

    Jensen, Jens Parbo; Nielsen, Otto Anker

    This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time. The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First, the approach considers...... the existing stopping patterns of the railway lines. Then, based on the passenger demand we try to optimize the overall utility by changing the stopping pattern in a way that capacity utilization is reduced without affecting the frequency of the train lines nor increasing the passengers’ travel time....

  7. Environmental change makes robust ecological networks fragile

    Science.gov (United States)

    Strona, Giovanni; Lafferty, Kevin D.

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.

  8. Biological Robustness: Paradigms, Mechanisms, and Systems Principles

    Directory of Open Access Journals (Sweden)

    James Michael Whitacre

    2012-05-01

    Full Text Available Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g. mutational, environmental are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior.

  9. Product interval automata

    Indian Academy of Sciences (India)

    Deepak D’Souza; P S Thiagarajan

    2002-04-01

    We identify a subclass of timed automata called product interval automata and develop its theory. These automata consist of a network of timed agents with the key restriction being that there is just one clock for each agent and the way the clocks are read and reset is determined by the distribution of shared actions across the agents. We show that the resulting automata admit a clean theory in both logical and language theoretic terms. We also show that product interval automata are expressive enough to model the timed behaviour of asynchronous digital circuits.

  10. Circadian modulation of interval timing in mice.

    Science.gov (United States)

    Agostino, Patricia V; do Nascimento, Micaela; Bussi, Ivana L; Eguía, Manuel C; Golombek, Diego A

    2011-01-25

    Temporal perception is fundamental to environmental adaptation in humans and other animals. To deal with timing and time perception, organisms have developed multiple systems that are active over a broad range of order of magnitude, the most important being circadian timing, interval timing and millisecond timing. The circadian pacemaker is located in the suprachiasmatic nuclei (SCN) of the hypothalamus, and is driven by a self-sustaining oscillator with a period close to 24h. Time estimation in the second-to-minutes range--known as interval timing--involves the interaction of the basal ganglia and the prefrontal cortex. In this work we tested the hypothesis that interval timing in mice is sensitive to circadian modulations. Animals were trained following the peak-interval (PI) procedure. Results show significant differences in the estimation of 24-second intervals at different times of day, with a higher accuracy in the group trained at night, which were maintained under constant dark (DD) conditions. Interval timing was also studied in animals under constant light (LL) conditions, which abolish circadian rhythmicity. Mice under LL conditions were unable to acquire temporal control in the peak interval procedure. Moreover, short time estimation in animals subjected to circadian desynchronizations (modeling jet lag-like situations) was also affected. Taken together, our results indicate that short-time estimation is modulated by the circadian clock. Copyright © 2010 Elsevier B.V. All rights reserved.

  11. Robust Regression and Lasso

    CERN Document Server

    Xu, Huan; Mannor, Shie

    2008-01-01

    Lasso, or $\\ell^1$ regularized least squares, has been explored extensively for its remarkable sparsity properties. It is shown in this paper that the solution to Lasso, in addition to its sparsity, has robustness properties: it is the solution to a robust optimization problem. This has two important consequences. First, robustness provides a connection of the regularizer to a physical property, namely, protection from noise. This allows a principled selection of the regularizer, and in particular, generalizations of Lasso that also yield convex optimization problems are obtained by considering different uncertainty sets. Secondly, robustness can itself be used as an avenue to exploring different properties of the solution. In particular, it is shown that robustness of the solution explains why the solution is sparse. The analysis as well as the specific results obtained differ from standard sparsity results, providing different geometric intuition. Furthermore, it is shown that the robust optimization formul...

  12. Robust Geometric Spanners

    CERN Document Server

    Bose, Prosenjit; Morin, Pat; Smid, Michiel

    2012-01-01

    Highly connected and yet sparse graphs (such as expanders or graphs of high treewidth) are fundamental, widely applicable and extensively studied combinatorial objects. We initiate the study of such highly connected graphs that are, in addition, geometric spanners. We define a property of spanners called robustness. Informally, when one removes a few vertices from a robust spanner, this harms only a small number of other vertices. We show that robust spanners must have a superlinear number of edges, even in one dimension. On the positive side, we give constructions, for any dimension, of robust spanners with a near-linear number of edges.

  13. Robustness of Structural Systems

    DEFF Research Database (Denmark)

    Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.

    2007-01-01

    The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...

  14. Adaptive Vertex Fitting

    CERN Document Server

    Frühwirth, R; Vanlaer, Pascal

    2007-01-01

    Vertex fitting frequently has to deal with both mis-associated tracks and mis-measured track errors. A robust, adaptive method is presented that is able to cope with contaminated data. The method is formulated as an iterative re-weighted Kalman filter. Annealing is introduced to avoid local minima in the optimization. For the initialization of the adaptive filter a robust algorithm is presented that turns out to perform well in a wide range of applications. The tuning of the annealing schedule and of the cut-off parameter is described, using simulated data from the CMS experiment. Finally, the adaptive property of the method is illustrated in two examples.

  15. Synchronised firing patterns in a random network of adaptive exponential integrate-and-fire

    CERN Document Server

    Borges, Fernando da Silva; Lameu, Ewandson Luiz; Bonetti, Robson Conrado; Iarosz, Kelly Cristiane; Caldas, Iberê Luiz; Baptista, Murilo da Silva; Batista, Antonio Marcos

    2016-01-01

    We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections, by constructing parameter spaces that identify these synchronous behaviours from measurements of the inter-spike interval and the calculation of the order parameter. Moreover, we verify the robustness of synchronisaton by applying an external perturbation to each neuron. The simulations show that bursting synchronisation is more robust than spike synchronisation.

  16. Robustness promotes evolvability of thermotolerance in an RNA virus

    Directory of Open Access Journals (Sweden)

    Turner Paul E

    2008-08-01

    Full Text Available Abstract Background The ability for an evolving population to adapt to a novel environment is achieved through a balance of robustness and evolvability. Robustness is the invariance of phenotype in the face of perturbation and evolvability is the capacity to adapt in response to selection. Genetic robustness has been posited, depending on the underlying mechanism, to either decrease the efficacy of selection, or increase the possibility of future adaptation. However, the true effect of genetic robustness on evolvability in biological systems remains uncertain. Results Here we demonstrate that genetic robustness increases evolvability of thermotolerance in laboratory populations of the RNA virus φ6. We observed that populations founded by robust clones evolved greater resistance to heat shock, relative to populations founded by brittle (less-robust clones. Thus, we provide empirical evidence for the idea that robustness can promote evolvability in this environment, and further suggest that evolvability can arise indirectly via selection for robustness, rather than through direct selective action. Conclusion Our data imply that greater tolerance of mutational change is associated with virus adaptability in a new niche, a finding generally relevant to evolutionary biology, and informative for elucidating how viruses might evolve to emerge in new habitats and/or overcome novel therapies.

  17. Interval methods: An introduction

    DEFF Research Database (Denmark)

    Achenie, L.E.K.; Kreinovich, V.; Madsen, Kaj

    2006-01-01

    . An important characteristic of the computer performance in scientific computing is the accuracy of the Computation results. Often, we can estimate this accuracy by using traditional statistical techniques. However, in many practical situations, we do not know the probability distributions of different...... the potential for solving increasingly difficult computational problems. However, given the complexity of modern computer architectures, the task of realizing this potential needs careful attention. A main concern of HPC is the development of software that optimizes the performance of a given computer...... measurement, estimation, and/or roundoff errors, we only know estimates of the upper bounds on the corresponding measurement errors, i.e., we only know an interval of possible values of each such error. The papers from the following chapter contain the description of the corresponding '' interval computation...

  18. Varieties of Confidence Intervals.

    Science.gov (United States)

    Cousineau, Denis

    2017-01-01

    Error bars are useful to understand data and their interrelations. Here, it is shown that confidence intervals of the mean (CI M s) can be adjusted based on whether the objective is to highlight differences between measures or not and based on the experimental design (within- or between-group designs). Confidence intervals (CIs) can also be adjusted to take into account the sampling mechanisms and the population size (if not infinite). Names are proposed to distinguish the various types of CIs and the assumptions underlying them, and how to assess their validity is explained. The various CIs presented here are easily obtained from a succession of multiplicative adjustments to the basic (unadjusted) CI width. All summary results should present a measure of precision, such as CIs, as this information is complementary to effect sizes.

  19. Applications of interval computations

    CERN Document Server

    Kreinovich, Vladik

    1996-01-01

    Primary Audience for the Book • Specialists in numerical computations who are interested in algorithms with automatic result verification. • Engineers, scientists, and practitioners who desire results with automatic verification and who would therefore benefit from the experience of suc­ cessful applications. • Students in applied mathematics and computer science who want to learn these methods. Goal Of the Book This book contains surveys of applications of interval computations, i. e. , appli­ cations of numerical methods with automatic result verification, that were pre­ sented at an international workshop on the subject in EI Paso, Texas, February 23-25, 1995. The purpose of this book is to disseminate detailed and surveyed information about existing and potential applications of this new growing field. Brief Description of the Papers At the most fundamental level, interval arithmetic operations work with sets: The result of a single arithmetic operation is the set of all possible results as the o...

  20. Overestimation of the second time interval replaces time-shrinking when the difference between two adjacent time intervals increases

    Directory of Open Access Journals (Sweden)

    Yoshitaka eNakajima

    2014-05-01

    Full Text Available When the onsets of three successive sound bursts mark two adjacent time intervals, the second time interval can be underestimated when it is physically longer than the first time interval by up to 100 ms. This illusion, time-shrinking, is very stable when the first time interval is 200 ms or shorter (Nakajima et al., 2004, Perception, 33. Time-shrinking had been considered a kind of perceptual assimilation to make the first and the second time interval more similar to each other. Here we investigated whether the underestimation of the second time interval was replaced by an overestimation if the physical difference between the neighboring time intervals was too large for the assimilation to take place; this was a typical situation in which a perceptual contrast could be expected. Three experiments to measure the overestimation/underestimation of the second time interval by the method of adjustment were conducted. The first time interval was varied from 40 to 280 ms, and such overestimations indeed took place when the first time interval was 80-280 ms. The overestimations were robust when the second time interval was longer than the first time interval by 240 ms or more, and the magnitude of the overestimation was larger than 100 ms in some conditions. Thus, a perceptual contrast to replace time-shrinking was established. An additional experiment indicated that this contrast did not affect the perception of the first time interval substantially: The contrast in the present conditions seemed unilateral.

  1. Magnetic Resonance Fingerprinting with short relaxation intervals.

    Science.gov (United States)

    Amthor, Thomas; Doneva, Mariya; Koken, Peter; Sommer, Karsten; Meineke, Jakob; Börnert, Peter

    2017-09-01

    The aim of this study was to investigate a technique for improving the performance of Magnetic Resonance Fingerprinting (MRF) in repetitive sampling schemes, in particular for 3D MRF acquisition, by shortening relaxation intervals between MRF pulse train repetitions. A calculation method for MRF dictionaries adapted to short relaxation intervals and non-relaxed initial spin states is presented, based on the concept of stationary fingerprints. The method is applicable to many different k-space sampling schemes in 2D and 3D. For accuracy analysis, T1 and T2 values of a phantom are determined by single-slice Cartesian MRF for different relaxation intervals and are compared with quantitative reference measurements. The relevance of slice profile effects is also investigated in this case. To further illustrate the capabilities of the method, an application to in-vivo spiral 3D MRF measurements is demonstrated. The proposed computation method enables accurate parameter estimation even for the shortest relaxation intervals, as investigated for different sampling patterns in 2D and 3D. In 2D Cartesian measurements, we achieved a scan acceleration of more than a factor of two, while maintaining acceptable accuracy: The largest T1 values of a sample set deviated from their reference values by 0.3% (longest relaxation interval) and 2.4% (shortest relaxation interval). The largest T2 values showed systematic deviations of up to 10% for all relaxation intervals, which is discussed. The influence of slice profile effects for multislice acquisition is shown to become increasingly relevant for short relaxation intervals. In 3D spiral measurements, a scan time reduction of 36% was achieved, maintaining the quality of in-vivo T1 and T2 maps. Reducing the relaxation interval between MRF sequence repetitions using stationary fingerprint dictionaries is a feasible method to improve the scan efficiency of MRF sequences. The method enables fast implementations of 3D spatially resolved

  2. Mechanisms for Robust Cognition

    Science.gov (United States)

    Walsh, Matthew M.; Gluck, Kevin A.

    2015-01-01

    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

  3. Mechanisms for Robust Cognition

    Science.gov (United States)

    Walsh, Matthew M.; Gluck, Kevin A.

    2015-01-01

    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

  4. Robustness of networks

    NARCIS (Netherlands)

    Wang, H.

    2009-01-01

    Our society depends more strongly than ever on large networks such as transportation networks, the Internet and power grids. Engineers are confronted with fundamental questions such as “how to evaluate the robustness of networks for a given service?”, “how to design a robust network?”, because netwo

  5. L1 adaptive controller of nonlinear reference system in presence of unmatched uncertainties

    Institute of Scientific and Technical Information of China (English)

    宋海涛; 张涛; 张国良

    2016-01-01

    An extension of L1 adaptive control is proposed for the unmatched uncertain nonlinear system with the nonlinear reference system that defines the performance specifications. The control law adapts fast and tracks the reference system with the guaranteed robustness and transient performance in the presence of unmatched uncertainties. The interval analysis is used to build the quasi-linear parameter-varying model of unmatched nonlinear system, and the robust stability of the proposed controller is addressed by sum of squares programming. The transient performance analysis shows that within the limit of hardware a large adaption gain can improve the asymptotic tracking performance. Simulation results are provided to demonstrate the theoretical findings of the proposed controller.

  6. Robust fault diagnosis for a class of nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    Zhanshan WANG; Huaguang ZHANG

    2006-01-01

    Robust fault diagnosis based on adaptive observer is studied for a class of nonlinear systems up to output injection. Adaptive fault updating laws are designed to guarantee the stability of the diagnosis system. The upper bounds of the state estimation error and fault estimation error of the adaptive observer are given respectively and the effects of parameter in the adaptive updating laws on fault estimation accuracy are also discussed. Simulation example demonstrates the effectiveness of the proposed methods and the analysis results.

  7. Online adaptation and verification of VMAT

    Energy Technology Data Exchange (ETDEWEB)

    Crijns, Wouter, E-mail: wouter.crijns@uzleuven.be [KU Leuven Department of Oncology, Laboratory of Experimental Radiotherapy, Herestraat 49, Leuven 3000, Belgium and KU Leuven Medical Imaging Research Center, Herestraat 49, Leuven 3000 (Belgium); Defraene, Gilles; Depuydt, Tom; Haustermans, Karin [KU Leuven Department of Oncology, Laboratory of Experimental Radiotherapy, Herestraat 49, Leuven 3000 (Belgium); Van Herck, Hans [KU Leuven Medical Imaging Research Center, Herestraat 49, Leuven 3000, Belgium and KU Leuven Department of Electrical Engineering (ESAT), PSI, Center for Processing Speech and Images, Leuven 3000 (Belgium); Maes, Frederik [KU Leuven Department of Electrical Engineering (ESAT), PSI, Center for Processing Speech and Images, Leuven 3000, Belgium and KU Leuven iMinds - Medical IT Department, Leuven 3000 (Belgium); Van den Heuvel, Frank [Department of Oncology, MRC-CR-UK Gray Institute of Radiation Oncology and Biology, University of Oxford, Oxford OX1 2JD (United Kingdom)

    2015-07-15

    practice. Results: The proposed adaptation of a two-arc VMAT plan resulted in the intended CTV{sub mean} (Δ ≤ 3%) and TCP (ΔTCP ≤ 0.001). Moreover, the method assures the intended CI{sub 95%} (Δ ≤ 11%) resulting in lowered rectal NTCP for all cases. Compared to replanning, their adaptation is faster (13 s vs 10 min) and more intuitive. Compared to the current clinical practice, it has a better protection of the healthy tissue. Compared to IMRT, VMAT is more robust to anatomical variations, but it is also less sensitive to the different correction steps. The observed variations of the plan parameters in their database included a linear dependence on the date of treatment planning and on the target radius. The MCS is not retained as QA metric due to a contrasting behavior of its components (LSV and AAV). If three out of four plan parameters (MU, EqFS, AAV, and LSV) need to lie inside a 50% prediction interval (3/4—50%PI), all adapted plans will be accepted. In contrast, all replanned plans do not meet this loose criterion, mainly because they have no connection to the initially optimized and verified plan. Conclusions: A direct (forward) VMAT adaptation performs equally well as (inverse) replanning but is faster and can be extended to real-time adaptation. The prediction intervals for the machine parameters are equivalent to the tolerance tables for couch shifts in the current clinical practice. A 3/4—50%PI QA criterion accepts all the adapted plans but rejects all the replanned plans.

  8. Catalase activity as a biomarker for mild-stress-induced robustness in Bacillus weihenstephanensis

    NARCIS (Netherlands)

    Besten, den H.M.W.; Effraimidou, S.; Abee, T.

    2013-01-01

    Microorganisms are able to survive and grow in changing environments by activating stress adaptation mechanisms which may enhance bacterial robustness. Stress-induced enhanced robustness complicates the predictability of microbial inactivation. Using psychrotolerant Bacillus weihenstephanensis strai

  9. Robustness of Structures

    DEFF Research Database (Denmark)

    Faber, M.H.; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard

    2011-01-01

    In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely the developm......In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...

  10. Interval methods: An introduction

    DEFF Research Database (Denmark)

    Achenie, L.E.K.; Kreinovich, V.; Madsen, Kaj

    2006-01-01

    This chapter contains selected papers presented at the Minisymposium on Interval Methods of the PARA'04 Workshop '' State-of-the-Art in Scientific Computing ''. The emphasis of the workshop was on high-performance computing (HPC). The ongoing development of ever more advanced computers provides....... An important characteristic of the computer performance in scientific computing is the accuracy of the Computation results. Often, we can estimate this accuracy by using traditional statistical techniques. However, in many practical situations, we do not know the probability distributions of different...... '' techniques, and the applications of these techniques to various problems of scientific computing....

  11. A Fast and Robust Method for Measuring Optical Channel Gain

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour; Stoustrup, Jakob; Villemoes, L.F.

    2000-01-01

    We present a numerically stable and computational simple method for fast and robust measurement of optical channel gain. By transmitting adaptively designed signals through the channel, good accuracy is possible even in severe noise conditions......We present a numerically stable and computational simple method for fast and robust measurement of optical channel gain. By transmitting adaptively designed signals through the channel, good accuracy is possible even in severe noise conditions...

  12. MULTIDISCIPLINARY ROBUST OPTIMIZATION DESIGN

    Institute of Scientific and Technical Information of China (English)

    Chen Jianjiang; Xiao Renbin; Zhong Yifang; Dou Gang

    2005-01-01

    Because uncertainty factors inevitably exist under multidisciplinary design environment, a hierarchical multidisciplinary robust optimization design based on response surface is proposed. The method constructs optimization model of subsystem level and system level to coordinate the coupling among subsystems, and also the response surface based on the artificial neural network is introduced to provide information for system level optimization tool to maintain the independence of subsystems,i.e. to realize multidisciplinary parallel design. The application case of electrical packaging demonstrates that reasonable robust optimum solution can be yielded and it is a potential and efficient multidisciplinary robust optimization approach.

  13. Real-Time Game Adaptation for Optimizing Player Satisfaction

    DEFF Research Database (Denmark)

    Yannakakis, Georgios; Hallam, John

    2009-01-01

    preferences for augmented-reality game players. An adaptive mechanism then adjusts controllable game parameters in real time in order to improve the entertainment value of the game for the player. The basic approach presented here applies gradient ascent to the user model to suggest the direction of parameter...... adjustment that leads toward games of higher entertainment value. A simple rule set exploits the derivative information to adjust specific game parameters to augment the entertainment value. Those adjustments take place frequently during the game with interadjustment intervals that maintain the user model......'s accuracy. Performance of the adaptation mechanism is evaluated using a game survey experiment. Results indicate the efficacy and robustness of the mechanism in adapting the game according to a user's individual playing features and enhancing the gameplay experience. The limitations and the use...

  14. Interval-based Synthesis

    Directory of Open Access Journals (Sweden)

    Angelo Montanari

    2014-08-01

    Full Text Available We introduce the synthesis problem for Halpern and Shoham's modal logic of intervals extended with an equivalence relation over time points, abbreviated HSeq. In analogy to the case of monadic second-order logic of one successor, the considered synthesis problem receives as input an HSeq formula phi and a finite set Sigma of propositional variables and temporal requests, and it establishes whether or not, for all possible evaluations of elements in Sigma in every interval structure, there exists an evaluation of the remaining propositional variables and temporal requests such that the resulting structure is a model for phi. We focus our attention on decidability of the synthesis problem for some meaningful fragments of HSeq, whose modalities are drawn from the set A (meets, Abar (met by, B (begins, Bbar (begun by, interpreted over finite linear orders and natural numbers. We prove that the fragment ABBbareq is decidable (non-primitive recursive hard, while the fragment AAbarBBbar turns out to be undecidable. In addition, we show that even the synthesis problem for ABBbar becomes undecidable if we replace finite linear orders by natural numbers.

  15. Interval probabilistic neural network.

    Science.gov (United States)

    Kowalski, Piotr A; Kulczycki, Piotr

    2017-01-01

    Automated classification systems have allowed for the rapid development of exploratory data analysis. Such systems increase the independence of human intervention in obtaining the analysis results, especially when inaccurate information is under consideration. The aim of this paper is to present a novel approach, a neural networking, for use in classifying interval information. As presented, neural methodology is a generalization of probabilistic neural network for interval data processing. The simple structure of this neural classification algorithm makes it applicable for research purposes. The procedure is based on the Bayes approach, ensuring minimal potential losses with regard to that which comes about through classification errors. In this article, the topological structure of the network and the learning process are described in detail. Of note, the correctness of the procedure proposed here has been verified by way of numerical tests. These tests include examples of both synthetic data, as well as benchmark instances. The results of numerical verification, carried out for different shapes of data sets, as well as a comparative analysis with other methods of similar conditioning, have validated both the concept presented here and its positive features.

  16. Chaos on the interval

    CERN Document Server

    Ruette, Sylvie

    2017-01-01

    The aim of this book is to survey the relations between the various kinds of chaos and related notions for continuous interval maps from a topological point of view. The papers on this topic are numerous and widely scattered in the literature; some of them are little known, difficult to find, or originally published in Russian, Ukrainian, or Chinese. Dynamical systems given by the iteration of a continuous map on an interval have been broadly studied because they are simple but nevertheless exhibit complex behaviors. They also allow numerical simulations, which enabled the discovery of some chaotic phenomena. Moreover, the "most interesting" part of some higher-dimensional systems can be of lower dimension, which allows, in some cases, boiling it down to systems in dimension one. Some of the more recent developments such as distributional chaos, the relation between entropy and Li-Yorke chaos, sequence entropy, and maps with infinitely many branches are presented in book form for the first time. The author gi...

  17. Interval arithmetic operations for uncertainty analysis with correlated interval variables

    Institute of Scientific and Technical Information of China (English)

    Chao Jiang; Chun-Ming Fu; Bing-Yu Ni; Xu Han

    2016-01-01

    A new interval arithmetic method is proposed to solve interval functions with correlated intervals through which the overestimation problem existing in interval analy-sis could be significantly alleviated. The correlation between interval parameters is defined by the multidimensional par-allelepiped model which is convenient to describe the correlative and independent interval variables in a unified framework. The original interval variables with correlation are transformed into the standard space without correlation, and then the relationship between the original variables and the standard interval variables is obtained. The expressions of four basic interval arithmetic operations, namely addi-tion, subtraction, multiplication, and division, are given in the standard space. Finally, several numerical examples and a two-step bar are used to demonstrate the effectiveness of the proposed method.

  18. Functional and structural vascular adaptations following 8 weeks of low volume high intensity interval training in lower leg of type 2 diabetes patients and individuals at high risk of metabolic syndrome

    DEFF Research Database (Denmark)

    Madsen, Søren Møller; Thorup, Anne Cathrine Sønderstgaard; Overgaard, Kristian;

    2015-01-01

    We wished to investigate the effects of 8 weeks of low volume high intensity interval training (HIIT) on endothelial function of popliteal artery and circulating cell adhesion molecules in type 2 diabetes (T2D) patients and matched controls (CON). Methods: Over 8 weeks, non-active T2D patients...... and CONs cycled three times per week (10 × 60 sec HIIT). Pre- and post-HIIT measurements of endothelial function were conducted by applying flow-mediated dilation (FMD) along with taking venous blood samples. Results: Baseline diameter of popliteal artery increased significantly from an average of 5.53 mm.......12% to 6.58% in the CON-group (p = 0.004) and 4.84% to 5.66% in the T2D-group: (p = 0.045). The shear rate reduced significantly in both groups (CON-group: p = 0.04; T2D-group: p = 0.002). Circulating cell adhesion molecules remained unchanged (p > 0.05). Conclusion: HIIT induced an improvement...

  19. Comparative Study of Different Guard Time Intervals to Improve the BER Performance of Wimax Systems to Minimize the Effects of ISI and ICI under Adaptive Modulation Techniques over SUI1 and AWGN Communication Channels

    CERN Document Server

    Hasan, Md Zahid; Islam, Md Ashraful; Hossain, Riaz

    2009-01-01

    The WIMAX technology based on air interface standard 802.16 wireless MAN is configured in the same way as a traditional cellular network with base stations using point to multipoint architecture to drive a service over a radius up to several kilometers. The range and the Non Line of Sight (NLOS) ability of WIMAX make the system very attractive for users, but there will be slightly higher BER at low SNR. The aim of this paper is the comparative study of different guard time intervals effect for improving BER at different SNR under digital modulation (QPSK, 16QAM and 64QAM) techniques and different communication channels AWGN and fading channels Stanford University Interim (SUI 1) of an WIMAX system. The comparison between these effects with Reed-Solomon (RS) encoder with Convolutional encoder (half) rated codes in FEC channel coding will be investigated. The simulation results of estimated Bit Error Rate (BER) displays that the implementation of interleaved RS code (255,239,8) with (half) rated Convolutional c...

  20. Robust Parameter Coordination for Multidisciplinary Design

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constraints network, which gives a formulated model to analyze the coupling effects between design variables and product specifications. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. To solve this constraint network model, a general consistent algorithm framework is designed and implemented with interval arithmetic and the genetic algorithm, which can deal with both algebraic and ordinary differential equations. With the help of this method, designers could infer the consistent solution space from the given specifications. A case study involving the design of a bogie dumping system demonstrates the usefulness of this approach.