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Sample records for robust adaptive interval

  1. 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

  2. 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.

  3. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... 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 ...

  4. An Overview of the Adaptive Robust DFT

    Directory of Open Access Journals (Sweden)

    Djurović Igor

    2010-01-01

    Full Text Available Abstract This paper overviews basic principles and applications of the robust DFT (RDFT approach, which is used for robust processing of frequency-modulated (FM signals embedded in non-Gaussian heavy-tailed noise. In particular, we concentrate on the spectral analysis and filtering of signals corrupted by impulsive distortions using adaptive and nonadaptive robust estimators. Several adaptive estimators of location parameter are considered, and it is shown that their application is preferable with respect to non-adaptive counterparts. This fact is demonstrated by efficiency comparison of adaptive and nonadaptive RDFT methods for different noise environments.

  5. 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.

  6. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.

  7. Robust Control with Enlaeged Interval of Uncertain Parameters

    Directory of Open Access Journals (Sweden)

    Marek Keresturi

    2002-01-01

    Full Text Available Robust control is advantageous for systems with defined interval of uncertain parameters. This can be substantially enlarged dividing it into a few sub-intervals. Corresponding controllers for each of them may be set after approximate identification of some uncertain plant parameters. The paper deals with application of the pole region assignment method for position control of the crane crab. The same track form is required for uncertain burden mass and approximate value of rope length. Measurement of crab position and speed is supposed, burden deviation angle is observed. Simulation results have verified feasibility of this design procedure.

  8. Global robust exponential stability analysis for interval recurrent neural networks

    International Nuclear Information System (INIS)

    Xu Shengyuan; Lam, James; Ho, Daniel W.C.; Zou Yun

    2004-01-01

    This Letter investigates the problem of robust global exponential stability analysis for interval recurrent neural networks (RNNs) via the linear matrix inequality (LMI) approach. The values of the time-invariant uncertain parameters are assumed to be bounded within given compact sets. An improved condition for the existence of a unique equilibrium point and its global exponential stability of RNNs with known parameters is proposed. Based on this, a sufficient condition for the global robust exponential stability for interval RNNs is obtained. Both of the conditions are expressed in terms of LMIs, which can be checked easily by various recently developed convex optimization algorithms. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition

  9. Robust Adaptable Video Copy Detection

    DEFF Research Database (Denmark)

    Assent, Ira; Kremer, Hardy

    2009-01-01

    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.......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...

  10. 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.

  11. Adaptive Critic Nonlinear Robust Control: A Survey.

    Science.gov (United States)

    Wang, Ding; He, Haibo; Liu, Derong

    2017-10-01

    Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

  12. 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 ...

  13. Robust Adaptive Thresholder For Document Scanning Applications

    Science.gov (United States)

    Hsing, To R.

    1982-12-01

    In document scanning applications, thresholding is used to obtain binary data from a scanner. However, due to: (1) a wide range of different color backgrounds; (2) density variations of printed text information; and (3) the shading effect caused by the optical systems, the use of adaptive thresholding to enhance the useful information is highly desired. This paper describes a new robust adaptive thresholder for obtaining valid binary images. It is basically a memory type algorithm which can dynamically update the black and white reference level to optimize a local adaptive threshold function. The results of high image quality from different types of simulate test patterns can be obtained by this algorithm. The software algorithm is described and experiment results are present to describe the procedures. Results also show that the techniques described here can be used for real-time signal processing in the varied applications.

  14. 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.

  15. Global robust exponential stability for interval neural networks with delay

    International Nuclear Information System (INIS)

    Cui Shihua; Zhao Tao; Guo Jie

    2009-01-01

    In this paper, new sufficient conditions for globally robust exponential stability of neural networks with either constant delays or time-varying delays are given. We show the sufficient conditions for the existence, uniqueness and global robust exponential stability of the equilibrium point by employing Lyapunov stability theory and linear matrix inequality (LMI) technique. Numerical examples are given to show the approval of our results.

  16. Robust adaptive control for Unmanned Aerial Vehicles

    Science.gov (United States)

    Kahveci, Nazli E.

    anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

  17. Robust Confidence Interval for a Ratio of Standard Deviations

    Science.gov (United States)

    Bonett, Douglas G.

    2006-01-01

    Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…

  18. A new criterion for global robust stability of interval neural networks with discrete time delays

    International Nuclear Information System (INIS)

    Li Chuandong; Chen Jinyu; Huang Tingwen

    2007-01-01

    This paper further studies global robust stability of a class of interval neural networks with discrete time delays. By introducing an equivalent transformation of interval matrices, a new criterion on global robust stability is established. In comparison with the results reported in the literature, the proposed approach leads to results with less restrictive conditions. Numerical examples are also worked through to illustrate our results

  19. 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.

  20. Robust Bayes Forecasting For Grouped Binary Data With Known Distortion Interval

    OpenAIRE

    Pashkevich, M.

    2004-01-01

    The paper is devoted the problem of robust forecasting for the beta-mixed hierarchical models of grouped binary data in the case of stochastic additive distortions of binary observations. In the case of known lower and upper bounds of the distortion intervals, a new robust minimax Bayes predictor is developed. The performance of the proposed forecasting technique is validated by computer simulationtadata.

  1. 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. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Optimal time interval for induction of immunologic adaptive response

    International Nuclear Information System (INIS)

    Ju Guizhi; Song Chunhua; Liu Shuzheng

    1994-01-01

    The optimal time interval between prior dose (D1) and challenge dose (D2) for the induction of immunologic adaptive response was investigated. Kunming mice were exposed to 75 mGy X-rays at a dose rate of 12.5 mGy/min. 3, 6, 12, 24 or 60 h after the prior irradiation the mice were challenged with a dose of 1.5 Gy at a dose rate of 0.33 Gy/min. 18h after D2, the mice were sacrificed for examination of immunological parameters. The results showed that with an interval of 6 h between D1 and D2, the adaptive response of the reaction of splenocytes to LPS was induced, and with an interval of 12 h the adaptive responses of spontaneous incorporation of 3 H-TdR into thymocytes and the reaction of splenocytes to Con A and LPS were induced with 75 mGy prior irradiation. The data suggested that the optimal time intervals between D1 and D2 for the induction of immunologic adaptive response were 6 h and 12 h with a D1 of 75 mGy and a D2 of 1.5 Gy. The mechanism of immunologic adaptation following low dose radiation is discussed

  3. Adaptive integral robust control and application to electromechanical servo systems.

    Science.gov (United States)

    Deng, Wenxiang; Yao, Jianyong

    2017-03-01

    This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  4. 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.

  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

    Ben Atitallah, Ismail

    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 subspace detection in impulsive noise

    KAUST Repository

    Ben Atitallah, Ismail; Kammoun, Abla; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.

    2016-01-01

    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.

  8. A novel non-probabilistic approach using interval analysis for robust design optimization

    International Nuclear Information System (INIS)

    Sun, Wei; Dong, Rongmei; Xu, Huanwei

    2009-01-01

    A technique for formulation of the objective and constraint functions with uncertainty plays a crucial role in robust design optimization. This paper presents the first application of interval methods for reformulating the robust optimization problem. Based on interval mathematics, the original real-valued objective and constraint functions are replaced with the interval-valued functions, which directly represent the upper and lower bounds of the new functions under uncertainty. The single objective function is converted into two objective functions for minimizing the mean value and the variation, and the constraint functions are reformulated with the acceptable robustness level, resulting in a bi-level mathematical model. Compared with other methods, this method is efficient and does not require presumed probability distribution of uncertain factors or gradient or continuous information of constraints. Two numerical examples are used to illustrate the validity and feasibility of the presented method

  9. Robust adaptive optics systems for vision science

    Science.gov (United States)

    Burns, S. A.; de Castro, A.; Sawides, L.; Luo, T.; Sapoznik, K.

    2018-02-01

    Adaptive Optics (AO) is of growing importance for understanding the impact of retinal and systemic diseases on the retina. While AO retinal imaging in healthy eyes is now routine, AO imaging in older eyes and eyes with optical changes to the anterior eye can be difficult and requires a control and an imaging system that is resilient when there is scattering and occlusion from the cornea and lens, as well as in the presence of irregular and small pupils. Our AO retinal imaging system combines evaluation of local image quality of the pupil, with spatially programmable detection. The wavefront control system uses a woofer tweeter approach, combining an electromagnetic mirror and a MEMS mirror and a single Shack Hartmann sensor. The SH sensor samples an 8 mm exit pupil and the subject is aligned to a region within this larger system pupil using a chin and forehead rest. A spot quality metric is calculated in real time for each lenslet. Individual lenslets that do not meet the quality metric are eliminated from the processing. Mirror shapes are smoothed outside the region of wavefront control when pupils are small. The system allows imaging even with smaller irregular pupils, however because the depth of field increases under these conditions, sectioning performance decreases. A retinal conjugate micromirror array selectively directs mid-range scatter to additional detectors. This improves detection of retinal capillaries even when the confocal image has poorer image quality that includes both photoreceptors and blood vessels.

  10. Considerations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval.

    Science.gov (United States)

    Raiche, Gilles; Blais, Jean-Guy

    2009-01-01

    In a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.

  11. Multivariable robust adaptive controller using reduced-order model

    Directory of Open Access Journals (Sweden)

    Wei Wang

    1990-04-01

    Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

  12. Robust, Causal, and Incremental Approaches to Investigating Linguistic Adaptation

    Science.gov (United States)

    Roberts, Seán G.

    2018-01-01

    This paper discusses the maximum robustness approach for studying cases of adaptation in language. We live in an age where we have more data on more languages than ever before, and more data to link it with from other domains. This should make it easier to test hypotheses involving adaptation, and also to spot new patterns that might be explained by adaptation. However, there is not much discussion of the overall approach to research in this area. There are outstanding questions about how to formalize theories, what the criteria are for directing research and how to integrate results from different methods into a clear assessment of a hypothesis. This paper addresses some of those issues by suggesting an approach which is causal, incremental and robust. It illustrates the approach with reference to a recent claim that dry environments select against the use of precise contrasts in pitch. Study 1 replicates a previous analysis of the link between humidity and lexical tone with an alternative dataset and finds that it is not robust. Study 2 performs an analysis with a continuous measure of tone and finds no significant correlation. Study 3 addresses a more recent analysis of the link between humidity and vowel use and finds that it is robust, though the effect size is small and the robustness of the measurement of vowel use is low. Methodological robustness of the general theory is addressed by suggesting additional approaches including iterated learning, a historical case study, corpus studies, and studying individual speech. PMID:29515487

  13. Adaptive robust control of the EBR-II reactor

    International Nuclear Information System (INIS)

    Power, M.A.; Edwards, R.M.

    1996-01-01

    Simulation results are presented for an adaptive H ∞ controller, a fixed H ∞ controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H ∞ controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H ∞ and classical controllers. This makes for a superior and more robust controller

  14. Adaptive robust Kalman filtering for precise point positioning

    International Nuclear Information System (INIS)

    Guo, Fei; Zhang, Xiaohong

    2014-01-01

    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. (paper)

  15. Histogram Equalization to Model Adaptation for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Suh Youngjoo

    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.

  16. Robust exponential stability and domains of attraction in a class of interval neural networks

    International Nuclear Information System (INIS)

    Yang Xiaofan; Liao Xiaofeng; Bai Sen; Evans, David J

    2005-01-01

    This paper addresses robust exponential stability as well as domains of attraction in a class of interval neural networks. A sufficient condition for an equilibrium point to be exponentially stable is established. And an estimate on the domains of attraction of exponentially stable equilibrium points is presented. Both the condition and the estimate are formulated in terms of the parameter intervals, the neurons' activation functions and the equilibrium point. Hence, they are easily checkable. In addition, our results neither depend on monotonicity of the activation functions nor on coupling conditions between the neurons. Consequently, these results are of practical importance in evaluating the performance of interval associative memory networks

  17. Detection of heart beats in multimodal data: a robust beat-to-beat interval estimation approach.

    Science.gov (United States)

    Antink, Christoph Hoog; Brüser, Christoph; Leonhardt, Steffen

    2015-08-01

    The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is straightforward under ideal conditions, the exact localization can be a challenging task if the signal is severely contaminated with noise and artifacts. At the same time, other signals directly related to cardiac activity are often available. In this multi-sensor scenario, methods of multimodal sensor-fusion allow the exploitation of redundancies to increase the accuracy and robustness of beat detection.In this paper, an algorithm for the robust detection of heart beats in multimodal data is presented. Classic peak-detection is augmented by robust multi-channel, multimodal interval estimation to eliminate false detections and insert missing beats. This approach yielded a score of 90.70 and was thus ranked third place in the PhysioNet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Muthmodal Data follow-up analysis.In the future, the robust beat-to-beat interval estimator may directly be used for the automated processing of multimodal patient data for applications such as diagnosis support and intelligent alarming.

  18. Robust stability analysis of adaptation algorithms for single perceptron.

    Science.gov (United States)

    Hui, S; Zak, S H

    1991-01-01

    The problem of robust stability and convergence of learning parameters of adaptation algorithms in a noisy environment for the single preceptron is addressed. The case in which the same input pattern is presented in the adaptation cycle is analyzed. The algorithm proposed is of the Widrow-Hoff type. It is concluded that this algorithm is robust. However, the weight vectors do not necessarily converge in the presence of measurement noise. A modified version of this algorithm in which the reduction factors are allowed to vary with time is proposed, and it is shown that this algorithm is robust and that the weight vectors converge in the presence of bounded noise. Only deterministic-type arguments are used in the analysis. An ultimate bound on the error in terms of a convex combination of the initial error and the bound on the noise is obtained.

  19. 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.

  20. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    , (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...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

  1. 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

  2. Robust Stabilization of Fractional-Order Systems with Interval Uncertainties via Fractional-Order Controllers

    Directory of Open Access Journals (Sweden)

    Mohammadtaghi Hamidi Beheshti

    2010-01-01

    Full Text Available We propose a fractional-order controller to stabilize unstable fractional-order open-loop systems with interval uncertainty whereas one does not need to change the poles of the closed-loop system in the proposed method. For this, we will use the robust stability theory of Fractional-Order Linear Time Invariant (FO-LTI systems. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of interval nonlinear systems and especially in fractional-order chaotic systems. Finally numerical simulations are presented to show the effectiveness of the proposed controller.

  3. Robust stability of interval bidirectional associative memory neural network with time delays.

    Science.gov (United States)

    Liao, Xiaofeng; Wong, Kwok-wo

    2004-04-01

    In this paper, the conventional bidirectional associative memory (BAM) neural network with signal transmission delay is intervalized in order to study the bounded effect of deviations in network parameters and external perturbations. The resultant model is referred to as a novel interval dynamic BAM (IDBAM) model. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of unique equilibrium and robust stability are derived. These results are fairly general and can be verified easily. To go further, we extend our investigation to the time-varying delay case. Some robust stability criteria for BAM with perturbations of time-varying delays are derived. Besides, our approach for the analysis allows us to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as the usual C1-smooth sigmoids. We believe that the results obtained have leading significance in the design and application of BAM neural networks.

  4. Global robust asymptotical stability of multi-delayed interval neural networks: an LMI approach

    International Nuclear Information System (INIS)

    Li Chuandong; Liao Xiaofeng; Zhang Rong

    2004-01-01

    Based on the Lyapunov-Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) technique, some delay-dependent criteria for interval neural networks (IDNN) with multiple time-varying delays are derived to guarantee global robust asymptotic stability. The main results are generalizations of some recent results reported in the literature. Numerical example is also given to show the effectiveness of our results

  5. Musical training generalises across modalities and reveals efficient and adaptive mechanisms for reproducing temporal intervals.

    Science.gov (United States)

    Aagten-Murphy, David; Cappagli, Giulia; Burr, David

    2014-03-01

    Expert musicians are able to time their actions accurately and consistently during a musical performance. We investigated how musical expertise influences the ability to reproduce auditory intervals and how this generalises across different techniques and sensory modalities. We first compared various reproduction strategies and interval length, to examine the effects in general and to optimise experimental conditions for testing the effect of music, and found that the effects were robust and consistent across different paradigms. Focussing on a 'ready-set-go' paradigm subjects reproduced time intervals drawn from distributions varying in total length (176, 352 or 704 ms) or in the number of discrete intervals within the total length (3, 5, 11 or 21 discrete intervals). Overall, Musicians performed more veridical than Non-Musicians, and all subjects reproduced auditory-defined intervals more accurately than visually-defined intervals. However, Non-Musicians, particularly with visual stimuli, consistently exhibited a substantial and systematic regression towards the mean interval. When subjects judged intervals from distributions of longer total length they tended to regress more towards the mean, while the ability to discriminate between discrete intervals within the distribution had little influence on subject error. These results are consistent with a Bayesian model that minimizes reproduction errors by incorporating a central tendency prior weighted by the subject's own temporal precision relative to the current distribution of intervals. Finally a strong correlation was observed between all durations of formal musical training and total reproduction errors in both modalities (accounting for 30% of the variance). Taken together these results demonstrate that formal musical training improves temporal reproduction, and that this improvement transfers from audition to vision. They further demonstrate the flexibility of sensorimotor mechanisms in adapting to

  6. Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

    Science.gov (United States)

    Tan, Zhen-ya; He, Feng

    2018-04-01

    With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

  7. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    OpenAIRE

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

    2015-01-01

    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...

  8. Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay

    International Nuclear Information System (INIS)

    Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia

    2009-01-01

    This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.

  9. A Hybrid Interval-Robust Optimization Model for Water Quality Management.

    Science.gov (United States)

    Xu, Jieyu; Li, Yongping; Huang, Guohe

    2013-05-01

    In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

  10. 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.

  11. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...... 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...

  12. Robust Stabilization of Fractional-Order Systems with Interval Uncertainties via Fractional-Order Controllers

    Directory of Open Access Journals (Sweden)

    Sayyad Delshad Saleh

    2010-01-01

    Full Text Available Abstract We propose a fractional-order controller to stabilize unstable fractional-order open-loop systems with interval uncertainty whereas one does not need to change the poles of the closed-loop system in the proposed method. For this, we will use the robust stability theory of Fractional-Order Linear Time Invariant (FO-LTI systems. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of interval nonlinear systems and especially in fractional-order chaotic systems. Finally numerical simulations are presented to show the effectiveness of the proposed controller.

  13. Robust Optimal Adaptive Trajectory Tracking Control of Quadrotor Helicopter

    Directory of Open Access Journals (Sweden)

    M. Navabi

    Full Text Available Abstract This paper focuses on robust optimal adaptive control strategy to deal with tracking problem of a quadrotor unmanned aerial vehicle (UAV in presence of parametric uncertainties, actuator amplitude constraints, and unknown time-varying external disturbances. First, Lyapunov-based indirect adaptive controller optimized by particle swarm optimization (PSO is developed for multi-input multi-output (MIMO nonlinear quadrotor to prevent input constraints violation, and then disturbance observer-based control (DOBC technique is aggregated with the control system to attenuate the effects of disturbance generated by an exogenous system. The performance of synthesis control method is evaluated by a new performance index function in time-domain, and the stability analysis is carried out using Lyapunov theory. Finally, illustrative numerical simulations are conducted to demonstrate the effectiveness of the presented approach in altitude and attitude tracking under several conditions, including large time-varying uncertainty, exogenous disturbance, and control input constraints.

  14. Scale-adaptive Local Patches for Robust Visual Object Tracking

    Directory of Open Access Journals (Sweden)

    Kang Sun

    2014-04-01

    Full Text Available This paper discusses the problem of robustly tracking objects which undergo rapid and dramatic scale changes. To remove the weakness of global appearance models, we present a novel scheme that combines object’s global and local appearance features. The local feature is a set of local patches that geometrically constrain the changes in the target’s appearance. In order to adapt to the object’s geometric deformation, the local patches could be removed and added online. The addition of these patches is constrained by the global features such as color, texture and motion. The global visual features are updated via the stable local patches during tracking. To deal with scale changes, we adapt the scale of patches in addition to adapting the object bound box. We evaluate our method by comparing it to several state-of-the-art trackers on publicly available datasets. The experimental results on challenging sequences confirm that, by using this scale-adaptive local patches and global properties, our tracker outperforms the related trackers in many cases by having smaller failure rate as well as better accuracy.

  15. 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.

  16. Robust sawtooth period control based on adaptive online optimization

    International Nuclear Information System (INIS)

    Bolder, J.J.; Witvoet, G.; De Baar, M.R.; Steinbuch, M.; Van de Wouw, N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.

    2012-01-01

    The systematic design of a robust adaptive control strategy for the sawtooth period using electron cyclotron current drive (ECCD) is presented. Recent developments in extremum seeking control (ESC) are employed to derive an optimized controller structure and offer practical tuning guidelines for its parameters. In this technique a cost function in terms of the desired sawtooth period is optimized online by changing the ECCD deposition location based on online estimations of the gradient of the cost function. The controller design does not require a detailed model of the sawtooth instability. Therefore, the proposed ESC is widely applicable to any sawtoothing plasma or plasma simulation and is inherently robust against uncertainties or plasma variations. Moreover, it can handle a broad class of disturbances. This is demonstrated by time-domain simulations, which show successful tracking of time-varying sawtooth period references throughout the whole operating space, even in the presence of variations in plasma parameters, disturbances and slow launcher mirror dynamics. Due to its simplicity and robustness the proposed ESC is a valuable sawtooth control candidate for any experimental tokamak plasma, and may even be applicable to other fusion-related control problems. (paper)

  17. 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.

  18. Interval Analysis Approach to Prototype the Robust Control of the Laboratory Overhead Crane

    Science.gov (United States)

    Smoczek, J.; Szpytko, J.; Hyla, P.

    2014-07-01

    The paper describes the software-hardware equipment and control-measurement solutions elaborated to prototype the laboratory scaled overhead crane control system. The novelty approach to crane dynamic system modelling and fuzzy robust control scheme design is presented. The iterative procedure for designing a fuzzy scheduling control scheme is developed based on the interval analysis of discrete-time closed-loop system characteristic polynomial coefficients in the presence of rope length and mass of a payload variation to select the minimum set of operating points corresponding to the midpoints of membership functions at which the linear controllers are determined through desired poles assignment. The experimental results obtained on the laboratory stand are presented.

  19. Interval Analysis Approach to Prototype the Robust Control of the Laboratory Overhead Crane

    International Nuclear Information System (INIS)

    Smoczek, J; Szpytko, J; Hyla, P

    2014-01-01

    The paper describes the software-hardware equipment and control-measurement solutions elaborated to prototype the laboratory scaled overhead crane control system. The novelty approach to crane dynamic system modelling and fuzzy robust control scheme design is presented. The iterative procedure for designing a fuzzy scheduling control scheme is developed based on the interval analysis of discrete-time closed-loop system characteristic polynomial coefficients in the presence of rope length and mass of a payload variation to select the minimum set of operating points corresponding to the midpoints of membership functions at which the linear controllers are determined through desired poles assignment. The experimental results obtained on the laboratory stand are presented

  20. Novel global robust stability criteria for interval neural networks with multiple time-varying delays

    International Nuclear Information System (INIS)

    Xu Shengyuan; Lam, James; Ho, Daniel W.C.

    2005-01-01

    This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method

  1. 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.

  2. 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.

  3. Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters

    Directory of Open Access Journals (Sweden)

    Burger Joep

    2017-09-01

    Full Text Available Adaptive survey designs (ASDs optimize design features, given 1 the interactions between the design features and characteristics of sampling units and 2 a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the structure of ASDs. The methodology is illustrated using a simple simulation study and a more complex but realistic case study on the Dutch Travel Survey. The proposed methodology can be applied to other ASD optimization problems. In our simulation study and case study, the ASD was fairly robust to imprecision, but not to realistic dynamics in the design parameters. To deal with the sensitivity of ASDs to changing design parameters, we recommend to learn and update the design parameters.

  4. 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.

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

    KAUST Repository

    Chaoui, Hicham; Khayamy, Mehdy; Aljarboua, Abdullah Abdulaziz

    2017-01-01

    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

  6. 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.

  7. Robust estimation of adaptive tensors of curvature by tensor voting.

    Science.gov (United States)

    Tong, Wai-Shun; Tang, Chi-Keung

    2005-03-01

    Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.

  8. Robust online tracking via adaptive samples selection with saliency detection

    Science.gov (United States)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

    Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

  9. Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties.

    Science.gov (United States)

    Song, Qiankun; Yu, Qinqin; Zhao, Zhenjiang; Liu, Yurong; Alsaadi, Fuad E

    2018-07-01

    In this paper, the boundedness and robust stability for a class of delayed complex-valued neural networks with interval parameter uncertainties are investigated. By using Homomorphic mapping theorem, Lyapunov method and inequality techniques, sufficient condition to guarantee the boundedness of networks and the existence, uniqueness and global robust stability of equilibrium point is derived for the considered uncertain neural networks. The obtained robust stability criterion is expressed in complex-valued LMI, which can be calculated numerically using YALMIP with solver of SDPT3 in MATLAB. An example with simulations is supplied to show the applicability and advantages of the acquired result. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. 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.

  11. 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

  12. 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.

  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. Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays

    International Nuclear Information System (INIS)

    Balasubramaniam, P.; Lakshmanan, S.; Manivannan, A.

    2012-01-01

    Highlights: ► Robust stability analysis for Markovian jumping interval neural networks is considered. ► Both linear fractional and interval uncertainties are considered. ► A new LKF is constructed with triple integral terms. ► MATLAB LMI control toolbox is used to validate theoretical results. ► Numerical examples are given to illustrate the effectiveness of the proposed method. - Abstract: This paper investigates robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional (LKF), some inequality techniques and stochastic stability theory, new delay-dependent stability criteria have been obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.

  15. Interval type-2 fuzzy gain-adaptive controller of a Doubly Fed ...

    African Journals Online (AJOL)

    ... Interval Type-2 Fuzzy Gain Adaptive IP (IT2FGAIP) controller and a conventional IP controller ... and an adaptive IP controller is proposed for the speed control of DFIM in the presence of ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  16. 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.

  17. Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

    2013-09-01

    This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

  18. Design and Analysis of Schemes for Adapting Migration Intervals in Parallel Evolutionary Algorithms.

    Science.gov (United States)

    Mambrini, Andrea; Sudholt, Dirk

    2015-01-01

    The migration interval is one of the fundamental parameters governing the dynamic behaviour of island models. Yet, there is little understanding on how this parameter affects performance, and how to optimally set it given a problem in hand. We propose schemes for adapting the migration interval according to whether fitness improvements have been found. As long as no improvement is found, the migration interval is increased to minimise communication. Once the best fitness has improved, the migration interval is decreased to spread new best solutions more quickly. We provide a method for obtaining upper bounds on the expected running time and the communication effort, defined as the expected number of migrants sent. Example applications of this method to common example functions show that our adaptive schemes are able to compete with, or even outperform, the optimal fixed choice of the migration interval, with regard to running time and communication effort.

  19. Robust adaptive fuzzy neural tracking control for a class of unknown ...

    Indian Academy of Sciences (India)

    In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is ... The robust controller is used to guarantee the stability and to control the per- ..... From the above analysis we have the following theorem:.

  20. Design of Robust Adaptive Array Processors for Non-Stationary Ocean Environments

    National Research Council Canada - National Science Library

    Wage, Kathleen E

    2009-01-01

    The overall goal of this project is to design adaptive array processing algorithms that have good transient performance, are robust to mismatch, work with low sample support, and incorporate waveguide...

  1. Design of uav robust autopilot based on adaptive neuro-fuzzy inference system

    Directory of Open Access Journals (Sweden)

    Mohand Achour Touat

    2008-04-01

    Full Text Available  This paper is devoted to the application of adaptive neuro-fuzzy inference systems to the robust control of the UAV longitudinal motion. The adaptive neore-fuzzy inference system model needs to be trained by input/output data. This data were obtained from the modeling of a ”crisp” robust control system. The synthesis of this system is based on the separation theorem, which defines the structure and parameters of LQG-optimal controller, and further - robust optimization of this controller, based on the genetic algorithm. Such design procedure can define the rule base and parameters of fuzzyfication and defuzzyfication algorithms of the adaptive neore-fuzzy inference system controller, which ensure the robust properties of the control system. Simulation of the closed loop control system of UAV longitudinal motion with adaptive neore-fuzzy inference system controller demonstrates high efficiency of proposed design procedure.

  2. 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......, (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...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

  3. 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...

  4. 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...

  5. Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

    Science.gov (United States)

    Wang, Xiuzhong; Srinivas, Chukka

    2016-03-01

    This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

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

    OpenAIRE

    Wu, Zhonghua; Lu, Jingchao; Shi, Jingping; Liu, Yang; Zhou, Qing

    2017-01-01

    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) tech...

  7. 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.

  8. Shape adaptive, robust iris feature extraction from noisy iris images.

    Science.gov (United States)

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

    2013-10-01

    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.

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

    NARCIS (Netherlands)

    Haasnoot, Marjolijn; Schellekens, J.; Beersma, J.; Middelkoop, H.; Kwadijk, Jacob Cornelis Jan

    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

  10. 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.

  11. Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems

    International Nuclear Information System (INIS)

    Chang Weider; Yan Junjuh

    2005-01-01

    A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p , K i , and K d , are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller

  12. Robust synchronization of chaotic systems via adaptive sliding mode control

    International Nuclear Information System (INIS)

    Yan, J.-J.; Hung, M.-L.; Chiang, T.-Y.; Yang, Y.-S.

    2006-01-01

    This Letter investigates the synchronization problem for a general class of chaotic systems. Using the sliding mode control technique, an adaptive control law is established to guarantee synchronization of the master and slave systems even when unknown parameters and external disturbances are present. In contrast to the previous works, the structure of slave system is simple and need not be identical to the master system. Furthermore, a novel proportional-integral (PI) switching surface is proposed to simplify the task of assigning the performance of the closed-loop error system in sliding mode. An illustrative example of Chua's circuit is given to demonstrate the effectiveness of the proposed synchronization scheme

  13. TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

    International Nuclear Information System (INIS)

    Boeck, M; Eriksson, K; Hardemark, B; Forsgren, A

    2016-01-01

    Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. 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 that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need

  14. 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.

  15. A methodology for adaptable and robust ecosystem services assessment.

    Directory of Open Access Journals (Sweden)

    Ferdinando Villa

    Full Text Available 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.

  16. 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.

  17. Robust controller with adaptation within the boundary layer: application to nuclear underwater inspection robot

    International Nuclear Information System (INIS)

    Park, Gee Yong; Yoon, Ji Sup; Hong, Dong Hee; Jeong, Jae Hoo

    2002-01-01

    In this paper, the robust control scheme with the improved control performance within the boundary layer is proposed. In the control scheme, the robust controller based on the traditional variable structure control method is modified to have the adaptation within the boundary layer. From this controller, the width of the boundary layer where the robust control input is smoothened out can be given by an appropriate value. But the improve control performance within the boundary layer can be achieved without the so-called control chattering because the role of adaptive control is to compensate for the uncovered portions of the robust control occurred from the continuous approximation within the boundary layer. Simulation tests for circular navigation of an underwater wall-ranging robot developed for inspection of wall surfaces in the research reactor, TRIGA MARK III, confirm the performance improvement

  18. 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.

  19. Robust

    DEFF Research Database (Denmark)

    2017-01-01

    Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...

  20. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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. (paper)

  2. Robust adaptive fuzzy neural tracking control for a class of unknown ...

    Indian Academy of Sciences (India)

    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 ...

  3. Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

    Science.gov (United States)

    Wang, Ding; Liu, Derong

    2018-06-01

    The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Data-adaptive Robust Optimization Method for the Economic Dispatch of Active Distribution Networks

    DEFF Research Database (Denmark)

    Zhang, Yipu; Ai, Xiaomeng; Fang, Jiakun

    2018-01-01

    Due to the restricted mathematical description of the uncertainty set, the current two-stage robust optimization is usually over-conservative which has drawn concerns from the power system operators. This paper proposes a novel data-adaptive robust optimization method for the economic dispatch...... of active distribution network with renewables. The scenario-generation method and the two-stage robust optimization are combined in the proposed method. To reduce the conservativeness, a few extreme scenarios selected from the historical data are used to replace the conventional uncertainty set....... The proposed extreme-scenario selection algorithm takes advantage of considering the correlations and can be adaptive to different historical data sets. A theoretical proof is given that the constraints will be satisfied under all the possible scenarios if they hold in the selected extreme scenarios, which...

  6. A delay-dependent approach to robust control for neutral uncertain neural networks with mixed interval time-varying delays

    International Nuclear Information System (INIS)

    Lu, Chien-Yu

    2011-01-01

    This paper considers the problem of delay-dependent global robust stabilization for discrete, distributed and neutral interval time-varying delayed neural networks described by nonlinear delay differential equations of the neutral type. The parameter uncertainties are norm bounded. The activation functions are assumed to be bounded and globally Lipschitz continuous. Using a Lyapunov functional approach and linear matrix inequality (LMI) techniques, the stability criteria for the uncertain neutral neural networks with interval time-varying delays are established in the form of LMIs, which can be readily verified using the standard numerical software. An important feature of the result reported is that all the stability conditions are dependent on the upper and lower bounds of the delays. Another feature of the results lies in that it involves fewer free weighting matrix strategy, and upper bounds of the inner product between two vectors are not introduced to reduce the conservatism of the criteria. Two illustrative examples are provided to demonstrate the effectiveness and the reduced conservatism of the proposed method

  7. Robust speech perception: Recognize the familiar, generalize to the similar, and adapt to the novel

    Science.gov (United States)

    Kleinschmidt, Dave F.; Jaeger, T. Florian

    2016-01-01

    Successful speech perception requires that listeners map the acoustic signal to linguistic categories. These mappings are not only probabilistic, but change depending on the situation. For example, one talker’s /p/ might be physically indistinguishable from another talker’s /b/ (cf. lack of invariance). We characterize the computational problem posed by such a subjectively non-stationary world and propose that the speech perception system overcomes this challenge by (1) recognizing previously encountered situations, (2) generalizing to other situations based on previous similar experience, and (3) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (1) to (3) can be understood as inference under uncertainty about the appropriate generative model for the current talker, thereby facilitating robust speech perception despite the lack of invariance. We focus on two critical aspects of the ideal adapter. First, in situations that clearly deviate from previous experience, listeners need to adapt. We develop a distributional (belief-updating) learning model of incremental adaptation. The model provides a good fit against known and novel phonetic adaptation data, including perceptual recalibration and selective adaptation. Second, robust speech recognition requires listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these two aspects of the ideal adapter provide a unifying explanation for adaptation, talker-specificity, and generalization across talkers and groups of talkers (e.g., accents and dialects). The ideal adapter provides a guiding framework for future investigations into speech perception and adaptation, and more broadly language comprehension. PMID:25844873

  8. 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.

  9. Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.

    Science.gov (United States)

    Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng

    2016-07-01

    In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.

  10. 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.

  11. Instantaneous Attitude Determination Based on Original Multi-antenna Observations Using Adaptively Robust Kalman Filtering

    Directory of Open Access Journals (Sweden)

    GAN Yu

    2015-09-01

    Full Text Available Attitude determination directly by carrier phase observation makes optimal use of observation and attitude constraints. The phase models based on misalignment angle and multiplicative quaternion error are derived. The state models for attitude estimation with and without external angular rate sensors are both erected. The attitude errors are estimated by adaptively robust filtering, in which the adaptive factors of ambiguity and attitude error are decided respectively following the idea of multi adaptive factor filtering. The factor of attitude is determined by a three-section function containing Ratio. Adaptively robust filtering makes the best use of constraint and historical information, fusing them in the calculation of float solution. As the accuracy of float solution and the structure of covariance matrix are improved greatly, the fix solution can be searched efficiently using LAMBDA (least-squares ambiguity decorrelation adjustment method merely, perfectly fulfilling the real-time requirement. Field test of a ship-based three-antenna attitude system is used to validate the proposed method. It is showed that direct attitude determination based on adaptively robust filtering has obvious advantages in efficiency and reliability.

  12. Robust synchronization of drive-response chaotic systems via adaptive sliding mode control

    International Nuclear Information System (INIS)

    Li, W.-L.; Chang, K.-M.

    2009-01-01

    A robust adaptive sliding control scheme is developed in this study to achieve synchronization for two identical chaotic systems in the presence of uncertain system parameters, external disturbances and nonlinear control inputs. An adaptation algorithm is given based on the Lyapunov stability theory. Using this adaptation technique to estimate the upper-bounds of parameter variation and external disturbance uncertainties, an adaptive sliding mode controller is then constructed without requiring the bounds of parameter and disturbance uncertainties to be known in advance. It is proven that the proposed adaptive sliding mode controller can maintain the existence of sliding mode in finite time in uncertain chaotic systems. Finally, numerical simulations are presented to show the effectiveness of the proposed control scheme.

  13. Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

    Science.gov (United States)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2017-04-01

    Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

  14. 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.

  15. 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...

  16. 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

    2017-12-01

    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 (SMART 3CM ) 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 (V 95% , D mean , D 1cc ) and institutional OAR constraints (e.g. V 33Gy ). SMART 3CM 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 V 95% =89%). Adaptive plans with SMART 3CM exhibited significant lower intermediate and high doses to all OARs than FULLOAR, which also failed in 36% of the cases to adhere to the V 33Gy dose constraint. SMART 3CM 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.

  17. 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.

  18. 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. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Pengchao Zhang

    2018-01-01

    Full Text Available This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV. It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.

  20. 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. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Synchronization and secure communication of chaotic systems via robust adaptive high-gain fuzzy observer

    International Nuclear Information System (INIS)

    Hyun, Chang-Ho; Park, Chang-Woo; Kim, Jae-Hun; Park, Mignon

    2009-01-01

    This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization and secure communication of chaotic systems. It is assumed that their states are immeasurable and their parameters are unknown. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. It improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived to estimate the unknown parameters and the stability of the proposed observer is analyzed. Some simulation result of synchronization and secure communication of chaotic systems is given to present the validity of theoretical derivations and the performance of the proposed observer as an application.

  2. 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. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    International Nuclear Information System (INIS)

    Yao, Jianyong; Jiao, Zongxia; Yao, Bin

    2014-01-01

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  4. Distributed robust adaptive control of high order nonlinear multi agent systems.

    Science.gov (United States)

    Hashemi, Mahnaz; Shahgholian, Ghazanfar

    2018-03-01

    In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Jianyong [Nanjing University of Science and Technology, Nanjing (China); Jiao, Zongxia [Beihang University, Beijing (China); Yao, Bin [Purdue University, West Lafayette (United States)

    2014-04-15

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  6. 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.

  7. 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.

  8. 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

    of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time-varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data-driven bandwidth selection......Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature...... 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...

  9. Robustness of critical points in a complex adaptive system: Effects of hedge behavior

    Science.gov (United States)

    Liang, Yuan; Huang, Ji-Ping

    2013-08-01

    In our recent papers, we have identified a class of phase transitions in the market-directed resource-allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system (with adaptive agents) may also be an intensive quantity, similar to those revealed in traditional physical systems (with non-adaptive units).

  10. Robust Longitudinal Aircraft- Control Based on an Adaptive Fuzzy-Logic Algorithm

    Directory of Open Access Journals (Sweden)

    Abdel- Latif Elshafei

    2002-06-01

    Full Text Available To study the aircraft response to a fast pull-up manoeuvre, a short period approximation of the longitudinal model is considered. The model is highly nonlinear and includes parametric uncertainties. To cope with a wide range of command signals, a robust adaptive fuzzy logic controller is proposed. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, robustifying and adaptive components are included in the control law to compensate for modeling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearity. The second system is an adaptive one that compensates for modeling errors. The derivation of the control law based on a dynamic game approach is given in detail. Stability of the closed-loop control system is also verified. Simulation results based on an F16-model illustrate a successful tracking performance of the proposed controller.

  11. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Directory of Open Access Journals (Sweden)

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  12. Interval for the expression of the adaptive response induced by gamma radiation in leucocytes of mouse In vivo

    International Nuclear Information System (INIS)

    Mendiola C, M.T.; Morales R, P.

    2002-01-01

    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)

  13. 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.

  14. Robust Unit Commitment Considering the Temporal and Spatial Correlations of Wind Farms Using a Data-Adaptive Approach

    DEFF Research Database (Denmark)

    Zhang, Yipu; Ai, Xiaomeng; Wen, Jinyu

    2018-01-01

    . In this paper, a novel data-adaptive robust optimization method for the unit commitment is proposed for the power system with wind farms integrated. The extreme scenario extraction and the two stage robust optimization are combined in the proposed method. The data-adaptive set consisting of a few extreme...... scenarios is derived to reduce the conservativeness by considering the temporal and spatial correlations of multiple wind farms. Numerical results demonstrate that the proposed data-adaptive robust optimization algorithm is less conservative than the current two-stage optimization approaches while maintains...

  15. A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.

    Science.gov (United States)

    Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing

    2018-03-07

    The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.

  16. Adaptive Robust Motion Control of Direct-Drive DC Motors with Continuous Friction Compensation

    Directory of Open Access Journals (Sweden)

    Jianyong Yao

    2013-01-01

    Full Text Available Uncertainties including the structured and unstructured, especially the nonlinear frictions, always exist in physical servo systems and degrade their tracking accuracy. In this paper, a practical method named adaptive robust controller (ARC is synthesized with a continuous differentiable friction model for high accuracy motion control of a direct-drive dc motor, which results in a continuous control input and thus is more suitable for application. To further reduce the noise sensitivity and improve the tracking accuracy, a desired compensation version of the proposed adaptive robust controller is also developed and its stability is guaranteed by a proper robust law. The proposed controllers not only account for the structured uncertainties (e.g., parametric uncertainties but also for the unstructured uncertainties (e.g., unconsidered nonlinear frictions. Furthermore, the controllers theoretically guarantee a prescribed output tracking transient performance and final tracking accuracy in both structured and unstructured uncertainties while achieving asymptotic output tracking in the absence of unstructured uncertainties, which is very important for high accuracy control of motion systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategies.

  17. Robust stator resistance identification of an IM drive using model reference adaptive system

    International Nuclear Information System (INIS)

    Madadi Kojabadi, Hossein; Abarzadeh, Mostafa; Aghaei Farouji, Said

    2013-01-01

    Highlights: ► We estimate the stator resistance and rotor speed of the IM. ► We proposed a new quantity to estimate the speed and stator resistance of IM. ► The proposed algorithm is robust to rotor resistance variations. ► We estimate the IM speed and stator resistance simultaneously to avoid speed error. - Abstract: Model reference adaptive system (MRAS) based robust stator resistance estimator for sensorless induction motor (IM) drive is proposed. The MRAS is formed with a semi-active power quantity. The proposed identification method can be achieved with on-line tuning of the stator resistance with robustness against rotor resistance variations. Stable and efficient estimation of IM speed at low region will be guaranteed by simultaneous identification of IM speed and stator resistance. The stability of proposed stator resistance estimator is checked through Popov’s hyperstability theorem. Simulation and experimental results are given to highlight the feasibility, the simplicity, and the robustness of the proposed method.

  18. Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

    Science.gov (United States)

    Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

    2017-12-01

    Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

  19. 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.

  20. Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

    Science.gov (United States)

    Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

    2007-12-01

    We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

  1. Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

    Directory of Open Access Journals (Sweden)

    Yang Jian

    2007-01-01

    Full Text Available We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

  2. 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.

  3. Robust synchronization of delayed neural networks based on adaptive control and parameters identification

    International Nuclear Information System (INIS)

    Zhou Jin; Chen Tianping; Xiang Lan

    2006-01-01

    This paper investigates synchronization dynamics of delayed neural networks with all the parameters unknown. By combining the adaptive control and linear feedback with the updated law, some simple yet generic criteria for determining the robust synchronization based on the parameters identification of uncertain chaotic delayed neural networks are derived by using the invariance principle of functional differential equations. It is shown that the approaches developed here further extend the ideas and techniques presented in recent literature, and they are also simple to implement in practice. Furthermore, the theoretical results are applied to a typical chaotic delayed Hopfied neural networks, and numerical simulation also demonstrate the effectiveness and feasibility of the proposed technique

  4. Sex Comparison of Knee Extensor Size, Strength and Fatigue Adaptation to Sprint Interval Training.

    Science.gov (United States)

    Bagley, Liam; Al-Shanti, Nasser; Bradburn, Steven; Baig, Osamah; Slevin, Mark; McPhee, Jamie S

    2018-03-12

    Regular sprint interval training (SIT) improves whole-body aerobic capacity and muscle oxidative potential, but very little is known about knee extensor anabolic or fatigue resistance adaptations, or whether effects are similar for males and females. The purpose of this study was to compare sex-related differences in knee extensor size, torque-velocity relationship and fatigability adaptations to 12 weeks SIT. Sixteen males and fifteen females (mean (SEM) age: 41 (±2.5) yrs) completed measurements of total body composition assessed by DXA, quadriceps muscle cross-sectional area (CSAQ) assessed by MRI, the knee extensor torque-velocity relationship (covering 0 - 240°·sec) and fatigue resistance, which was measured as the decline in torque from the first to the last of 60 repeated concentric knee extensions performed at 180°·sec. SIT consisted of 4 x 20 second sprints on a cycle ergometer set at an initial power output of 175% of power at VO2max, three times per week for 12 weeks. CSAQ increased by 5% (p=0.023) and fatigue resistance improved 4.8% (p=0.048), with no sex differences in these adaptations (sex comparisons: p=0.140 and p=0.282, respectively). Knee extensor isometric and concentric torque was unaffected by SIT in both males and females (p>0.05 for all velocities). 12 weeks SIT, totalling 4 minutes very intense cycling per week, significantly increased fatigue resistance and CSAQ similarly in males and females, but did not significantly increase torque in males or females. These results suggest that SIT is a time-effective training modality for males and females to increase leg muscle size and fatigue resistance.

  5. Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

    Directory of Open Access Journals (Sweden)

    Pau G

    2006-01-01

    Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

  6. 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.

  7. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

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    Haimin Yang

    2017-01-01

    Full Text Available Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam, for long short-term memory (LSTM to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

  8. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

    Science.gov (United States)

    Yang, Haimin; Pan, Zhisong; Tao, Qing

    2017-01-01

    Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

  9. Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

    Science.gov (United States)

    Piatrou, Piotr; Gilles, Luc

    2005-02-20

    Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

  10. Active Recovery After High-Intensity Interval-Training Does Not Attenuate Training Adaptation

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    Thimo Wiewelhove

    2018-04-01

    Full Text Available Objective: High-intensity interval training (HIIT can be extremely demanding and can consequently produce high blood lactate levels. Previous studies have shown that lactate is a potent metabolic stimulus, which is important for adaptation. Active recovery (ACT after intensive exercise, however, enhances blood lactate removal in comparison with passive recovery (PAS and, consequently, may attenuate endurance performance improvements. Therefore, the aim of this study was to examine the influence of regular ACT on training adaptations during a HIIT mesocycle.Methods: Twenty-six well-trained male intermittent sport athletes (age: 23.5 ± 2.5 years; O2max: 55.36 ± 3.69 ml min kg-1 participated in a randomized controlled trial consisting of 4 weeks of a running-based HIIT mesocycle with a total of 12 HIIT sessions. After each training session, participants completed 15 min of either moderate jogging (ACT or PAS. Subjects were matched to the ACT or PAS groups according to age and performance. Before the HIIT program and 1 week after the last training session, the athletes performed a progressive incremental exercise test on a motor-driven treadmill to determine O2max, maximum running velocity (vmax, the running velocity at which O2max occurs (vO2max, and anaerobic lactate threshold (AT. Furthermore, repeated sprint ability (RSA were determined.Results: In the whole group the HIIT mesocycle induced significant or small to moderate changes in vmax (p < 0.001, effect size [ES] = 0.65,, vO2max (p < 0.001, ES = 0.62, and AT (p < 0.001, ES = 0.56 compared with the values before the intervention. O2max and RSA remained unchanged throughout the study. In addition, no significant differences in the changes were noted in any of the parameters between ACT and PAS except for AT (p < 0.05, ES = 0.57.Conclusion: Regular use of individualized ACT did not attenuate training adaptations during a HIIT mesocycle compared to PAS. Interestingly, we found that the ACT

  11. Adaptive Changes After 2 Weeks of 10-s Sprint Interval Training With Various Recovery Times

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    Robert A. Olek

    2018-04-01

    Full Text Available Purpose: The aim of this study was to compare the effect of applying two different rest recovery times in a 10-s sprint interval training session on aerobic and anaerobic capacities as well as skeletal muscle enzyme activities.Methods: Fourteen physically active but not highly trained male subjects (mean maximal oxygen uptake 50.5 ± 1.0 mlO2·kg−1·min−1 participated in the study. The training protocol involved a series of 10-s sprints separated by either 1-min (SIT10:1 or 4-min (SIT10:4 of recovery. The number of sprints progressed from four to six over six sessions separated by 1–2 days rest. Pre and post intervention anthropometric measurements, assessment of aerobic, anaerobic capacity and muscle biopsy were performed. In the muscle samples maximal activities of citrate synthase (CS, 3-hydroxyacylCoA dehydrogenase (HADH, carnitine palmitoyl-transferase (CPT, malate dehydrogenase (MDH, and its mitochondrial form (mMDH, as well as lactate dehydrogenase (LDH were determined. Analysis of variance was performed to determine changes between conditions.Results: Maximal oxygen uptake improved significantly in both training groups, by 13.6% in SIT10:1 and 11.9% in SIT10:4, with no difference between groups. Wingate anaerobic test results indicated main effect of time for total work, peak power output and mean power output, which increased significantly and similarly in both groups. Significant differences between training groups were observed for end power output, which increased by 10.8% in SIT10:1, but remained unchanged in SIT10:4. Both training protocols induced similar increase in CS activity (main effect of time p < 0.05, but no other enzymes.Conclusion: Sprint interval training protocols induce metabolic adaptation over a short period of time, and the reduced recovery between bouts may attenuate fatigue during maximal exercise.

  12. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

    Science.gov (United States)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

    2011-12-01

    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  13. 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.

  14. 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.

  15. Robust adaptive multivariable higher-order sliding mode flight control for air-breathing hypersonic vehicle with actuator failures

    Directory of Open Access Journals (Sweden)

    Peng Li

    2016-10-01

    Full Text Available This article proposes an adaptive multivariable higher-order sliding mode control for the longitudinal model of an air-breathing vehicle under system uncertainties and actuator failures. Firstly, a fast finite-time control law is designed for a chain of integrators. Secondly, based on the input/output feedback linearization technique, the system uncertainty and external disturbances are modeled as additive certainty and the actuator failures are modeled as multiplicative uncertainty. By using the proposed fast finite-time control law, a robust multivariable higher-order sliding mode control is designed for the air-breathing hypersonic vehicle with actuator failures. Finally, adaptive laws are proposed for the adaptation of the parameters in the robust multivariable higher-order sliding mode control. Thus, the bounds of the uncertainties are not needed in the control system design. Simulation results show the effectiveness of the proposed robust adaptive multivariable higher-order sliding mode control.

  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. Image-adaptive and robust digital wavelet-domain watermarking for images

    Science.gov (United States)

    Zhao, Yi; Zhang, Liping

    2018-03-01

    We propose a new frequency domain wavelet based watermarking technique. The key idea of our scheme is twofold: multi-tier solution representation of image and odd-even quantization embedding/extracting watermark. Because many complementary watermarks need to be hidden, the watermark image designed is image-adaptive. The meaningful and complementary watermark images was embedded into the original image (host image) by odd-even quantization modifying coefficients, which was selected from the detail wavelet coefficients of the original image, if their magnitudes are larger than their corresponding Just Noticeable Difference thresholds. The tests show good robustness against best-known attacks such as noise addition, image compression, median filtering, clipping as well as geometric transforms. Further research may improve the performance by refining JND thresholds.

  18. 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...

  19. Robust Ordering of Anaphase Events by Adaptive Thresholds and Competing Degradation Pathways.

    Science.gov (United States)

    Kamenz, Julia; Mihaljev, Tamara; Kubis, Armin; Legewie, Stefan; Hauf, Silke

    2015-11-05

    The splitting of chromosomes in anaphase and their delivery into the daughter cells needs to be accurately executed to maintain genome stability. Chromosome splitting requires the degradation of securin, whereas the distribution of the chromosomes into the daughter cells requires the degradation of cyclin B. We show that cells encounter and tolerate variations in the abundance of securin or cyclin B. This makes the concurrent onset of securin and cyclin B degradation insufficient to guarantee that early anaphase events occur in the correct order. We uncover that the timing of chromosome splitting is not determined by reaching a fixed securin level, but that this level adapts to the securin degradation kinetics. In conjunction with securin and cyclin B competing for degradation during anaphase, this provides robustness to the temporal order of anaphase events. Our work reveals how parallel cell-cycle pathways can be temporally coordinated despite variability in protein concentrations. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. 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.

  1. Feasibility of online IMPT adaptation using fast, automatic and robust dose restoration

    Science.gov (United States)

    Bernatowicz, Kinga; Geets, Xavier; Barragan, Ana; Janssens, Guillaume; Souris, Kevin; Sterpin, Edmond

    2018-04-01

    Intensity-modulated proton therapy (IMPT) offers excellent dose conformity and healthy tissue sparing, but it can be substantially compromised in the presence of anatomical changes. A major dosimetric effect is caused by density changes, which alter the planned proton range in the patient. Three different methods, which automatically restore an IMPT plan dose on a daily CT image were implemented and compared: (1) simple dose restoration (DR) using optimization objectives of the initial plan, (2) voxel-wise dose restoration (vDR), and (3) isodose volume dose restoration (iDR). Dose restorations were calculated for three different clinical cases, selected to test different capabilities of the restoration methods: large range adaptation, complex dose distributions and robust re-optimization. All dose restorations were obtained in less than 5 min, without manual adjustments of the optimization settings. The evaluation of initial plans on repeated CTs showed large dose distortions, which were substantially reduced after restoration. In general, all dose restoration methods improved DVH-based scores in propagated target volumes and OARs. Analysis of local dose differences showed that, although all dose restorations performed similarly in high dose regions, iDR restored the initial dose with higher precision and accuracy in the whole patient anatomy. Median dose errors decreased from 13.55 Gy in distorted plan to 9.75 Gy (vDR), 6.2 Gy (DR) and 4.3 Gy (iDR). High quality dose restoration is essential to minimize or eventually by-pass the physician approval of the restored plan, as long as dose stability can be assumed. Motion (as well as setup and range uncertainties) can be taken into account by including robust optimization in the dose restoration. Restoring clinically-approved dose distribution on repeated CTs does not require new ROI segmentation and is compatible with an online adaptive workflow.

  2. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    Science.gov (United States)

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.

  3. 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

  4. Robust Adaptive Stabilization of Linear Time-Invariant Dynamic Systems by Using Fractional-Order Holds and Multirate Sampling Controls

    Directory of Open Access Journals (Sweden)

    S. Alonso-Quesada

    2010-01-01

    Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.

  5. Adaptive nonlinear robust relative pose control of spacecraft autonomous rendezvous and proximity operations.

    Science.gov (United States)

    Sun, Liang; Huo, Wei; Jiao, Zongxia

    2017-03-01

    This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

    Directory of Open Access Journals (Sweden)

    Dongming Li

    2017-04-01

    Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

  7. Robust adaptive control for a hybrid solid oxide fuel cell system

    Science.gov (United States)

    Snyder, Steven

    2011-12-01

    Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.

  8. Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

    Science.gov (United States)

    Zhang, Lei; Zhang, David

    2016-08-10

    We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

  9. 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.

  10. Practical Considerations about Expected A Posteriori Estimation in Adaptive Testing: Adaptive A Priori, Adaptive Correction for Bias, and Adaptive Integration Interval.

    Science.gov (United States)

    Raiche, Gilles; Blais, Jean-Guy

    In a computerized adaptive test (CAT), it would be desirable to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Decreasing the number of items is accompanied, however, by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. G. Raiche (2000) has…

  11. 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.

  12. 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)

  13. 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.

  14. 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...

  15. Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.

    Science.gov (United States)

    Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin

    2015-06-01

    We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.

  16. 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.

  17. 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.

  18. 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.

  19. Adaptive tuning of a 2DOF controller for robust cell manipulation using IPMC actuators

    International Nuclear Information System (INIS)

    McDaid, A J; Aw, K C; Haemmerle, E; Xie, S Q; Shahinpoor, M

    2011-01-01

    Rapid advancement in medicine and bioscience is causing demand for faster, more accurate and dexterous as well as safer and more reliable micro-manipulators capable of handling biological cells. Current micro-manipulation techniques commonly damage cell walls and membranes due to their stiffness and rigidity. Ionic polymer-metal composite (IPMC) actuators have inherent compliance and with their ability to operate well in fluid and cellular environments they present a unique solution for safe cell manipulation. The reason for the downfall of IPMCs is that their complex behaviour makes them hard to control precisely in unknown environments and in the presence of sizeable external disturbances. This paper presents a novel scheme for adaptively tuning IPMC actuators for precise and robust micro-manipulation of biological cells. A two-degree-of-freedom (2DOF) controller is developed to allow optimal performance for both disturbance rejection (DR) and set point (SP) tracking. These criteria are optimized using a proposed IFT algorithm which adaptively updates the controller parameters, with no model or prior knowledge of the operating conditions, to achieve a compliant manipulation system which can precisely track targets in the presence of large external disturbances, as will be encountered in real biological environments. Experiments are presented showing the performance optimization of an IPMC actuator in the presence of external mechanical disturbances as well as the optimization of the SP tracking. The IFT algorithm successfully tunes the DR and SP to an 85% and 69% improvement, respectively. Results are also presented for a one-degree-of-freedom (1DOF) controller tuned first for DR and then for SP, for a comparison with the 2DOF controller. Validation has been undertaken to verify that the 2DOF controller does indeed outperform both 1DOF controllers over a variety of operating conditions.

  20. Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

    Science.gov (United States)

    Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

    2012-03-01

    Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

  1. Using adaptive processes and adverse outcome pathways to develop meaningful, robust, and actionable environmental monitoring programs.

    Science.gov (United States)

    Arciszewski, Tim J; Munkittrick, Kelly R; Scrimgeour, Garry J; Dubé, Monique G; Wrona, Fred J; Hazewinkel, Rod R

    2017-09-01

    The primary goals of environmental monitoring are to indicate whether unexpected changes related to development are occurring in the physical, chemical, and biological attributes of ecosystems and to inform meaningful management intervention. Although achieving these objectives is conceptually simple, varying scientific and social challenges often result in their breakdown. Conceptualizing, designing, and operating programs that better delineate monitoring, management, and risk assessment processes supported by hypothesis-driven approaches, strong inference, and adverse outcome pathways can overcome many of the challenges. Generally, a robust monitoring program is characterized by hypothesis-driven questions associated with potential adverse outcomes and feedback loops informed by data. Specifically, key and basic features are predictions of future observations (triggers) and mechanisms to respond to success or failure of those predictions (tiers). The adaptive processes accelerate or decelerate the effort to highlight and overcome ignorance while preventing the potentially unnecessary escalation of unguided monitoring and management. The deployment of the mutually reinforcing components can allow for more meaningful and actionable monitoring programs that better associate activities with consequences. Integr Environ Assess Manag 2017;13:877-891. © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

  2. Region of interest based robust watermarking scheme for adaptation in small displays

    Science.gov (United States)

    Vivekanandhan, Sapthagirivasan; K. B., Kishore Mohan; Vemula, Krishna Manohar

    2010-02-01

    Now-a-days Multimedia data can be easily replicated and the copyright is not legally protected. Cryptography does not allow the use of digital data in its original form and once the data is decrypted, it is no longer protected. Here we have proposed a new double protected digital image watermarking algorithm, which can embed the watermark image blocks into the adjacent regions of the host image itself based on their blocks similarity coefficient which is robust to various noise effects like Poisson noise, Gaussian noise, Random noise and thereby provide double security from various noises and hackers. As instrumentation application requires a much accurate data, the watermark image which is to be extracted back from the watermarked image must be immune to various noise effects. Our results provide better extracted image compared to the present/existing techniques and in addition we have done resizing the same for various displays. Adaptive resizing for various size displays is being experimented wherein we crop the required information in a frame, zoom it for a large display or resize for a small display using a threshold value and in either cases background is not given much importance but it is only the fore-sight object which gains importance which will surely be helpful in performing surgeries.

  3. 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.

  4. 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.

  5. 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.

  6. Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

    Science.gov (United States)

    Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

    2018-05-08

    When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

  7. Robustness and management adaptability in tropical rangelands: a viability-based assessment under the non-equilibrium paradigm.

    Science.gov (United States)

    Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M

    2014-08-01

    Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

  8. A Multi-Pathfinder for Developing Adaptive Robust Policies in System Dynamics

    NARCIS (Netherlands)

    Hamarat, C.; Pruyt, E.; Loonen, E.T.

    2013-01-01

    Adaptivity is essential for dynamically complex and uncertain systems. Adaptive policymaking is an approach to design policies that can be adapted over time to how the future unfolds. It is crucial for adaptive policymaking to specify under what conditions and how to adapt the policy. The

  9. 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

  10. Odor-context effects in free recall after a short retention interval: a new methodology for controlling adaptation.

    Science.gov (United States)

    Isarida, Takeo; Sakai, Tetsuya; Kubota, Takayuki; Koga, Miho; Katayama, Yu; Isarida, Toshiko K

    2014-04-01

    The present study investigated context effects of incidental odors in free recall after a short retention interval (5 min). With a short retention interval, the results are not confounded by extraneous odors or encounters with the experimental odor and possible rehearsal during a long retention interval. A short study time condition (4 s per item), predicted not to be affected by adaptation to the odor, and a long study time condition (8 s per item) were used. Additionally, we introduced a new method for recovery from adaptation, where a dissimilar odor was briefly presented at the beginning of the retention interval, and we demonstrated the effectiveness of this technique. An incidental learning paradigm was used to prevent overshadowing from confounding the results. In three experiments, undergraduates (N = 200) incidentally studied words presented one-by-one and received a free recall test. Two pairs of odors and a third odor having different semantic-differential characteristics were selected from 14 familiar odors. One of the odors was presented during encoding, and during the test, the same odor (same-context condition) or the other odor within the pair (different-context condition) was presented. Without using a recovery-from-adaptation method, a significant odor-context effect appeared in the 4-s/item condition, but not in the 8-s/item condition. Using the recovery-from-adaptation method, context effects were found for both the 8- and the 4-s/item conditions. The size of the recovered odor-context effect did not change with study time. There were no serial position effects. Implications of the present findings are discussed.

  11. QT Interval Adaption to RR Interval Changes and Correlation Analysis between Heart Rate Variability and QT Interval Variability%QT间期对RR间期变化的响应及HRV与QTV的关联性分析

    Institute of Scientific and Technical Information of China (English)

    朱逸; 杨啸林; 彭屹

    2013-01-01

    体表心电图作为无创和连续的监测手段,在心脏安全评测方面具有重要而不可替代的位置.心电图中的间期时间序列包含着重要信息,其中以反映心动周期的RR间期序列,以及以QT间期为代表的反映心室复极化时程的间期序列,在临床上最为基础,相关的研究具有更为重要的意义.文中从应用基础研究的角度,就QT间期对于RR间期变化的响应,以及心率变异性(HRV)和QT间期变异性(QTV)关联性分析,分别介绍了其分析方法和研究进展,并且展望了可能的应用前景.%As a noninvasive and continuous monitoring method, surface electrocardiogram is significant in evaluating cardiac safety. The time interval series extracted from surface electrocardiogran contain important information. The RR and QT interval series, representing the cardiac cycle and the duration of ventricular repolarization, are with more research value. From the perspective of applied basic research, the methods and progress, concerning the QT interval adaption to RR interval changes and correlation analysis between heart rale variability (HRV) and QT interval variability (QTV) , were introduced here. And their potential applications were discussed as well.

  12. Hunter-gatherer postcranial robusticity relative to patterns of mobility, climatic adaptation, and selection for tissue economy.

    Science.gov (United States)

    Stock, J T

    2006-10-01

    Human skeletal robusticity is influenced by a number of factors, including habitual behavior, climate, and physique. Conflicting evidence as to the relative importance of these factors complicates our ability to interpret variation in robusticity in the past. It remains unclear how the pattern of robusticity in the skeleton relates to adaptive constraints on skeletal morphology. This study investigates variation in robusticity in claviculae, humeri, ulnae, femora, and tibiae among human foragers, relative to climate and habitual behavior. Cross-sectional geometric properties of the diaphyses are compared among hunter-gatherers from southern Africa (n = 83), the Andaman Islands (n = 32), Tierra del Fuego (n = 34), and the Great Lakes region (n = 15). The robusticity of both proximal and distal limb segments correlates negatively with climate and positively with patterns of terrestrial and marine mobility among these groups. However, the relative correspondence between robusticity and these factors varies throughout the body. In the lower limb, partial correlations between polar second moment of area (J(0.73)) and climate decrease from proximal to distal section locations, while this relationship increases from proximal to distal in the upper limb. Patterns of correlation between robusticity and mobility, either terrestrial or marine, generally increase from proximal to distal in the lower and upper limbs, respectively. This suggests that there may be a stronger relationship between observed patterns of diaphyseal hypertrophy and behavioral differences between populations in distal elements. Despite this trend, strength circularity indices at the femoral midshaft show the strongest correspondence with terrestrial mobility, particularly among males.

  13. Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

    Science.gov (United States)

    Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

    2017-10-01

    Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

  14. Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

    Science.gov (United States)

    Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

    2014-11-01

    This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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. (paper)

  16. 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

  17. 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

  18. A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

    Science.gov (United States)

    Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

    This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

  19. 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.

  20. Nonlinear model-based robust control of a nuclear reactor using adaptive PIF gains and variable structure controller

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Cho, Nam Zin

    1993-01-01

    A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods. (Author)

  1. Adaptive Space-Time, Processing for High Performance, Robust Military Wireless Communications

    National Research Council Canada - National Science Library

    Haimovich, Alexander

    2000-01-01

    ...: (I) performance of adaptive arrays for wireless communications over fading channels in the presence of cochannel interference particularly the case when the number of interference sources exceeds...

  2. 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

  3. Implementation of robust adaptive control for robotic manipulator using TMS320C30

    International Nuclear Information System (INIS)

    Han, S. H.

    1996-01-01

    A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the adaptive feedforward and feedback controller and PI type time-varying control elements. The control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot. (author)

  4. Robust and adaptive band-to-band image transform of UAS miniature multi-lens multispectral camera

    Science.gov (United States)

    Jhan, Jyun-Ping; Rau, Jiann-Yeou; Haala, Norbert

    2018-03-01

    Utilizing miniature multispectral (MS) or hyperspectral (HS) cameras by mounting them on an Unmanned Aerial System (UAS) has the benefits of convenience and flexibility to collect remote sensing imagery for precision agriculture, vegetation monitoring, and environment investigation applications. Most miniature MS cameras adopt a multi-lens structure to record discrete MS bands of visible and invisible information. The differences in lens distortion, mounting positions, and viewing angles among lenses mean that the acquired original MS images have significant band misregistration errors. We have developed a Robust and Adaptive Band-to-Band Image Transform (RABBIT) method for dealing with the band co-registration of various types of miniature multi-lens multispectral cameras (Mini-MSCs) to obtain band co-registered MS imagery for remote sensing applications. The RABBIT utilizes modified projective transformation (MPT) to transfer the multiple image geometry of a multi-lens imaging system to one sensor geometry, and combines this with a robust and adaptive correction (RAC) procedure to correct several systematic errors and to obtain sub-pixel accuracy. This study applies three state-of-the-art Mini-MSCs to evaluate the RABBIT method's performance, specifically the Tetracam Miniature Multiple Camera Array (MiniMCA), Micasense RedEdge, and Parrot Sequoia. Six MS datasets acquired at different target distances and dates, and locations are also applied to prove its reliability and applicability. Results prove that RABBIT is feasible for different types of Mini-MSCs with accurate, robust, and rapid image processing efficiency.

  5. An adaptive robust optimization scheme for water-flooding optimization in oil reservoirs using residual analysis

    NARCIS (Netherlands)

    Siraj, M.M.; Van den Hof, P.M.J.; Jansen, J.D.

    2017-01-01

    Model-based dynamic optimization of the water-flooding process in oil reservoirs is a computationally complex problem and suffers from high levels of uncertainty. A traditional way of quantifying uncertainty in robust water-flooding optimization is by considering an ensemble of uncertain model

  6. Engineering of Fast and Robust Adaptive Control for Fixed-Wing Unmanned Aircraft

    Science.gov (United States)

    2017-06-01

    evaluate the use of adaptive control on fixed-wing unmanned aircraft . The growing demand for unmanned systems will inherit the costs associated with...aerospace environment . 2.2 Classical Feedback vs Adaptive Control Control of a system can be categorized into two required elements; the requirement to...stabilize the system in the presence of: 1. disturbances that affect the controlled states and outputs (pitch rate perturbation caused by environmental

  7. SU-F-BRB-07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online-Adaptive Radiotherapy

    International Nuclear Information System (INIS)

    Hill, P; Labby, Z; Bayliss, R A; Geurts, M; Bayouth, J

    2015-01-01

    Purpose: To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online-adaptive radiotherapy plans using similarity metrics. Methods: The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam-on time), the tool computes and presents histograms of derived metrics (e.g. step-and-shoot segment field sizes, segment average leaf gaps). Such metrics were investigated for their ability to predict that an online-adapted plan reasonably similar to a baseline plan where deliverability has already been established. Results: In the realm of online-adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re-optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online-adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements. Conclusion: The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online-adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to

  8. 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

    2017-11-01

    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 ISA. Published by Elsevier Ltd. All rights reserved.

  9. 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.

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

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, Ibrahim

    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 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.

  12. Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

    Science.gov (United States)

    Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

    2018-04-01

    In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

  13. Fast, accurate, and robust frequency offset estimation based on modified adaptive Kalman filter in coherent optical communication system

    Science.gov (United States)

    Yang, Yanfu; Xiang, Qian; Zhang, Qun; Zhou, Zhongqing; Jiang, Wen; He, Qianwen; Yao, Yong

    2017-09-01

    We propose a joint estimation scheme for fast, accurate, and robust frequency offset (FO) estimation along with phase estimation based on modified adaptive Kalman filter (MAKF). The scheme consists of three key modules: extend Kalman filter (EKF), lock detector, and FO cycle slip recovery. The EKF module estimates time-varying phase induced by both FO and laser phase noise. The lock detector module makes decision between acquisition mode and tracking mode and consequently sets the EKF tuning parameter in an adaptive manner. The third module can detect possible cycle slip in the case of large FO and make proper correction. Based on the simulation and experimental results, the proposed MAKF has shown excellent estimation performance featuring high accuracy, fast convergence, as well as the capability of cycle slip recovery.

  14. 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.

  15. 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...

  16. Robust model predictive cooperative adaptive cruise control subject to V2V impairments

    NARCIS (Netherlands)

    Van Nunen, Ellen; Verhaegh, Jan; Silvas, Emilia; Semsar-Kazerooni, Elham; Van De Wouw, Nathan

    2018-01-01

    To improve traffic throughput, Cooperative Adaptive Cruise Control (CACC) has been proposed as a solution. The usage of Vehicle-to-Vehicle (V2V) communication enables short following distances, thereby increasing road capacity and fuel reduction (especially for trucks). Control designs for CACC use

  17. Synchronization dynamics in a small pacemaker neuronal ensemble via a robust adaptive controller

    International Nuclear Information System (INIS)

    Cornejo-Pérez, O.; Solis-Perales, G.C.; Arenas-Prado, J.A.

    2012-01-01

    The synchronization dynamics of a pacemaker neuronal ensemble under the action of a control command is studied herein. The ensemble corresponds to the pyloric central pattern generator of the stomatogastric ganglion of lobster. The desired dynamics is provided by means of an external master neuron and it is induced via a nonlinear controller. Such a controller is composed of a linearizing-like controller and a high gain observer; the controller is able to counteract uncertainties and external perturbations in the controlled system. Numerical simulations of the robust synchronization dynamics of the master neuron and the pacemaker neuronal ensemble are displayed.

  18. Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

    Directory of Open Access Journals (Sweden)

    Muhammad Iqbal

    2018-02-01

    Full Text Available This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided.

  19. Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

    Science.gov (United States)

    Iqbal, Muhammad; Rehan, Muhammad; Hong, Keum-Shik

    2018-01-01

    This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN) neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided. PMID:29535622

  20. Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

    Science.gov (United States)

    Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

    2009-10-01

    A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.

  1. Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses

    Science.gov (United States)

    Patel, Gauravkumar K.; Hahne, Janne M.; Castellini, Claudio; Farina, Dario; Dosen, Strahinja

    2017-10-01

    Objective. Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. Approach. We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control. Further, a realistic evaluation of the cxMYO was performed online in able-bodied subjects using three functional tasks, during which the cxMYO was compared to a purely machine-learning-based myoelectric control (MYO). Main results. The results demonstrated that utilizing context information decreased the number of unwanted commands, improving the performance (success rate and dropped objects) in all three functional tasks. Specifically, the median number of objects dropped per round with cxMYO was zero in all three tasks and a significant increase in the number of successful transfers was seen in two out of three functional tasks. Additionally, the subjects reported better user experience. Significance. This is the first online evaluation of a method integrating information from multiple on-board prosthesis sensors to modulate the output of a machine-learning-based myoelectric controller. The proposed scheme is general and presents a simple, non-invasive and cost-effective approach for improving the robustness of myoelectric control.

  2. 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.

  3. Robust Adaptation? Assessing the sensitivity of safety margins in flood defences to uncertainty in future simulations - a case study from Ireland.

    Science.gov (United States)

    Murphy, Conor; Bastola, Satish; Sweeney, John

    2013-04-01

    Climate change impact and adaptation assessments have traditionally adopted a 'top-down' scenario based approach, where information from different Global Climate Models (GCMs) and emission scenarios are employed to develop impacts led adaptation strategies. Due to the tradeoffs in the computational cost and need to include a wide range of GCMs for fuller characterization of uncertainties, scenarios are better used for sensitivity testing and adaptation options appraisal. One common approach to adaptation that has been defined as robust is the use of safety margins. In this work the sensitivity of safety margins that have been adopted by the agency responsible for flood risk management in Ireland, to the uncertainty in future projections are examined. The sensitivity of fluvial flood risk to climate change is assessed for four Irish catchments using a large number of GCMs (17) forced with three emissions scenarios (SRES A1B, A2, B1) as input to four hydrological models. Both uncertainty within and between hydrological models is assessed using the GLUE framework. Regionalisation is achieved using a change factor method to infer changes in the parameters of a weather generator using monthly output from the GCMs, while flood frequency analysis is conducted using the method of probability weighted moments to fit the Generalised Extreme Value distribution to ~20,000 annual maxima series. The sensitivity of design margins to the uncertainty space considered is visualised using risk response surfaces. The hydrological sensitivity is measured as the percentage change in flood peak for specified recurrence intervals. Results indicate that there is a considerable residual risk associated with allowances of +20% when uncertainties are accounted for and that the risk of exceedence of design allowances is greatest for more extreme, low frequency events with considerable implication for critical infrastructure, e.g., culverts, bridges, flood defences whose designs are normally

  4. 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

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

    Directory of Open Access Journals (Sweden)

    Bloch Isabelle

    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 Transmission of H.264/AVC Streams Using Adaptive Group Slicing and Unequal Error Protection

    Science.gov (United States)

    Thomos, Nikolaos; Argyropoulos, Savvas; Boulgouris, Nikolaos V.; Strintzis, Michael G.

    2006-12-01

    We present a novel scheme for the transmission of H.264/AVC video streams over lossy packet networks. The proposed scheme exploits the error-resilient features of H.264/AVC codec and employs Reed-Solomon codes to protect effectively the streams. A novel technique for adaptive classification of macroblocks into three slice groups is also proposed. The optimal classification of macroblocks and the optimal channel rate allocation are achieved by iterating two interdependent steps. Dynamic programming techniques are used for the channel rate allocation process in order to reduce complexity. Simulations clearly demonstrate the superiority of the proposed method over other recent algorithms for transmission of H.264/AVC streams.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    Purpose: 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. Methods and Materials: 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. Results: Margin reduction from 5 mm to 3 mm to 0 mm generally led to an organ-at-risk (OAR) mean dose (D_m_e_a_n) 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, D_m_e_a_n) 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.

  8. High-Intensity Interval vs. Continuous Endurance Training: Preventive Effects on Hormonal Changes and Physiological Adaptations in Prediabetes Patients.

    Science.gov (United States)

    Safarimosavi, Saleh; Mohebbi, Hamid; Rohani, Hadi

    2018-06-22

    Safarimosavi, S, Mohebbi, H, and Rohani, H. High-intensity interval vs. continuous endurance training: Preventive effects on hormonal changes and physiological adaptations in prediabetes patients. J Strength Cond Res XX(X): 000-000, 2018-The aim of this study was to examine the effects of a 12-week high-intensity interval training (HIIT) intervention, or an isocaloric continuous endurance training (CET) intervention on insulin resistance indices and change in irisin and preptin in patients with prediabetes. Thirty-two prediabetic male patients (age = 38.7 ± 4; body mass index = 26.9 ± 1.4 kg·m; and V[Combining Dot Above]O2peak = 2.49 ± 0.22 L·min) were randomly assigned into 3 training groups (N = 8). These groups were matched based on the required energy expenditure (EE) for completing each protocol: (a) HIIT (10 × 60 seconds at 90% peak oxygen uptake [V[Combining Dot Above]O2peak], 1: 1 work to recovery at 50 W), (b) CET at an intensity equivalent to maximal fat oxidation (Fatmax) (CETFAT) (pedaling for a duration that expends an equivalent EE to an HIIT session [E ≈ HIIT]), (c) CET at an intensity equivalent to anaerobic threshold (CETAT) (E ≈ HIIT), and (d) the control group (CON): continued to perform their daily activities. After intervention, blood glucose levels were significantly (p HIIT group compared with CETAT group. Exercise training improved the insulin resistance index by 35, 28, and 37% in CETFAT, CETAT, and HIIT groups, respectively. Irisin concentrations in the HIIT and CETAT groups was significantly (p HIIT and CETFAT resulted in significant (p HIIT and CETFAT protocols had similar effects on the insulin resistance index of prediabetic patients. Also, the intensity and type of exercise were effective factors in changing irisin and preptin concentrations.

  9. 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.

  10. A novel robust proportional-integral (PI) adaptive observer design for chaos synchronization

    International Nuclear Information System (INIS)

    Pourgholi Mahdi; Majd Vahid Johari

    2011-01-01

    In this paper, chaos synchronization in the presence of parameter uncertainty, observer gain perturbation and exogenous input disturbance is considered. A nonlinear non-fragile proportional-integral (PI) adaptive observer is designed for the synchronization of chaotic systems; its stability conditions based on the Lyapunov technique are derived. The observer proportional and integral gains, by converting the conditions into linear matrix inequality (LMI), are optimally selected from solutions that satisfy the observer stability conditions such that the effect of disturbance on the synchronization error becomes minimized. To show the effectiveness of the proposed method, simulation results for the synchronization of a Lorenz chaotic system with unknown parameters in the presence of an exogenous input disturbance and abrupt gain perturbation are reported. (general)

  11. On Adapting the Tensor Voting Framework to Robust Color Image Denoising

    Science.gov (United States)

    Moreno, Rodrigo; Garcia, Miguel Angel; Puig, Domenec; Julià, Carme

    This paper presents an adaptation of the tensor voting framework for color image denoising, while preserving edges. Tensors are used in order to encode the CIELAB color channels, the uniformity and the edginess of image pixels. A specific voting process is proposed in order to propagate color from a pixel to its neighbors by considering the distance between pixels, the perceptual color difference (by using an optimized version of CIEDE2000), a uniformity measurement and the likelihood of the pixels being impulse noise. The original colors are corrected with those encoded by the tensors obtained after the voting process. Peak to noise ratios and visual inspection show that the proposed methodology has a better performance than state-of-the-art techniques.

  12. Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties

    Science.gov (United States)

    Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

    2017-10-01

    In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.

  13. 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.

  14. 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

    2018-02-14

    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.

  15. Hybrid GPU-CPU adaptive precision ray-triangle intersection tests for robust high-performance GPU dosimetry computations

    International Nuclear Information System (INIS)

    Perrotte, Lancelot; Bodin, Bruno; Chodorge, Laurent

    2011-01-01

    Before an intervention on a nuclear site, it is essential to study different scenarios to identify the less dangerous one for the operator. Therefore, it is mandatory to dispose of an efficient dosimetry simulation code with accurate results. One classical method in radiation protection is the straight-line attenuation method with build-up factors. In the case of 3D industrial scenes composed of meshes, the computation cost resides in the fast computation of all of the intersections between the rays and the triangles of the scene. Efficient GPU algorithms have already been proposed, that enable dosimetry calculation for a huge scene (800000 rays, 800000 triangles) in a fraction of second. But these algorithms are not robust: because of the rounding caused by floating-point arithmetic, the numerical results of the ray-triangle intersection tests can differ from the expected mathematical results. In worst case scenario, this can lead to a computed dose rate dramatically inferior to the real dose rate to which the operator is exposed. In this paper, we present a hybrid GPU-CPU algorithm to manage adaptive precision floating-point arithmetic. This algorithm allows robust ray-triangle intersection tests, with very small loss of performance (less than 5 % overhead), and without any need for scene-dependent tuning. (author)

  16. 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 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 reaction-diffusion case. With application to models in biology and physics, different spatiotemporal dynamics are observed and displayed.

  17. 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.

  18. 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

  19. Adaptive robust pole-placement control of 4-leg voltage-source inverters for standalone photovoltaic systems: Considering digital delays

    International Nuclear Information System (INIS)

    Nasiri, Reza; Radan, Ahmad

    2011-01-01

    Three leg inverters for photovoltaic systems have a lot of disadvantages, especially when the load is unbalanced. These disadvantages are for example, small utilization of the DC link voltage, the dependency of the modulation factor of the load current and the superposition of a DC component with the output AC voltage. A solution for these problems is the 4-leg inverter. Most papers dealing with 4-leg inverters ignore the effect of digital delays in control loop and suggest classic controllers, such as PI controller. However, the transient performance of the system does not become adjustable by applying classic control techniques. Additionally, adaptive control techniques have not yet been discussed for 4-leg inverters. This paper proposes the pole-placement control strategy via state feedback with integral state, which is a modern control technique, to control the system. Consequently, resulted system becomes highly robust. In addition, it suggests a Self-Tuner Regulator to guarantee the adaptive performance of the final system. Moreover, it proposes a novel model, considering digital delays, for 4-leg inverters. Simulation results show that transient performance of the system becomes accurately adjustable and the 4-leg inverter generates balanced voltage, with sinusoidal waveform, in spite of the presence of RL time variant loads.

  20. 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.

  1. Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study.

    Science.gov (United States)

    Rouhollahi, Korosh; Emadi Andani, Mehran; Karbassi, Seyed Mahdi; Izadi, Iman

    2017-02-01

    Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson's tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed-loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.

  2. Beneficial Autophagic Activities, Mitochondrial Function, and Metabolic Phenotype Adaptations Promoted by High-Intensity Interval Training in a Rat Model

    Directory of Open Access Journals (Sweden)

    Fang-Hui Li

    2018-05-01

    Full Text Available The effects of high-intensity interval (HIIT and moderate-intensity continuous training (MICT on basal autophagy and mitochondrial function in cardiac and skeletal muscle and plasma metabolic phenotypes have not been clearly characterized. Here, we investigated how 10-weeks HIIT and MICT differentially modify basal autophagy and mitochondrial markers in cardiac and skeletal muscle and conducted an untargeted metabolomics study with proton nuclear magnetic resonance (1H NMR spectroscopy and multivariate statistical analysis of plasma metabolic phenotypes. Male Sprague–Dawley rats were separated into three groups: sedentary control (SED, MICT, and HIIT. Rats underwent evaluation of exercise performance, including exercise tolerance and grip strength, and blood lactate levels were measured immediately after an incremental exercise test. Plasma samples were analyzed by 1H NMR. The expression of autophagy and mitochondrial markers and autophagic flux (LC3II/LC3-I ratio in cardiac, rectus femoris, and soleus muscle were analyzed by western blotting. Time to exhaustion and grip strength increased significantly following HIIT compared with that in both SED and MICT groups. Compared with those in the SED group, blood lactate level, and the expression of SDH, COX-IV, and SIRT3 significantly increased in rectus femoris and soleus muscle of both HIIT and MICT groups. Meanwhile, SDH and COX-IV content of cardiac muscle and COX-IV and SIRT3 content of rectus femoris and soleus muscle increased significantly following HIIT compared with that following MICT. The expression of LC3-II, ATG-3, and Beclin-1 and LC3II/LC3-I ratio were significantly increased only in soleus and cardiac muscle following HIIT. These data indicate that HIIT was more effective for improving physical performance and facilitating cardiac and skeletal muscle adaptations that increase mitochondrial function and basal autophagic activities. Moreover, 1H NMR spectroscopy and multivariate

  3. Beneficial Autophagic Activities, Mitochondrial Function, and Metabolic Phenotype Adaptations Promoted by High-Intensity Interval Training in a Rat Model.

    Science.gov (United States)

    Li, Fang-Hui; Li, Tao; Ai, Jing-Yi; Sun, Lei; Min, Zhu; Duan, Rui; Zhu, Ling; Liu, Yan-Ying; Liu, Timon Cheng-Yi

    2018-01-01

    The effects of high-intensity interval (HIIT) and moderate-intensity continuous training (MICT) on basal autophagy and mitochondrial function in cardiac and skeletal muscle and plasma metabolic phenotypes have not been clearly characterized. Here, we investigated how 10-weeks HIIT and MICT differentially modify basal autophagy and mitochondrial markers in cardiac and skeletal muscle and conducted an untargeted metabolomics study with proton nuclear magnetic resonance ( 1 H NMR) spectroscopy and multivariate statistical analysis of plasma metabolic phenotypes. Male Sprague-Dawley rats were separated into three groups: sedentary control (SED), MICT, and HIIT. Rats underwent evaluation of exercise performance, including exercise tolerance and grip strength, and blood lactate levels were measured immediately after an incremental exercise test. Plasma samples were analyzed by 1 H NMR. The expression of autophagy and mitochondrial markers and autophagic flux (LC3II/LC3-I ratio) in cardiac, rectus femoris, and soleus muscle were analyzed by western blotting. Time to exhaustion and grip strength increased significantly following HIIT compared with that in both SED and MICT groups. Compared with those in the SED group, blood lactate level, and the expression of SDH, COX-IV, and SIRT3 significantly increased in rectus femoris and soleus muscle of both HIIT and MICT groups. Meanwhile, SDH and COX-IV content of cardiac muscle and COX-IV and SIRT3 content of rectus femoris and soleus muscle increased significantly following HIIT compared with that following MICT. The expression of LC3-II, ATG-3, and Beclin-1 and LC3II/LC3-I ratio were significantly increased only in soleus and cardiac muscle following HIIT. These data indicate that HIIT was more effective for improving physical performance and facilitating cardiac and skeletal muscle adaptations that increase mitochondrial function and basal autophagic activities. Moreover, 1 H NMR spectroscopy and multivariate statistical

  4. 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

  5. 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. Copyright © 2015 the American Physiological Society.

  6. 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.

  7. Robust Stability and Stabilization of Interval Uncertain Descriptor Fractional-Order Systems with the Fractional-Order α: The 1≤α<2 Case

    Directory of Open Access Journals (Sweden)

    Yuanhua Li

    2015-01-01

    Full Text Available Stability and stabilization of fractional-order interval system is investigated. By adding parameters to linear matrix inequalities, necessary and sufficient conditions for stability and stabilization of the system are obtained. The results on stability check for uncertain FO-LTI systems with interval coefficients of dimension n only need to solve one 4n-by-4n LMI. Numerical examples are presented to shown the effectiveness of our results.

  8. Energy landscape reveals that the budding yeast cell cycle is a robust and adaptive multi-stage process.

    Directory of Open Access Journals (Sweden)

    Cheng Lv

    2015-03-01

    Full Text Available Quantitatively understanding the robustness, adaptivity and efficiency of cell cycle dynamics under the influence of noise is a fundamental but difficult question to answer for most eukaryotic organisms. Using a simplified budding yeast cell cycle model perturbed by intrinsic noise, we systematically explore these issues from an energy landscape point of view by constructing an energy landscape for the considered system based on large deviation theory. Analysis shows that the cell cycle trajectory is sharply confined by the ambient energy barrier, and the landscape along this trajectory exhibits a generally flat shape. We explain the evolution of the system on this flat path by incorporating its non-gradient nature. Furthermore, we illustrate how this global landscape changes in response to external signals, observing a nice transformation of the landscapes as the excitable system approaches a limit cycle system when nutrients are sufficient, as well as the formation of additional energy wells when the DNA replication checkpoint is activated. By taking into account the finite volume effect, we find additional pits along the flat cycle path in the landscape associated with the checkpoint mechanism of the cell cycle. The difference between the landscapes induced by intrinsic and extrinsic noise is also discussed. In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems.

  9. Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

    Science.gov (United States)

    Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

    2014-09-01

    This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  10. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. 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). Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Anatomical robust optimization to account for nasal cavity filling variation during intensity-modulated proton therapy: a comparison with conventional and adaptive planning strategies

    Science.gov (United States)

    van de Water, Steven; Albertini, Francesca; Weber, Damien C.; Heijmen, Ben J. M.; Hoogeman, Mischa S.; Lomax, Antony J.

    2018-01-01

    The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 ‘synthetic’ CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system ‘Erasmus-iCycle’ was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95%  ⩾  98% and V107%  ⩽  2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and

  13. MUSIC-CONTENT-ADAPTIVE ROBUST PRINCIPAL COMPONENT ANALYSIS FOR A SEMANTICALLY CONSISTENT SEPARATION OF FOREGROUND AND BACKGROUND IN MUSIC AUDIO SIGNALS

    OpenAIRE

    Papadopoulos , Hélène; Ellis , Daniel P.W.

    2014-01-01

    International audience; Robust Principal Component Analysis (RPCA) is a technique to decompose signals into sparse and low rank components, and has recently drawn the attention of the MIR field for the problem of separating leading vocals from accompaniment, with appealing re-sults obtained on small excerpts of music. However, the perfor-mance of the method drops when processing entire music tracks. We present an adaptive formulation of RPCA that incorporates music content information to guid...

  14. 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

  15. Effect of tapering after a period of high-volume sprint interval training on running performance and muscular adaptations in moderately trained runners

    DEFF Research Database (Denmark)

    Skovgaard, Casper; Almquist, Nicki Winfield; Kvorning, Thue

    2018-01-01

    The effect of tapering following a period of high-volume sprint interval training (SIT) and a basic volume of aerobic training on performance and muscle adaptations in moderately trained runners was examined. Eleven (8 males, 3 females) runners (maximum oxygen uptake (VO2-max): 56.8±2.9 mL·min(-1...... running test at 90% of vVO2-max to exhaustion (RRT). In addition, a biopsy from m. vastus lateralis was obtained at rest. Performance during RRT was better (P... at 60% of vVO2-max was lower (P

  16. 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.

  17. Complex reference values for endocrine and special chemistry biomarkers across pediatric, adult, and geriatric ages: establishment of robust pediatric and adult reference intervals on the basis of the Canadian Health Measures Survey.

    Science.gov (United States)

    Adeli, Khosrow; Higgins, Victoria; Nieuwesteeg, Michelle; Raizman, Joshua E; Chen, Yunqi; Wong, Suzy L; Blais, David

    2015-08-01

    Defining laboratory biomarker reference values in a healthy population and understanding the fluctuations in biomarker concentrations throughout life and between sexes are critical to clinical interpretation of laboratory test results in different disease states. The Canadian Health Measures Survey (CHMS) has collected blood samples and health information from the Canadian household population. In collaboration with the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER), the data have been analyzed to determine reference value distributions and reference intervals for several endocrine and special chemistry biomarkers in pediatric, adult, and geriatric age groups. CHMS collected data and blood samples from thousands of community participants aged 3 to 79 years. We used serum samples to measure 13 immunoassay-based special chemistry and endocrine markers. We assessed reference value distributions and, after excluding outliers, calculated age- and sex-specific reference intervals, along with corresponding 90% CIs, according to CLSI C28-A3 guidelines. We observed fluctuations in biomarker reference values across the pediatric, adult, and geriatric age range, with stratification required on the basis of age for all analytes. Additional sex partitions were required for apolipoprotein AI, homocysteine, ferritin, and high sensitivity C-reactive protein. The unique collaboration between CALIPER and CHMS has enabled, for the first time, a detailed examination of the changes in various immunochemical markers that occur in healthy individuals of different ages. The robust age- and sex-specific reference intervals established in this study provide insight into the complex biological changes that take place throughout development and aging and will contribute to improved clinical test interpretation. © 2015 American Association for Clinical Chemistry.

  18. Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

    Science.gov (United States)

    Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping

    2018-03-01

    This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.

  19. Robust Spread-Spectrum Communications Over Non-Gaussian Channels. Adaptive Disturbance Suppression With Small Data Support

    National Research Council Canada - National Science Library

    Batalama, Stella

    2001-01-01

    .... To achieve adaptive, rapid, and effective SS interference suppression from a small number of input observations, we defined a new class of linear filters that we called Auxiliary-Vector (AV) filters...

  20. 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)

  1. A Novel Finite-Sum Inequality-Based Method for Robust H∞ Control of Uncertain Discrete-Time Takagi-Sugeno Fuzzy Systems With Interval-Like Time-Varying Delays.

    Science.gov (United States)

    Zhang, Xian-Ming; Han, Qing-Long; Ge, Xiaohua

    2017-09-22

    This paper is concerned with the problem of robust H∞ control of an uncertain discrete-time Takagi-Sugeno fuzzy system with an interval-like time-varying delay. A novel finite-sum inequality-based method is proposed to provide a tighter estimation on the forward difference of certain Lyapunov functional, leading to a less conservative result. First, an auxiliary vector function is used to establish two finite-sum inequalities, which can produce tighter bounds for the finite-sum terms appearing in the forward difference of the Lyapunov functional. Second, a matrix-based quadratic convex approach is employed to equivalently convert the original matrix inequality including a quadratic polynomial on the time-varying delay into two boundary matrix inequalities, which delivers a less conservative bounded real lemma (BRL) for the resultant closed-loop system. Third, based on the BRL, a novel sufficient condition on the existence of suitable robust H∞ fuzzy controllers is derived. Finally, two numerical examples and a computer-simulated truck-trailer system are provided to show the effectiveness of the obtained results.

  2. Using Direct Policy Search to Identify Robust Strategies in Adapting to Uncertain Sea Level Rise and Storm Surge

    Science.gov (United States)

    Garner, G. G.; Keller, K.

    2017-12-01

    Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with deeply uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods have provided tremendous insight into this decision problem, but are often silent on tradeoffs as well as the effects of tail-area events and of potential future learning. Here we reformulate a simple sea-level rise adaptation model to address these concerns. We show that Direct Policy Search yields improved solution quality, with respect to Pareto-dominance in the objectives, over the traditional approach under uncertain sea-level rise projections and storm surge. Additionally, the new formulation produces high quality solutions with less computational demands than the traditional approach. Our results illustrate the utility of multi-objective adaptive formulations for the example of coastal adaptation, the value of information provided by observations, and point to wider-ranging application in climate change adaptation decision problems.

  3. 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

    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......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...... regularization (VR) algorithms. The FDAF-PEM-AFROW versions significantly outperform the original versions in every simulation. In terms of computational complexity, the FDAF-PEM-AFROW versions are themselves about two orders of magnitude cheaper than the original versions....

  4. Automatic NC-Data generation method for 5-axis cutting of turbine-blades by finding Safe heel-angles and adaptive path-intervals

    International Nuclear Information System (INIS)

    Piao, Cheng Dao; Lee, Cheol Soo; Cho, Kyu Zong; Park, Gwang Ryeol

    2004-01-01

    In this paper, an efficient method for generating 5-axis cutting data for a turbine blade is presented. The interference elimination of 5-axis cutting currently is very complicated, and it takes up a lot of time. The proposed method can generate an interference-free tool path, within an allowance range. Generating the cutting data just point to the cutting process and using it to obtain NC data by calculating the feed rate, allows us to maintain the proper feed rate of the 5-axis machine. This paper includes the algorithms for: (1) CL data generation by detecting an interference-free heel angle, (2) finding the optimal tool path interval considering the cusp-height, (3) finding the adaptive feed rate values for each cutter path, and (4) the inverse kinematics depending on the structure of the 5-axis machine, for generating the NC data

  5. Robust cellulosic ethanol production from SPORL-pretreated lodgepole pine using an adapted strain Saccharomyces cervisiae without detoxification

    Science.gov (United States)

    S. Tian; X.L. Luo; X.S. Yang; J.Y. Zhu

    2010-01-01

    This study reports an ethanol yield of 270 L/ton wood from lodgepole pine pretreated with sulfite pretreatment to overcome recalcitrance of lignocellulose (SPORL) using an adapted strain, Saccharomyces cerevisiae Y5, without detoxification. The enzymatic hydrolysate produced from pretreated cellulosic solids substrate was combined with pretreatment hydrolysate before...

  6. Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

    Science.gov (United States)

    Tiwari, Shivendra N.; Padhi, Radhakant

    2018-01-01

    Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

  7. Cold-water immersion after training sessions: Effects on fiber type-specific adaptations in muscle K+ transport proteins to sprint-interval training in men.

    Science.gov (United States)

    Christiansen, Danny; Bishop, David John; Broatch, James R; Bangsbo, Jens; McKenna, Michael John; Murphy, Robyn M

    2018-05-10

    Effects of regular use of cold-water immersion (CWI) on fiber type-specific adaptations in muscle K + transport proteins to intense training, along with their relationship to changes in mRNA levels after the first training session, were investigated in humans. Nineteen recreationally-active men (24{plus minus}6 y, 79.5{plus minus}10.8 kg, 44.6{plus minus}5.8 mL∙kg -1 ∙min -1 ) completed six weeks of sprint-interval cycling either without (passive rest; CON) or with training sessions followed by CWI (15 min at 10{degree sign}C; COLD). Muscle biopsies were obtained before and after training to determine abundance of Na + ,K + -ATPase isoforms (α 1-3 , β 1-3 ) and FXYD1, and after recovery treatments (+0h and +3h) on the first day of training to measure mRNA content. Training increased (ptraining (p>0.05). CWI after each session did not influence responses to training (p>0.05). However, α 2 mRNA increased after the first session in COLD (+0h, p0.05). In both conditions, α 1 and β 3 mRNA increased (+3h; p 0.05) after the first session. In summary, Na + ,K + -ATPase isoforms are differently regulated in type I and II muscle fibers by sprint-interval training in humans, which for most isoforms do not associate with changes in mRNA levels after the first training session. CWI neither impairs nor improves protein adaptations to intense training of importance for muscle K + regulation.

  8. 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.

  9. Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Zhongrong Zhang

    2016-01-01

    Full Text Available Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, precise wind power forecasts are of primary importance to solve operational, planning and economic problems in the growing wind power scenario. Previous research has focused efforts on the deterministic forecast of wind power values, but less attention has been paid to providing information about wind energy. Based on an optimal Adaptive-Network-Based Fuzzy Inference System (ANFIS and Singular Spectrum Analysis (SSA, this paper develops a hybrid uncertainty forecasting model, IFASF (Interval Forecast-ANFIS-SSA-Firefly Alogorithm, to obtain the upper and lower bounds of daily average wind power, which is beneficial for the practical operation of both the grid company and independent power producers. To strengthen the practical ability of this developed model, this paper presents a comparison between IFASF and other benchmarks, which provides a general reference for this aspect for statistical or artificially intelligent interval forecast methods. The comparison results show that the developed model outperforms eight benchmarks and has a satisfactory forecasting effectiveness in three different wind farms with two time horizons.

  10. 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。

  11. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    DEFF Research Database (Denmark)

    Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

    2016-01-01

    Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

  12. Robust Decision Making to Support Water Quality Climate Adaptation: a Case Study in the Chesapeake Bay Watershed

    Science.gov (United States)

    Fischbach, J. R.; Lempert, R. J.; Molina-Perez, E.

    2017-12-01

    The U.S. Environmental Protection Agency (USEPA), together with state and local partners, develops watershed implementation plans designed to meet water quality standards. Climate uncertainty, along with uncertainty about future land use changes or the performance of water quality best management practices (BMPs), may make it difficult for these implementation plans to meet water quality goals. In this effort, we explored how decision making under deep uncertainty (DMDU) methods such as Robust Decision Making (RDM) could help USEPA and its partners develop implementation plans that are more robust to future uncertainty. The study focuses on one part of the Chesapeake Bay watershed, the Patuxent River, which is 2,479 sq km in area, highly urbanized, and has a rapidly growing population. We simulated the contribution of stormwater contaminants from the Patuxent to the overall Total Maximum Daily Load (TMDL) for the Chesapeake Bay under multiple scenarios reflecting climate and other uncertainties. Contaminants considered included nitrogen, phosphorus, and sediment loads. The assessment included a large set of scenario simulations using the USEPA Chesapeake Bay Program's Phase V watershed model. Uncertainties represented in the analysis included 18 downscaled climate projections (based on 6 general circulation models and 3 emissions pathways), 12 land use scenarios with different population projections and development patterns, and alternative assumptions about BMP performance standards and efficiencies associated with different suites of stormwater BMPs. Finally, we developed cost estimates for each of the performance standards and compared cost to TMDL performance as a key tradeoff for future water quality management decisions. In this talk, we describe how this research can help inform climate-related decision support at USEPA's Chesapeake Bay Program, and more generally how RDM and other DMDU methods can support improved water quality management under climate

  13. Robustness and strategies of adaptation among farmer varieties of African Rice (Oryza glaberrima) and Asian Rice (Oryza sativa) across West Africa.

    Science.gov (United States)

    Mokuwa, Alfred; Nuijten, Edwin; Okry, Florent; Teeken, Béla; Maat, Harro; Richards, Paul; Struik, Paul C

    2013-01-01

    This study offers evidence of the robustness of farmer rice varieties (Oryza glaberrima and O. sativa) in West Africa. Our experiments in five West African countries showed that farmer varieties were tolerant of sub-optimal conditions, but employed a range of strategies to cope with stress. Varieties belonging to the species Oryza glaberrima - solely the product of farmer agency - were the most successful in adapting to a range of adverse conditions. Some of the farmer selections from within the indica and japonica subspecies of O. sativa also performed well in a range of conditions, but other farmer selections from within these two subspecies were mainly limited to more specific niches. The results contradict the rather common belief that farmer varieties are only of local value. Farmer varieties should be considered by breeding programmes and used (alongside improved varieties) in dissemination projects for rural food security.

  14. Robustness and Strategies of Adaptation among Farmer Varieties of African Rice (Oryza glaberrima) and Asian Rice (Oryza sativa) across West Africa

    Science.gov (United States)

    Maat, Harro; Richards, Paul; Struik, Paul C.

    2013-01-01

    This study offers evidence of the robustness of farmer rice varieties (Oryza glaberrima and O. sativa) in West Africa. Our experiments in five West African countries showed that farmer varieties were tolerant of sub-optimal conditions, but employed a range of strategies to cope with stress. Varieties belonging to the species Oryza glaberrima – solely the product of farmer agency – were the most successful in adapting to a range of adverse conditions. Some of the farmer selections from within the indica and japonica subspecies of O. sativa also performed well in a range of conditions, but other farmer selections from within these two subspecies were mainly limited to more specific niches. The results contradict the rather common belief that farmer varieties are only of local value. Farmer varieties should be considered by breeding programmes and used (alongside improved varieties) in dissemination projects for rural food security. PMID:23536754

  15. Robust cellulosic ethanol production from SPORL-pretreated lodgepole pine using an adapted strain Saccharomyces cerevisiae without detoxification.

    Science.gov (United States)

    Tian, S; Luo, X L; Yang, X S; Zhu, J Y

    2010-11-01

    This study reports an ethanol yield of 270L/ton wood from lodgepole pine pretreated with sulfite pretreatment to overcome recalcitrance of lignocellulose (SPORL) using an adapted strain, Saccharomyces cerevisiae Y5, without detoxification. The enzymatic hydrolysate produced from pretreated cellulosic solids substrate was combined with pretreatment hydrolysate before fermentation. Detoxification of the pretreatment hydrolysate using overliming or XAD-4 resin before being combined with enzymatic hydrolysate improved ethanol productivity in the first 4h of fermentation and overall fermentation efficiency. However, detoxification did not improve final ethanol yield because of sugar losses. The Y5 strain showed excellent ethanol productivities of 2.0 and 0.8g/L/h averaged over a period of 4 and 24h, respectively, in the undetoxified run. The furan metabolization rates of the Y5 strain were significantly higher for the undetoxified run than those for the detoxidfied runs, suggesting it can tolerate even higher furan concentrations than those studied. Preliminary mass and energy balances were conducted. SPORL produced an excellent monomeric sugar recovery value of about 85% theoretical and a net energy output of 4.05GJ/ton wood with an ethanol energy production efficiency of 178% before distillation.

  16. Creatine Monohydrate Supplementation Does Not Augment Fitness, Performance, or Body Composition Adaptations in Response to Four Weeks of High-Intensity Interval Training in Young Females.

    Science.gov (United States)

    Forbes, Scott C; Sletten, Nathan; Durrer, Cody; Myette-Côté, Étienne; Candow, D; Little, Jonathan P

    2017-06-01

    High-intensity interval training (HIIT) has been shown to improve cardiorespiratory fitness, performance, body composition, and insulin sensitivity. Creatine (Cr) supplementation may augment responses to HIIT, leading to even greater physiological adaptations. The purpose of this study was to determine the effects of 4 weeks of HIIT (three sessions/week) combined with Cr supplementation in recreationally active females. Seventeen females (age = 23 ± 4 yrs; BMI = 23.4 ± 2.4) were randomly assigned to either Cr (Cr; 0.3 g・kg -1 ・d -1 for 5 d followed by 0.1 g・kg -1 ・d -1 for 23 days; n = 9) or placebo (PLA; n = 8). Before and after the intervention, VO 2peak , ventilatory threshold (VT), time-trial performance, lean body mass and fat mass, and insulin sensitivity were assessed. HIIT improved VO 2peak (Cr = +10.2%; PLA = +8.8%), VT (Cr = +12.7%; PLA = +9.9%), and time-trial performance (Cr = -11.5%; PLA = -11.6%) with no differences between groups (time main effects, all p body lean mass (Cr = +0.5%; PLA = -0.9%), or insulin resistance (Cr = +3.9%; PLA = +18.7%). In conclusion, HIIT is an effective way to improve cardiorespiratory fitness, VT, and time-trial performance. The addition of Cr to HIIT did not augment improvements in cardiorespiratory fitness, performance or body composition in recreationally active females.

  17. 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.

  18. 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.

  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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

    Science.gov (United States)

    Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

    2018-04-01

    This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

  2. 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

  3. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  4. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.

  5. 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

    2018-03-01

    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.

  6. Robust nonhomogeneous training samples detection method for space-time adaptive processing radar using sparse-recovery with knowledge-aided

    Science.gov (United States)

    Li, Zhihui; Liu, Hanwei; Zhang, Yongshun; Guo, Yiduo

    2017-10-01

    The performance of space-time adaptive processing (STAP) may degrade significantly when some of the training samples are contaminated by the signal-like components (outliers) in nonhomogeneous clutter environments. To remove the training samples contaminated by outliers in nonhomogeneous clutter environments, a robust nonhomogeneous training samples detection method using the sparse-recovery (SR) with knowledge-aided (KA) is proposed. First, the reduced-dimension (RD) overcomplete spatial-temporal steering dictionary is designed with the prior knowledge of system parameters and the possible target region. Then, the clutter covariance matrix (CCM) of cell under test is efficiently estimated using a modified focal underdetermined system solver (FOCUSS) algorithm, where a RD overcomplete spatial-temporal steering dictionary is applied. Third, the proposed statistics are formed by combining the estimated CCM with the generalized inner products (GIP) method, and the contaminated training samples can be detected and removed. Finally, several simulation results validate the effectiveness of the proposed KA-SR-GIP method.

  7. Robustly stable adaptive control of a tandem of master-slave robotic manipulators with force reflection by using a multiestimation scheme.

    Science.gov (United States)

    Ibeas, Asier; de la Sen, Manuel

    2006-10-01

    The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.

  8. Whole-Body High-Intensity Interval Training Induce Similar Cardiorespiratory Adaptations Compared With Traditional High-Intensity Interval Training and Moderate-Intensity Continuous Training in Healthy Men.

    Science.gov (United States)

    Schaun, Gustavo Z; Pinto, Stephanie S; Silva, Mariana R; Dolinski, Davi B; Alberton, Cristine L

    2018-05-07

    Schaun, GZ, Pinto, SS, Silva, MR, Dolinski, DB, and Alberton, CL. Sixteen weeks of whole-body high-intensity interval training induce similar cardiorespiratory responses compared with traditional high-intensity interval training and moderate-intensity continuous training in healthy men. J Strength Cond Res XX(X): 000-000, 2018-Low-volume high-intensity interval training (HIIT) protocols that use the body weight as resistance could be an interesting and inexpensive alternative to traditional ergometer-based high-intensity interval training (HIIT-T) and moderate-intensity continuous training (MICT). Therefore, our aim was to compare the effects of 16 weeks of whole-body HIIT (HIIT-WB), HIIT-T, and MICT on maximal oxygen uptake (V[Combining Dot Above]O2max), second ventilatory threshold (VT2), and running economy (RE) outcomes. Fifty-five healthy men (23.7 ± 0.7 years, 1.79 ± 0.01 m, 78.5 ± 1.7 kg) were randomized into 3 training groups (HIIT-T = 17; HIIT-WB = 19; MICT = 19) for 16 weeks (3× per week). The HIIT-T group performed eight 20-second bouts at 130% of the velocity associated to V[Combining Dot Above]O2max (vV[Combining Dot Above]O2max) interspersed by 10-second passive recovery on a treadmill, whereas HIIT-WB group performed the same protocol but used calisthenics exercises at an all-out intensity instead of treadmill running. Finally, MICT group exercised for 30 minutes at 90-95% of the heart rate (HR) associated to VT2. After the intervention, all groups improved V[Combining Dot Above]O2max, vV[Combining Dot Above]O2max, time to exhaustion (Tmax), VT2, velocity associated with VT2 (vVT2), and time to reach VT2 (tVT2) significantly (p HIIT-T compared with HIIT-WB (p HIIT-WB can be as effective as traditional HIIT while also being time-efficient compared with MICT to improve health-related outcomes after 16 weeks of training. However, HIIT-T and MICT seem preferable to enhance performance-related outcomes compared with HIIT-WB.

  9. 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.......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...

  10. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  11. 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

  12. 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

  13. 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.

  14. Short and Long Term Effects of High-Intensity Interval Training on Hormones, Metabolites, Antioxidant System, Glycogen Concentration, and Aerobic Performance Adaptations in Rats

    OpenAIRE

    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 anaer...

  15. 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 y parámetros 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, cuando el modelo de la planta se desvía del nominal, para el cual se realizó el diseño.En este trabajo se evalúa el comportamiento 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 del diseño, costo computacional de la implementación y sensibilidad ante variaciones en los parámetros y/o presencia de disturbios. Se llega a conclusiones que permiten disponer de criterios para la elección más adecuada, en dependencia de los requerimientos dinámicos que la aplicación demande, así como de los medios técnicos de que se disponga.  Many dynamic systems have first order mathematic models, with time variable parameters. In these cases, the classical tools do not satisfy at all control system stability, good performance and perturbation rejection, when the plant model differs from the nominal one, for which the controller was designed.In this article, three control strategies are 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, the computational 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.

  16. 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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Economic Justification Of Robust Or Adaptive Planning And Design Of Resilient Water Resources Systems Under Deep Uncertainty: A Case Study In The Iolanda Water Treatment Plant Of Lusaka, Zambia

    Science.gov (United States)

    Mendoza, G.; Tkach, M.; Kucharski, J.; Chaudhry, R.

    2017-12-01

    This discussion is focused around the application of a bottom-up vulnerability assessment procedure for planning of climate resilience to a water treament plant for teh city of Iolanda, Zambia. This project is a Millennium Challenge Corporation (MCC) innitiaive with technical support by the UNESCO category II, International Center for Integrated Water Resources Management (ICIWaRM) with secretariat at the US Army Corps of Engineers Institute for Water Resources. The MCC is an innovative and independent U.S. foreign aid agency that is helping lead the fight against global poverty. The bottom-up vulnerability assessmentt framework examines critical performance thresholds, examines the external drivers that would lead to failure, establishes plausibility and analytical uncertainty that would lead to failure, and provides the economic justification for robustness or adaptability. This presentation will showcase the experiences in the application of the bottom-up framework to a region that is very vulnerable to climate variability, has poor instituional capacities, and has very limited data. It will illustrate the technical analysis and a decision process that led to a non-obvious climate robust solution. Most importantly it will highlight the challenges of utilizing discounted cash flow analysis (DCFA), such as net present value, in justifying robust or adaptive solutions, i.e. comparing solution under different future risks. We highlight a solution to manage the potential biases these DCFA procedures can incur.

  18. Robust Scientists

    DEFF Research Database (Denmark)

    Gorm Hansen, Birgitte

    their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... 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...

  19. Robustness and Strategies of Adaptation among Farmer Varieties of African Rice (Oryza glaberrima) and Asian Rice (Oryza sativa) across West Africa

    NARCIS (Netherlands)

    Mokuwa, A.; Nuijten, H.A.C.P.; Okry, F.; Teeken, B.W.E.; Maat, H.; Richards, P.; Struik, P.C.

    2013-01-01

    This study offers evidence of the robustness of farmer rice varieties (Oryza glaberrima and O. sativa) in West Africa. Our experiments in five West African countries showed that farmer varieties were tolerant of sub-optimal conditions, but employed a range of strategies to cope with stress.

  20. 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 ...

  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. Measure of robustness for complex networks

    Science.gov (United States)

    Youssef, Mina Nabil

    to the spread of susceptible/infected/recovered (SIR) epidemics. To compute VCSIR, we propose a novel individual-based approach to model the spread of SIR epidemics in networks, which captures the infection size for a given effective infection rate. Thus, VCSIR quantitatively integrates the infection strength with the corresponding infection size. To optimize the VCSIR metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation

  3. Interval selection with machine-dependent intervals

    OpenAIRE

    Bohmova K.; Disser Y.; Mihalak M.; Widmayer P.

    2013-01-01

    We study an offline interval scheduling problem where every job has exactly one associated interval on every machine. To schedule a set of jobs, exactly one of the intervals associated with each job must be selected, and the intervals selected on the same machine must not intersect.We show that deciding whether all jobs can be scheduled is NP-complete already in various simple cases. In particular, by showing the NP-completeness for the case when all the intervals associated with the same job...

  4. 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...

  5. Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

    International Nuclear Information System (INIS)

    Shabani, Hikma; Ahmed, Musse Mohamud; Khan, Sheroz; Hameed, Shahab Ahmed; Habaebi, Mohamed Hadi

    2013-01-01

    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

  6. 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.

  7. 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.

  8. Convex Interval Games

    NARCIS (Netherlands)

    Alparslan-Gok, S.Z.; Brânzei, R.; Tijs, S.H.

    2008-01-01

    In this paper, convex interval games are introduced and some characterizations are given. Some economic situations leading to convex interval games are discussed. The Weber set and the Shapley value are defined for a suitable class of interval games and their relations with the interval core for

  9. A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

    Science.gov (United States)

    Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

    2011-01-01

    Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

  10. 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.

  11. 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...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  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. Robustness in laying hens

    NARCIS (Netherlands)

    Star, L.

    2008-01-01

    The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust

  14. Programming with Intervals

    Science.gov (United States)

    Matsakis, Nicholas D.; Gross, Thomas R.

    Intervals are a new, higher-level primitive for parallel programming with which programmers directly construct the program schedule. Programs using intervals can be statically analyzed to ensure that they do not deadlock or contain data races. In this paper, we demonstrate the flexibility of intervals by showing how to use them to emulate common parallel control-flow constructs like barriers and signals, as well as higher-level patterns such as bounded-buffer producer-consumer. We have implemented intervals as a publicly available library for Java and Scala.

  15. Perceptual Robust Design

    DEFF Research Database (Denmark)

    Pedersen, Søren Nygaard

    The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...

  16. 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.

  17. 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...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... 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...

  18. Robust multivariate analysis

    CERN Document Server

    J Olive, David

    2017-01-01

    This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

  19. Robustness: confronting lessons from physics and biology.

    Science.gov (United States)

    Lesne, Annick

    2008-11-01

    The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

  20. Step Detection Robust against the Dynamics of Smartphones

    Science.gov (United States)

    Lee, Hwan-hee; Choi, Suji; Lee, Myeong-jin

    2015-01-01

    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. PMID:26516857

  1. Overconfidence in Interval Estimates

    Science.gov (United States)

    Soll, Jack B.; Klayman, Joshua

    2004-01-01

    Judges were asked to make numerical estimates (e.g., "In what year was the first flight of a hot air balloon?"). Judges provided high and low estimates such that they were X% sure that the correct answer lay between them. They exhibited substantial overconfidence: The correct answer fell inside their intervals much less than X% of the time. This…

  2. Robustness of Structures

    DEFF Research Database (Denmark)

    Faber, Michael Havbro; 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...... ‘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...... 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...

  3. Robust Growth Determinants

    OpenAIRE

    Doppelhofer, Gernot; Weeks, Melvyn

    2011-01-01

    This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...

  4. Robust Programming by Example

    OpenAIRE

    Bishop , Matt; Elliott , Chip

    2011-01-01

    Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.

  5. Self-organization principles result in robust control of flexible manufacturing systems

    DEFF Research Database (Denmark)

    Nature shows us in our daily life how robust, flexible and optimal self-organized modular constructions work in complex physical, chemical and biological systems, which successfully adapt to new and unexpected situations. A promising strategy is therefore to use such self-organization and pattern...... problems with several autonomous robots and several targets are considered as model of flexible manufacturing systems. Each manufacturing target has to be served in a given time interval by one and only one robot and the total working costs have to be minimized (or total winnings maximized). A specifically...... constructed dynamical system approach (coupled selection equations) is used which is based on pattern formation principles and results in fault resistant and robust behaviour. An important feature is that this type of control also guarantees feasiblitiy of the assignment solutions. In previous work...

  6. Novel global robust stability criterion for neural networks with delay

    International Nuclear Information System (INIS)

    Singh, Vimal

    2009-01-01

    A novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example illustrating the improvement of the present criterion over several recently reported criteria is given.

  7. 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...

  8. Adaptive Detection and ISI Mitigation for Mobile Molecular Communication.

    Science.gov (United States)

    Chang, Ge; Lin, Lin; Yan, Hao

    2018-03-01

    Current studies on modulation and detection schemes in molecular communication mainly focus on the scenarios with static transmitters and receivers. However, mobile molecular communication is needed in many envisioned applications, such as target tracking and drug delivery. Until now, investigations about mobile molecular communication have been limited. In this paper, a static transmitter and a mobile bacterium-based receiver performing random walk are considered. In this mobile scenario, the channel impulse response changes due to the dynamic change of the distance between the transmitter and the receiver. Detection schemes based on fixed distance fail in signal detection in such a scenario. Furthermore, the intersymbol interference (ISI) effect becomes more complex due to the dynamic character of the signal which makes the estimation and mitigation of the ISI even more difficult. In this paper, an adaptive ISI mitigation method and two adaptive detection schemes are proposed for this mobile scenario. In the proposed scheme, adaptive ISI mitigation, estimation of dynamic distance, and the corresponding impulse response reconstruction are performed in each symbol interval. Based on the dynamic channel impulse response in each interval, two adaptive detection schemes, concentration-based adaptive threshold detection and peak-time-based adaptive detection, are proposed for signal detection. Simulations demonstrate that the ISI effect is significantly reduced and the adaptive detection schemes are reliable and robust for mobile molecular communication.

  9. Robust procedures in chemometrics

    DEFF Research Database (Denmark)

    Kotwa, Ewelina

    properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...

  10. Surveillance test interval optimization

    International Nuclear Information System (INIS)

    Cepin, M.; Mavko, B.

    1995-01-01

    Technical specifications have been developed on the bases of deterministic analyses, engineering judgment, and expert opinion. This paper introduces our risk-based approach to surveillance test interval (STI) optimization. This approach consists of three main levels. The first level is the component level, which serves as a rough estimation of the optimal STI and can be calculated analytically by a differentiating equation for mean unavailability. The second and third levels give more representative results. They take into account the results of probabilistic risk assessment (PRA) calculated by a personal computer (PC) based code and are based on system unavailability at the system level and on core damage frequency at the plant level

  11. 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, T 1 and T 2 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 T 1 values of a sample set deviated from their reference values by 0.3% (longest relaxation interval) and 2.4% (shortest relaxation interval). The largest T 2 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

  12. 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...

  13. Nonlinear Robust Disturbance Attenuation Control Design for Static Var Compensator in Power System

    Directory of Open Access Journals (Sweden)

    Ting Liu

    2013-01-01

    Full Text Available The problem of designing an adaptive backstepping controller for nonlinear static var compensator (SVC system is addressed adopting two perspectives. First, instead of artificially assuming an upper bound or inequality scaling, the minimax theory is used to treat the external unknown disturbances. The system is insensitive to effects of large disturbances due to taking into account the worst case disturbance. Second, a parameter projection mechanism is introduced in adaptive control to force the parameter estimate within a prior specified interval. The proposed controller handles the nonlinear parameterization without compromising control smoothness and at the same time the parameter estimate speed is improved and the robustness of system is strengthened. Considering the short-circuit ground fault and mechanical power perturbation, a simulation study is carried out. The results show the effectiveness of the proposed control method.

  14. Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

    DEFF Research Database (Denmark)

    Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.

    2016-01-01

    robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

  15. Robustness of Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2008-01-01

    This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). 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 new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...

  16. Robustness of structures

    DEFF Research Database (Denmark)

    Vrouwenvelder, T.; Sørensen, John Dalsgaard

    2009-01-01

    After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....

  17. Robust regularized least-squares beamforming approach to signal estimation

    KAUST Repository

    Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.

    2017-01-01

    In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill

  18. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  19. Robustness - theoretical framework

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.

    2010-01-01

    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 new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....

  20. 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...... 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....... 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...

  1. Multichannel interval timer

    International Nuclear Information System (INIS)

    Turko, B.T.

    1983-10-01

    A CAMAC based modular multichannel interval timer is described. The timer comprises twelve high resolution time digitizers with a common start enabling twelve independent stop inputs. Ten time ranges from 2.5 μs to 1.3 μs can be preset. Time can be read out in twelve 24-bit words either via CAMAC Crate Controller or an external FIFO register. LSB time calibration is 78.125 ps. An additional word reads out the operational status of twelve stop channels. The system consists of two modules. The analog module contains a reference clock and 13 analog time stretchers. The digital module contains counters, logic and interface circuits. The timer has an excellent differential linearity, thermal stability and crosstalk free performance

  2. Experimenting with musical intervals

    Science.gov (United States)

    Lo Presto, Michael C.

    2003-07-01

    When two tuning forks of different frequency are sounded simultaneously the result is a complex wave with a repetition frequency that is the fundamental of the harmonic series to which both frequencies belong. The ear perceives this 'musical interval' as a single musical pitch with a sound quality produced by the harmonic spectrum responsible for the waveform. This waveform can be captured and displayed with data collection hardware and software. The fundamental frequency can then be calculated and compared with what would be expected from the frequencies of the tuning forks. Also, graphing software can be used to determine equations for the waveforms and predict their shapes. This experiment could be used in an introductory physics or musical acoustics course as a practical lesson in superposition of waves, basic Fourier series and the relationship between some of the ear's subjective perceptions of sound and the physical properties of the waves that cause them.

  3. 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...

  4. Qualitative Robustness in Estimation

    Directory of Open Access Journals (Sweden)

    Mohammed Nasser

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of   qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.

  5. 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...

  6. 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.

  7. Robustness of airline alliance route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

    2015-05-01

    The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

  8. 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.

  9. Online adaptation and verification of VMAT

    International Nuclear Information System (INIS)

    Crijns, Wouter; Defraene, Gilles; Depuydt, Tom; Haustermans, Karin; Van Herck, Hans; Maes, Frederik; Van den Heuvel, Frank

    2015-01-01

    . Results: The proposed adaptation of a two-arc VMAT plan resulted in the intended CTV mean (Δ ≤ 3%) and TCP (ΔTCP ≤ 0.001). Moreover, the method assures the intended CI 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

  10. PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

    Institute of Scientific and Technical Information of China (English)

    HU Jie; PENG Yinghong; XIONG Guangleng

    2006-01-01

    A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

  11. Robust power spectral estimation for EEG data.

    Science.gov (United States)

    Melman, Tamar; Victor, Jonathan D

    2016-08-01

    Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Robustness in econometrics

    CERN Document Server

    Sriboonchitta, Songsak; Huynh, Van-Nam

    2017-01-01

    This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

  13. Robust plasmonic substrates

    DEFF Research Database (Denmark)

    Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas

    2014-01-01

    Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...

  14. Robust Object Tracking Using Valid Fragments Selection.

    Science.gov (United States)

    Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

  15. Robust surgery loading

    NARCIS (Netherlands)

    Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert

    2008-01-01

    We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This

  16. Robustness Envelopes of Networks

    NARCIS (Netherlands)

    Trajanovski, S.; Martín-Hernández, J.; Winterbach, W.; Van Mieghem, P.

    2013-01-01

    We study the robustness of networks under node removal, considering random node failure, as well as targeted node attacks based on network centrality measures. Whilst both of these have been studied in the literature, existing approaches tend to study random failure in terms of average-case

  17. Detection of bursts in neuronal spike trains by the mean inter-spike interval method

    Institute of Scientific and Technical Information of China (English)

    Lin Chen; Yong Deng; Weihua Luo; Zhen Wang; Shaoqun Zeng

    2009-01-01

    Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgrnent. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

  18. Confidence intervals for correlations when data are not normal.

    Science.gov (United States)

    Bishara, Anthony J; Hittner, James B

    2017-02-01

    With nonnormal data, the typical confidence interval of the correlation (Fisher z') may be inaccurate. The literature has been unclear as to which of several alternative methods should be used instead, and how extreme a violation of normality is needed to justify an alternative. Through Monte Carlo simulation, 11 confidence interval methods were compared, including Fisher z', two Spearman rank-order methods, the Box-Cox transformation, rank-based inverse normal (RIN) transformation, and various bootstrap methods. Nonnormality often distorted the Fisher z' confidence interval-for example, leading to a 95 % confidence interval that had actual coverage as low as 68 %. Increasing the sample size sometimes worsened this problem. Inaccurate Fisher z' intervals could be predicted by a sample kurtosis of at least 2, an absolute sample skewness of at least 1, or significant violations of normality hypothesis tests. Only the Spearman rank-order and RIN transformation methods were universally robust to nonnormality. Among the bootstrap methods, an observed imposed bootstrap came closest to accurate coverage, though it often resulted in an overly long interval. The results suggest that sample nonnormality can justify avoidance of the Fisher z' interval in favor of a more robust alternative. R code for the relevant methods is provided in supplementary materials.

  19. A robust classic.

    Science.gov (United States)

    Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus

    2011-01-01

    In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.

  20. Robust Airline Schedules

    OpenAIRE

    Eggenberg, Niklaus; Salani, Matteo; Bierlaire, Michel

    2010-01-01

    Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incurred by possible modifications of the original plan to be performed when reality does not reflect what was expected in the planning phase. The modern research trend focuses on "robustness" of solutions instead of yield or profit. Although ro...

  1. A closer look at adaptive regret

    NARCIS (Netherlands)

    D. Adamskyi (Dmitri); W.M. Koolen-Wijkstra (Wouter); A. Chernov (Alexey); V. Vovk

    2016-01-01

    textabstractFor the prediction with expert advice setting, we consider methods to construct algorithms that have low adaptive regret. The adaptive regret of an algorithm on a time interval [t1,t2] is the loss of the algorithm minus the loss of the best expert over that interval. Adaptive regret

  2. Global robust stability of delayed recurrent neural networks

    International Nuclear Information System (INIS)

    Cao Jinde; Huang Deshuang; Qu Yuzhong

    2005-01-01

    This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results

  3. Delay-Dependent Guaranteed Cost Control of an Interval System with Interval Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Xiao Min

    2009-01-01

    Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

  4. Robust efficient video fingerprinting

    Science.gov (United States)

    Puri, Manika; Lubin, Jeffrey

    2009-02-01

    We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

  5. Real-time control systems: feedback, scheduling and robustness

    Science.gov (United States)

    Simon, Daniel; Seuret, Alexandre; Sename, Olivier

    2017-08-01

    The efficient control of real-time distributed systems, where continuous components are governed through digital devices and communication networks, needs a careful examination of the constraints arising from the different involved domains inside co-design approaches. Thanks to the robustness of feedback control, both new control methodologies and slackened real-time scheduling schemes are proposed beyond the frontiers between these traditionally separated fields. A methodology to design robust aperiodic controllers is provided, where the sampling interval is considered as a control variable of the system. Promising experimental results are provided to show the feasibility and robustness of the approach.

  6. Interval stability for complex systems

    Science.gov (United States)

    Klinshov, Vladimir V.; Kirillov, Sergey; Kurths, Jürgen; Nekorkin, Vladimir I.

    2018-04-01

    Stability of dynamical systems against strong perturbations is an important problem of nonlinear dynamics relevant to many applications in various areas. Here, we develop a novel concept of interval stability, referring to the behavior of the perturbed system during a finite time interval. Based on this concept, we suggest new measures of stability, namely interval basin stability (IBS) and interval stability threshold (IST). IBS characterizes the likelihood that the perturbed system returns to the stable regime (attractor) in a given time. IST provides the minimal magnitude of the perturbation capable to disrupt the stable regime for a given interval of time. The suggested measures provide important information about the system susceptibility to external perturbations which may be useful for practical applications. Moreover, from a theoretical viewpoint the interval stability measures are shown to bridge the gap between linear and asymptotic stability. We also suggest numerical algorithms for quantification of the interval stability characteristics and demonstrate their potential for several dynamical systems of various nature, such as power grids and neural networks.

  7. Robust Performance And Dissipation of Stochastic Control Systems

    DEFF Research Database (Denmark)

    Thygesen, Uffe Høgsbro

    and topology on the space of supply rates. For instance, we give conditions under which the available storage is a continuous convex function of the supply rate. Dissipation theory in the existing literature applies only to deterministic systems. This is unfortunate since robust control applications typically...... is a prototype of robust adaptive control problems. We show that the optimal (minimax) controller for this problem is finite dimensional but not based on certainty equivalence, and we discuss the heuristic certainty equivalence controller....

  8. Robust Control Design via Linear Programming

    Science.gov (United States)

    Keel, L. H.; Bhattacharyya, S. P.

    1998-01-01

    This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.

  9. Passion, Robustness and Perseverance

    DEFF Research Database (Denmark)

    Lim, Miguel Antonio; Lund, Rebecca

    2016-01-01

    Evaluation and merit in the measured university are increasingly based on taken-for-granted assumptions about the “ideal academic”. We suggest that the scholar now needs to show that she is passionate about her work and that she gains pleasure from pursuing her craft. We suggest that passion...... and pleasure achieve an exalted status as something compulsory. The scholar ought to feel passionate about her work and signal that she takes pleasure also in the difficult moments. Passion has become a signal of robustness and perseverance in a job market characterised by funding shortages, increased pressure...... way to demonstrate their potential and, crucially, their passion for their work. Drawing on the literature on technologies of governance, we reflect on what is captured and what is left out by these two evaluation instruments. We suggest that bibliometric analysis at the individual level is deeply...

  10. Robust Optical Flow Estimation

    Directory of Open Access Journals (Sweden)

    Javier Sánchez Pérez

    2013-10-01

    Full Text Available n this work, we describe an implementation of the variational method proposed by Brox etal. in 2004, which yields accurate optical flows with low running times. It has several benefitswith respect to the method of Horn and Schunck: it is more robust to the presence of outliers,produces piecewise-smooth flow fields and can cope with constant brightness changes. Thismethod relies on the brightness and gradient constancy assumptions, using the information ofthe image intensities and the image gradients to find correspondences. It also generalizes theuse of continuous L1 functionals, which help mitigate the effect of outliers and create a TotalVariation (TV regularization. Additionally, it introduces a simple temporal regularizationscheme that enforces a continuous temporal coherence of the flow fields.

  11. Robust Multimodal Dictionary Learning

    Science.gov (United States)

    Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

    2014-01-01

    We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674

  12. Robust snapshot interferometric spectropolarimetry.

    Science.gov (United States)

    Kim, Daesuk; Seo, Yoonho; Yoon, Yonghee; Dembele, Vamara; Yoon, Jae Woong; Lee, Kyu Jin; Magnusson, Robert

    2016-05-15

    This Letter describes a Stokes vector measurement method based on a snapshot interferometric common-path spectropolarimeter. The proposed scheme, which employs an interferometric polarization-modulation module, can extract the spectral polarimetric parameters Ψ(k) and Δ(k) of a transmissive anisotropic object by which an accurate Stokes vector can be calculated in the spectral domain. It is inherently strongly robust to the object 3D pose variation, since it is designed distinctly so that the measured object can be placed outside of the interferometric module. Experiments are conducted to verify the feasibility of the proposed system. The proposed snapshot scheme enables us to extract the spectral Stokes vector of a transmissive anisotropic object within tens of msec with high accuracy.

  13. International Conference on Robust Statistics

    CERN Document Server

    Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter

    2003-01-01

    Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

  14. Design of Robust Neural Network Classifiers

    DEFF Research Database (Denmark)

    Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

    1998-01-01

    This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

  15. Robust photometric stereo using structural light sources

    Science.gov (United States)

    Han, Tian-Qi; Cheng, Yue; Shen, Hui-Liang; Du, Xin

    2014-05-01

    We propose a robust photometric stereo method by using structural arrangement of light sources. In the arrangement, light sources are positioned on a planar grid and form a set of collinear combinations. The shadow pixels are detected by adaptive thresholding. The specular highlight and diffuse pixels are distinguished according to their intensity deviations of the collinear combinations, thanks to the special arrangement of light sources. The highlight detection problem is cast as a pattern classification problem and is solved using support vector machine classifiers. Considering the possible misclassification of highlight pixels, the ℓ1 regularization is further employed in normal map estimation. Experimental results on both synthetic and real-world scenes verify that the proposed method can robustly recover the surface normal maps in the case of heavy specular reflection and outperforms the state-of-the-art techniques.

  16. Comparing interval estimates for small sample ordinal CFA models.

    Science.gov (United States)

    Natesan, Prathiba

    2015-01-01

    Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading

  17. Combined Interval Training and Post-exercise Nutrition in Type 2 Diabetes: A Randomized Control Trial

    OpenAIRE

    Francois, Monique E.; Durrer, Cody; Pistawka, Kevin J.; Halperin, Frank A.; Chang, Courtney; Little, Jonathan P.

    2017-01-01

    Background: High-intensity interval training (HIIT) can improve several aspects of cardiometabolic health. Previous studies have suggested that adaptations to exercise training can be augmented with post-exercise milk or protein consumption, but whether this nutritional strategy can impact the cardiometabolic adaptations to HIIT in type 2 diabetes is unknown. Objective: To determine if the addition of a post-exercise milk or protein beverage to a high-intensity interval training (HIIT) interv...

  18. Robustness Analyses of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik

    2013-01-01

    The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...

  19. Robust Helicopter Stabilization in the Face of Wind Disturbance

    DEFF Research Database (Denmark)

    A. Danapalasingam, Kumeresan; Leth, John-Josef; la Cour-Harbo, Anders

    2010-01-01

    When a helicopter is required to hover with minimum deviations from a desired position without measurements of an affecting persistent wind disturbance, a robustly stabilizing control action is vital. In this paper, the stabilization of the position and translational velocity of a nonlinear...... controller is then designed based on nonlinear adaptive output regulations and robust stabilization of a chain of integrators by a saturated feedback. Simulation results show the effectiveness of the control design in the stabilization of helicopter motion and the built-in robustness of the controller...

  20. Tensor voting for robust color edge detection

    OpenAIRE

    Moreno, Rodrigo; García, Miguel Ángel; Puig, Domenec

    2014-01-01

    The final publication is available at Springer via http://dx.doi.org/10.1007/978-94-007-7584-8_9 This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to ...

  1. A scoping review of the psychological responses to interval exercise: is interval exercise a viable alternative to traditional exercise?

    Science.gov (United States)

    Stork, Matthew J; Banfield, Laura E; Gibala, Martin J; Martin Ginis, Kathleen A

    2017-12-01

    While considerable evidence suggests that interval exercise confers numerous physiological adaptations linked to improved health, its psychological consequences and behavioural implications are less clear and the subject of intense debate. The purpose of this scoping review was to catalogue studies investigating the psychological responses to interval exercise in order to identify what psychological outcomes have been assessed, the research methods used, and the results. A secondary objective was to identify research issues and gaps. Forty-two published articles met the review inclusion/exclusion criteria. These studies involved 1258 participants drawn from various active/inactive and healthy/unhealthy populations, and 55 interval exercise protocols (69% high-intensity interval training [HIIT], 27% sprint interval training [SIT], and 4% body-weight interval training [BWIT]). Affect and enjoyment were the most frequently studied psychological outcomes. Post-exercise assessments indicate that overall, enjoyment of, and preferences for interval exercise are equal or greater than for continuous exercise, and participants can hold relatively positive social cognitions regarding interval exercise. Although several methodological issues (e.g., inconsistent use of terminology, measures and protocols) and gaps (e.g., data on adherence and real-world protocols) require attention, from a psychological perspective, the emerging data support the viability of interval exercise as an alternative to continuous exercise.

  2. Dynamics robustness of cascading systems.

    Directory of Open Access Journals (Sweden)

    Jonathan T Young

    2017-03-01

    Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

  3. Robust continuous clustering.

    Science.gov (United States)

    Shah, Sohil Atul; Koltun, Vladlen

    2017-09-12

    Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

  4. Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures

    Directory of Open Access Journals (Sweden)

    Ionut Bebu

    2016-06-01

    Full Text Available For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR from several studies, the number needed to treat (NNT, and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities even when the sample sizes are not large. An appealing feature of the proposed solutions is that they are not based on maximization of the likelihood, and hence are free from convergence issues associated with the numerical calculation of the maximum likelihood estimators, especially in the context of the log-binomial model. The results are illustrated with a number of examples. The overall conclusion is that the proposed methodologies based on generalized pivotal quantities and fiducial quantities provide an accurate and unified approach for the interval estimation of the various epidemiological measures in the context of binary outcome data with or without covariates.

  5. Haemostatic reference intervals in pregnancy

    DEFF Research Database (Denmark)

    Szecsi, Pal Bela; Jørgensen, Maja; Klajnbard, Anna

    2010-01-01

    largely unchanged during pregnancy, delivery, and postpartum and were within non-pregnant reference intervals. However, levels of fibrinogen, D-dimer, and coagulation factors VII, VIII, and IX increased markedly. Protein S activity decreased substantially, while free protein S decreased slightly and total......Haemostatic reference intervals are generally based on samples from non-pregnant women. Thus, they may not be relevant to pregnant women, a problem that may hinder accurate diagnosis and treatment of haemostatic disorders during pregnancy. In this study, we establish gestational age......-20, 21-28, 29-34, 35-42, at active labor, and on postpartum days 1 and 2. Reference intervals for each gestational period using only the uncomplicated pregnancies were calculated in all 391 women for activated partial thromboplastin time (aPTT), fibrinogen, fibrin D-dimer, antithrombin, free protein S...

  6. Robust Trust in Expert Testimony

    Directory of Open Access Journals (Sweden)

    Christian Dahlman

    2015-05-01

    Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.

  7. Effect of smoothing on robust chaos.

    Science.gov (United States)

    Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae

    2010-08-01

    In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.

  8. Inverse Interval Matrix: A Survey

    Czech Academy of Sciences Publication Activity Database

    Rohn, Jiří; Farhadsefat, R.

    2011-01-01

    Roč. 22, - (2011), s. 704-719 E-ISSN 1081-3810 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval matrix * inverse interval matrix * NP-hardness * enclosure * unit midpoint * inverse sign stability * nonnegative invertibility * absolute value equation * algorithm Subject RIV: BA - General Mathematics Impact factor: 0.808, year: 2010 http://www.math.technion.ac.il/iic/ ela / ela -articles/articles/vol22_pp704-719.pdf

  9. Robust portfolio selection based on asymmetric measures of variability of stock returns

    Science.gov (United States)

    Chen, Wei; Tan, Shaohua

    2009-10-01

    This paper addresses a new uncertainty set--interval random uncertainty set for robust optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming to robust mean-variance portfolio selection under interval random uncertainty sets in the elements of mean vector and covariance matrix. Numerical experiments with real market data indicate that our approach results in better portfolio performance.

  10. INTERVAL STATE ESTIMATION FOR SINGULAR DIFFERENTIAL EQUATION SYSTEMS WITH DELAYS

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2016-07-01

    Full Text Available The paper deals with linear differential equation systems with algebraic restrictions (singular systems and a method of interval observer design for this kind of systems. The systems contain constant time delay, measurement noise and disturbances. Interval observer synthesis is based on monotone and cooperative systems technique, linear matrix inequations, Lyapunov function theory and interval arithmetic. The set of conditions that gives the possibility for interval observer synthesis is proposed. Results of synthesized observer operation are shown on the example of dynamical interindustry balance model. The advantages of proposed method are that it is adapted to observer design for uncertain systems, if the intervals of admissible values for uncertain parameters are given. The designed observer is capable to provide asymptotically definite limits on the estimation accuracy, since the interval of admissible values for the object state is defined at every instant. The obtained result provides an opportunity to develop the interval estimation theory for complex systems that contain parametric uncertainty, varying delay and nonlinear elements. Interval observers increasingly find applications in economics, electrical engineering, mechanical systems with constraints and optimal flow control.

  11. Dynamic Properties of QT Intervals

    Czech Academy of Sciences Publication Activity Database

    Halámek, Josef; Jurák, Pavel; Vondra, Vlastimil; Lipoldová, J.; Leinveber, Pavel; Plachý, M.; Fráňa, P.; Kára, T.

    2009-01-01

    Roč. 36, - (2009), s. 517-520 ISSN 0276-6574 R&D Projects: GA ČR GA102/08/1129; GA MŠk ME09050 Institutional research plan: CEZ:AV0Z20650511 Keywords : QT Intervals * arrhythmia diagnosis Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering http://cinc.mit.edu/archives/2009/pdf/0517.pdf

  12. Haemostatic reference intervals in pregnancy

    DEFF Research Database (Denmark)

    Szecsi, Pal Bela; Jørgensen, Maja; Klajnbard, Anna

    2010-01-01

    Haemostatic reference intervals are generally based on samples from non-pregnant women. Thus, they may not be relevant to pregnant women, a problem that may hinder accurate diagnosis and treatment of haemostatic disorders during pregnancy. In this study, we establish gestational age-specific refe......Haemostatic reference intervals are generally based on samples from non-pregnant women. Thus, they may not be relevant to pregnant women, a problem that may hinder accurate diagnosis and treatment of haemostatic disorders during pregnancy. In this study, we establish gestational age......-specific reference intervals for coagulation tests during normal pregnancy. Eight hundred one women with expected normal pregnancies were included in the study. Of these women, 391 had no complications during pregnancy, vaginal delivery, or postpartum period. Plasma samples were obtained at gestational weeks 13......-20, 21-28, 29-34, 35-42, at active labor, and on postpartum days 1 and 2. Reference intervals for each gestational period using only the uncomplicated pregnancies were calculated in all 391 women for activated partial thromboplastin time (aPTT), fibrinogen, fibrin D-dimer, antithrombin, free protein S...

  13. Interval matrices: Regularity generates singularity

    Czech Academy of Sciences Publication Activity Database

    Rohn, Jiří; Shary, S.P.

    2018-01-01

    Roč. 540, 1 March (2018), s. 149-159 ISSN 0024-3795 Institutional support: RVO:67985807 Keywords : interval matrix * regularity * singularity * P-matrix * absolute value equation * diagonally singilarizable matrix Subject RIV: BA - General Mathematics Impact factor: 0.973, year: 2016

  14. Chaotic dynamics from interspike intervals

    DEFF Research Database (Denmark)

    Pavlov, A N; Sosnovtseva, Olga; Mosekilde, Erik

    2001-01-01

    Considering two different mathematical models describing chaotic spiking phenomena, namely, an integrate-and-fire and a threshold-crossing model, we discuss the problem of extracting dynamics from interspike intervals (ISIs) and show that the possibilities of computing the largest Lyapunov expone...

  15. Reference Intervals of Common Clinical Chemistry Analytes for Adults in Hong Kong.

    Science.gov (United States)

    Lo, Y C; Armbruster, David A

    2012-04-01

    Defining reference intervals is a major challenge because of the difficulty in recruiting volunteers to participate and testing samples from a significant number of healthy reference individuals. Historical literature citation intervals are often suboptimal because they're be based on obsolete methods and/or only a small number of poorly defined reference samples. Blood donors in Hong Kong gave permission for additional blood to be collected for reference interval testing. The samples were tested for twenty-five routine analytes on the Abbott ARCHITECT clinical chemistry system. Results were analyzed using the Rhoads EP evaluator software program, which is based on the CLSI/IFCC C28-A guideline, and defines the reference interval as the 95% central range. Method specific reference intervals were established for twenty-five common clinical chemistry analytes for a Chinese ethnic population. The intervals were defined for each gender separately and for genders combined. Gender specific or combined gender intervals were adapted as appropriate for each analyte. A large number of healthy, apparently normal blood donors from a local ethnic population were tested to provide current reference intervals for a new clinical chemistry system. Intervals were determined following an accepted international guideline. Laboratories using the same or similar methodologies may adapt these intervals if deemed validated and deemed suitable for their patient population. Laboratories using different methodologies may be able to successfully adapt the intervals for their facilities using the reference interval transference technique based on a method comparison study.

  16. High-intensity interval training: Modulating interval duration in overweight/obese men.

    Science.gov (United States)

    Smith-Ryan, Abbie E; Melvin, Malia N; Wingfield, Hailee L

    2015-05-01

    High-intensity interval training (HIIT) is a time-efficient strategy shown to induce various cardiovascular and metabolic adaptations. Little is known about the optimal tolerable combination of intensity and volume necessary for adaptations, especially in clinical populations. In a randomized controlled pilot design, we evaluated the effects of two types of interval training protocols, varying in intensity and interval duration, on clinical outcomes in overweight/obese men. Twenty-five men [body mass index (BMI) > 25 kg · m(2)] completed baseline body composition measures: fat mass (FM), lean mass (LM) and percent body fat (%BF) and fasting blood glucose, lipids and insulin (IN). A graded exercise cycling test was completed for peak oxygen consumption (VO2peak) and power output (PO). Participants were randomly assigned to high-intensity short interval (1MIN-HIIT), high-intensity interval (2MIN-HIIT) or control groups. 1MIN-HIIT and 2MIN-HIIT completed 3 weeks of cycling interval training, 3 days/week, consisting of either 10 × 1 min bouts at 90% PO with 1 min rests (1MIN-HIIT) or 5 × 2 min bouts with 1 min rests at undulating intensities (80%-100%) (2MIN-HIIT). There were no significant training effects on FM (Δ1.06 ± 1.25 kg) or %BF (Δ1.13% ± 1.88%), compared to CON. Increases in LM were not significant but increased by 1.7 kg and 2.1 kg for 1MIN and 2MIN-HIIT groups, respectively. Increases in VO2peak were also not significant for 1MIN (3.4 ml·kg(-1) · min(-1)) or 2MIN groups (2.7 ml · kg(-1) · min(-1)). IN sensitivity (HOMA-IR) improved for both training groups (Δ-2.78 ± 3.48 units; p < 0.05) compared to CON. HIIT may be an effective short-term strategy to improve cardiorespiratory fitness and IN sensitivity in overweight males.

  17. Engineering Robustness of Microbial Cell Factories.

    Science.gov (United States)

    Gong, Zhiwei; Nielsen, Jens; Zhou, Yongjin J

    2017-10-01

    Metabolic engineering and synthetic biology offer great prospects in developing microbial cell factories capable of converting renewable feedstocks into fuels, chemicals, food ingredients, and pharmaceuticals. However, prohibitively low production rate and mass concentration remain the major hurdles in industrial processes even though the biosynthetic pathways are comprehensively optimized. These limitations are caused by a variety of factors unamenable for host cell survival, such as harsh industrial conditions, fermentation inhibitors from biomass hydrolysates, and toxic compounds including metabolic intermediates and valuable target products. Therefore, engineered microbes with robust phenotypes is essential for achieving higher yield and productivity. In this review, the recent advances in engineering robustness and tolerance of cell factories is described to cope with these issues and briefly introduce novel strategies with great potential to enhance the robustness of cell factories, including metabolic pathway balancing, transporter engineering, and adaptive laboratory evolution. This review also highlights the integration of advanced systems and synthetic biology principles toward engineering the harmony of overall cell function, more than the specific pathways or enzymes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Robust adaptive control of the sawtooth instability in nuclear fusion

    NARCIS (Netherlands)

    Bolder, J.J.; Witvoet, G.; Baar, de M.R.; Wouw, van de N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.; Steinbuch, M.

    2012-01-01

    The sawtooth instability is a repetitive phenomenon occurring in plasmas of tokamak nuclear fusion reactors. Experimental studies of these instabilities and the effect they have on the plasma (notably the drive of secondary instabilities and consequent performance reduction) for a wide variety of

  19. Adaptive ACMS: A robust localized Approximated Component Mode Synthesis Method

    OpenAIRE

    Madureira, Alexandre L.; Sarkis, Marcus

    2017-01-01

    We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\\infty$ coefficients. The methods are of Galerkin type and follows the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into multiscale and fine subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based...

  20. Robust object tacking based on self-adaptive search area

    Science.gov (United States)

    Dong, Taihang; Zhong, Sheng

    2018-02-01

    Discriminative correlation filter (DCF) based trackers have recently achieved excellent performance with great computational efficiency. However, DCF based trackers suffer boundary effects, which result in the unstable performance in challenging situations exhibiting fast motion. In this paper, we propose a novel method to mitigate this side-effect in DCF based trackers. We change the search area according to the prediction of target motion. When the object moves fast, broad search area could alleviate boundary effects and reserve the probability of locating object. When the object moves slowly, narrow search area could prevent effect of useless background information and improve computational efficiency to attain real-time performance. This strategy can impressively soothe boundary effects in situations exhibiting fast motion and motion blur, and it can be used in almost all DCF based trackers. The experiments on OTB benchmark show that the proposed framework improves the performance compared with the baseline trackers.

  1. Robust and Adaptive Block Tracking Method Based on Particle Filter

    Directory of Open Access Journals (Sweden)

    Bin Sun

    2015-10-01

    Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

  2. Adaptive and robust active vibration control methodology and tests

    CERN Document Server

    Landau, Ioan Doré; Castellanos-Silva, Abraham; Constantinescu, Aurelian

    2017-01-01

    This book approaches the design of active vibration control systems from the perspective of today’s ideas of computer control. It formulates the various design problems encountered in the active management of vibration as control problems and searches for the most appropriate tools to solve them. The experimental validation of the solutions proposed on relevant tests benches is also addressed. To promote the widespread acceptance of these techniques, the presentation eliminates unnecessary theoretical developments (which can be found elsewhere) and focuses on algorithms and their use. The solutions proposed cannot be fully understood and creatively exploited without a clear understanding of the basic concepts and methods, so these are considered in depth. The focus is on enhancing motivations, algorithm presentation and experimental evaluation. MATLAB®routines, Simulink® diagrams and bench-test data are available for download and encourage easy assimilation of the experimental and exemplary material. Thre...

  3. Robust Adaptive Signal Processing Methods for Heterogeneous Radar Clutter Scenarios

    National Research Council Canada - National Science Library

    Rangaswamy, Muralidhar; Lin, Freeman C; Gerlach, Karl R

    2004-01-01

    .... Specifically, we present the performance of the normalized matched filter test in a background of disturbance consisting of clutter having a covariance matrix with known structure and unknown scaling...

  4. Robust chaos synchronization based on adaptive fuzzy delayed ...

    Indian Academy of Sciences (India)

    cations in secure communication, economics, signal generator design, chemical reaction, ... that may cause instability and poor performance. ... synchronization error system is asymptotically stable with a guaranteed H∞ norm bound.

  5. Robust control of time-delay chaotic systems

    International Nuclear Information System (INIS)

    Hua Changchun; Guan Xinping

    2003-01-01

    Robust control problem of nonlinear time-delay chaotic systems is investigated. For such uncertain systems, we propose adaptive feedback controller and novel nonlinear feedback controller. They are both independent of the time delay and can render the corresponding closed-loop systems globally uniformly ultimately bounded stable. The simulations on controlling logistic system are made and the results show the controllers are feasible

  6. Robust and distributed hypothesis testing

    CERN Document Server

    Gül, Gökhan

    2017-01-01

    This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...

  7. Robustness of IPTV business models

    NARCIS (Netherlands)

    Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.

    2008-01-01

    The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we

  8. Robustness Evaluation of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2009-01-01

    Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....

  9. Robust statistical methods with R

    CERN Document Server

    Jureckova, Jana

    2005-01-01

    Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...

  10. Robust boosting via convex optimization

    Science.gov (United States)

    Rätsch, Gunnar

    2001-12-01

    In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules - also called base hypotheses. The so-called boosting algorithms iteratively find a weighted linear combination of base hypotheses that predict well on unseen data. We address the following issues: o The statistical learning theory framework for analyzing boosting methods. We study learning theoretic guarantees on the prediction performance on unseen examples. Recently, large margin classification techniques emerged as a practical result of the theory of generalization, in particular Boosting and Support Vector Machines. A large margin implies a good generalization performance. Hence, we analyze how large the margins in boosting are and find an improved algorithm that is able to generate the maximum margin solution. o How can boosting methods be related to mathematical optimization techniques? To analyze the properties of the resulting classification or regression rule, it is of high importance to understand whether and under which conditions boosting converges. We show that boosting can be used to solve large scale constrained optimization problems, whose solutions are well characterizable. To show this, we relate boosting methods to methods known from mathematical optimization, and derive convergence guarantees for a quite general family of boosting algorithms. o How to make Boosting noise robust? One of the problems of current boosting techniques is that they are sensitive to noise in the training sample. In order to make boosting robust, we transfer the soft margin idea from support vector learning to boosting. We develop theoretically motivated regularized algorithms that exhibit a high noise robustness. o How to adapt boosting to regression problems

  11. Robustly Fitting and Forecasting Dynamical Data With Electromagnetically Coupled Artificial Neural Network: A Data Compression Method.

    Science.gov (United States)

    Wang, Ziyin; Liu, Mandan; Cheng, Yicheng; Wang, Rubin

    2017-06-01

    In this paper, a dynamical recurrent artificial neural network (ANN) is proposed and studied. Inspired from a recent research in neuroscience, we introduced nonsynaptic coupling to form a dynamical component of the network. We mathematically proved that, with adequate neurons provided, this dynamical ANN model is capable of approximating any continuous dynamic system with an arbitrarily small error in a limited time interval. Its extreme concise Jacobian matrix makes the local stability easy to control. We designed this ANN for fitting and forecasting dynamic data and obtained satisfied results in simulation. The fitting performance is also compared with those of both the classic dynamic ANN and the state-of-the-art models. Sufficient trials and the statistical results indicated that our model is superior to those have been compared. Moreover, we proposed a robust approximation problem, which asking the ANN to approximate a cluster of input-output data pairs in large ranges and to forecast the output of the system under previously unseen input. Our model and learning scheme proposed in this paper have successfully solved this problem, and through this, the approximation becomes much more robust and adaptive to noise, perturbation, and low-order harmonic wave. This approach is actually an efficient method for compressing massive external data of a dynamic system into the weight of the ANN.

  12. Revisionist integral deferred correction with adaptive step-size control

    KAUST Repository

    Christlieb, Andrew; Macdonald, Colin; Ong, Benjamin; Spiteri, Raymond

    2015-01-01

    © 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step

  13. Numerically robust geometry engine for compound solid geometries

    International Nuclear Information System (INIS)

    Vlachoudis, V.; Sinuela-Pastor, D.

    2013-01-01

    Monte Carlo programs heavily rely on a fast and numerically robust solid geometry engines. However the success of solid modeling, depends on facilities for specifying and editing parameterized models through a user-friendly graphical front-end. Such a user interface has to be fast enough in order to be interactive for 2D and/or 3D displays, but at the same time numerically robust in order to display possible modeling errors at real time that could be critical for the simulation. The graphical user interface Flair for FLUKA currently employs such an engine where special emphasis has been given on being fast and numerically robust. The numerically robustness is achieved by a novel method of estimating the floating precision of the operations, which dynamically adapts all the decision operations accordingly. Moreover a predictive caching mechanism is ensuring that logical errors in the geometry description are found online, without compromising the processing time by checking all regions. (authors)

  14. Efficient and robust gradient enhanced Kriging emulators.

    Energy Technology Data Exchange (ETDEWEB)

    Dalbey, Keith R.

    2013-08-01

    %E2%80%9CNaive%E2%80%9D or straight-forward Kriging implementations can often perform poorly in practice. The relevant features of the robustly accurate and efficient Kriging and Gradient Enhanced Kriging (GEK) implementations in the DAKOTA software package are detailed herein. The principal contribution is a novel, effective, and efficient approach to handle ill-conditioning of GEK's %E2%80%9Ccorrelation%E2%80%9D matrix, RN%CC%83, based on a pivoted Cholesky factorization of Kriging's (not GEK's) correlation matrix, R, which is a small sub-matrix within GEK's RN%CC%83 matrix. The approach discards sample points/equations that contribute the least %E2%80%9Cnew%E2%80%9D information to RN%CC%83. Since these points contain the least new information, they are the ones which when discarded are both the easiest to predict and provide maximum improvement of RN%CC%83's conditioning. Prior to this work, handling ill-conditioned correlation matrices was a major, perhaps the principal, unsolved challenge necessary for robust and efficient GEK emulators. Numerical results demonstrate that GEK predictions can be significantly more accurate when GEK is allowed to discard points by the presented method. Numerical results also indicate that GEK can be used to break the curse of dimensionality by exploiting inexpensive derivatives (such as those provided by automatic differentiation or adjoint techniques), smoothness in the response being modeled, and adaptive sampling. Development of a suitable adaptive sampling algorithm was beyond the scope of this work; instead adaptive sampling was approximated by omitting the cost of samples discarded by the presented pivoted Cholesky approach.

  15. Robust loss functions for boosting.

    Science.gov (United States)

    Kanamori, Takafumi; Takenouchi, Takashi; Eguchi, Shinto; Murata, Noboru

    2007-08-01

    Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.

  16. Theoretical Framework for Robustness Evaluation

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2011-01-01

    This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...

  17. Robustness of airline route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

    2016-03-01

    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  18. Statistical intervals a guide for practitioners

    CERN Document Server

    Hahn, Gerald J

    2011-01-01

    Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric stati

  19. A Maximum Entropy Method for a Robust Portfolio Problem

    Directory of Open Access Journals (Sweden)

    Yingying Xu

    2014-06-01

    Full Text Available We propose a continuous maximum entropy method to investigate the robustoptimal portfolio selection problem for the market with transaction costs and dividends.This robust model aims to maximize the worst-case portfolio return in the case that allof asset returns lie within some prescribed intervals. A numerical optimal solution tothe problem is obtained by using a continuous maximum entropy method. Furthermore,some numerical experiments indicate that the robust model in this paper can result in betterportfolio performance than a classical mean-variance model.

  20. Dijets at large rapidity intervals

    CERN Document Server

    Pope, B G

    2001-01-01

    Inclusive diet production at large pseudorapidity intervals ( Delta eta ) between the two jets has been suggested as a regime for observing BFKL dynamics. We have measured the dijet cross section for large Delta eta in pp collisions at square root s = 1800 and 630 GeV using the DOE detector. The partonic cross section increases strongly with the size of Delta eta . The observed growth is even stronger than expected on the basis of BFKL resummation in the leading logarithmic approximation. The growth of the partonic cross section can be accommodated with an effective BFKL intercept of alpha /sub BFKL/(20 GeV) = 1.65 +or- 0.07.

  1. Variational collocation on finite intervals

    International Nuclear Information System (INIS)

    Amore, Paolo; Cervantes, Mayra; Fernandez, Francisco M

    2007-01-01

    In this paper, we study a set of functions, defined on an interval of finite width, which are orthogonal and which reduce to the sinc functions when the appropriate limit is taken. We show that these functions can be used within a variational approach to obtain accurate results for a variety of problems. We have applied them to the interpolation of functions on finite domains and to the solution of the Schroedinger equation, and we have compared the performance of the present approach with others

  2. Robust Portfolio Optimization Using Pseudodistances.

    Science.gov (United States)

    Toma, Aida; Leoni-Aubin, Samuela

    2015-01-01

    The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

  3. Robust methods for data reduction

    CERN Document Server

    Farcomeni, Alessio

    2015-01-01

    Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

  4. Multi-focus Image Fusion Using Epifluorescence Microscopy for Robust Vascular Segmentation

    OpenAIRE

    Pelapur, Rengarajan; Prasath, Surya; Palaniappan, Kannappan

    2014-01-01

    We are building a computerized image analysis system for Dura Mater vascular network from fluorescence microscopy images. We propose a system that couples a multi-focus image fusion module with a robust adaptive filtering based segmentation. The robust adaptive filtering scheme handles noise without destroying small structures, and the multi focal image fusion considerably improves the overall segmentation quality by integrating information from multiple images. Based on the segmenta...

  5. Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

    Science.gov (United States)

    Burken, John J.

    2005-01-01

    This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

  6. Many-objective robust decision making for water allocation under climate change

    NARCIS (Netherlands)

    Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E.

    2017-01-01

    Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large

  7. Some Characterizations of Convex Interval Games

    NARCIS (Netherlands)

    Brânzei, R.; Tijs, S.H.; Alparslan-Gok, S.Z.

    2008-01-01

    This paper focuses on new characterizations of convex interval games using the notions of exactness and superadditivity. We also relate big boss interval games with concave interval games and obtain characterizations of big boss interval games in terms of exactness and subadditivity.

  8. Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Hua

    2018-03-01

    Full Text Available This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.

  9. Robust Optimal Design of Quantum Electronic Devices

    Directory of Open Access Journals (Sweden)

    Ociel Morales

    2018-01-01

    Full Text Available We consider the optimal design of a sequence of quantum barriers, in order to manufacture an electronic device at the nanoscale such that the dependence of its transmission coefficient on the bias voltage is linear. The technique presented here is easily adaptable to other response characteristics. There are two distinguishing features of our approach. First, the transmission coefficient is determined using a semiclassical approximation, so we can explicitly compute the gradient of the objective function. Second, in contrast with earlier treatments, manufacturing uncertainties are incorporated in the model through random variables; the optimal design problem is formulated in a probabilistic setting and then solved using a stochastic collocation method. As a measure of robustness, a weighted sum of the expectation and the variance of a least-squares performance metric is considered. Several simulations illustrate the proposed technique, which shows an improvement in accuracy over 69% with respect to brute-force, Monte-Carlo-based methods.

  10. Robust design optimization using the price of robustness, robust least squares and regularization methods

    Science.gov (United States)

    Bukhari, Hassan J.

    2017-12-01

    In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

  11. A robust multilevel simultaneous eigenvalue solver

    Science.gov (United States)

    Costiner, Sorin; Taasan, Shlomo

    1993-01-01

    Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

  12. Robust hashing for 3D models

    Science.gov (United States)

    Berchtold, Waldemar; Schäfer, Marcel; Rettig, Michael; Steinebach, Martin

    2014-02-01

    3D models and applications are of utmost interest in both science and industry. With the increment of their usage, their number and thereby the challenge to correctly identify them increases. Content identification is commonly done by cryptographic hashes. However, they fail as a solution in application scenarios such as computer aided design (CAD), scientific visualization or video games, because even the smallest alteration of the 3D model, e.g. conversion or compression operations, massively changes the cryptographic hash as well. Therefore, this work presents a robust hashing algorithm for 3D mesh data. The algorithm applies several different bit extraction methods. They are built to resist desired alterations of the model as well as malicious attacks intending to prevent correct allocation. The different bit extraction methods are tested against each other and, as far as possible, the hashing algorithm is compared to the state of the art. The parameters tested are robustness, security and runtime performance as well as False Acceptance Rate (FAR) and False Rejection Rate (FRR), also the probability calculation of hash collision is included. The introduced hashing algorithm is kept adaptive e.g. in hash length, to serve as a proper tool for all applications in practice.

  13. On the possible role of robustness in the evolution of infectious diseases

    Science.gov (United States)

    Ogbunugafor, C. Brandon; Pease, James B.; Turner, Paul E.

    2010-06-01

    Robustness describes the capacity for a biological system to remain canalized despite perturbation. Genetic robustness affords maintenance of phenotype despite mutational input, necessarily involving the role of epistasis. Environmental robustness is phenotypic constancy in the face of environmental variation, where epistasis may be uninvolved. Here we discuss genetic and environmental robustness, from the standpoint of infectious disease evolution, and suggest that robustness may be a unifying principle for understanding how different disease agents evolve. We focus especially on viruses with RNA genomes due to their importance in the evolution of emerging diseases and as model systems to test robustness theory. We present new data on adaptive constraints for a model RNA virus challenged to evolve in response to UV radiation. We also draw attention to other infectious disease systems where robustness theory may prove useful for bridging evolutionary biology and biomedicine, especially the evolution of antibiotic resistance in bacteria, immune evasion by influenza, and malaria parasite infections.

  14. Statistical coding and decoding of heartbeat intervals.

    Science.gov (United States)

    Lucena, Fausto; Barros, Allan Kardec; Príncipe, José C; Ohnishi, Noboru

    2011-01-01

    The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

  15. Statistical coding and decoding of heartbeat intervals.

    Directory of Open Access Journals (Sweden)

    Fausto Lucena

    Full Text Available The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

  16. Advances in robust fractional control

    CERN Document Server

    Padula, Fabrizio

    2015-01-01

    This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially-oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, becau...

  17. Robustness of digital artist authentication

    DEFF Research Database (Denmark)

    Jacobsen, Robert; Nielsen, Morten

    In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....

  18. Attractive ellipsoids in robust control

    CERN Document Server

    Poznyak, Alexander; Azhmyakov, Vadim

    2014-01-01

    This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will a...

  19. Robustness of holonomic quantum gates

    International Nuclear Information System (INIS)

    Solinas, P.; Zanardi, P.; Zanghi, N.

    2005-01-01

    Full text: If the driving field fluctuates during the quantum evolution this produces errors in the applied operator. The holonomic (and geometrical) quantum gates are believed to be robust against some kind of noise. Because of the geometrical dependence of the holonomic operators can be robust against this kind of noise; in fact if the fluctuations are fast enough they cancel out leaving the final operator unchanged. I present the numerical studies of holonomic quantum gates subject to this parametric noise, the fidelity of the noise and ideal evolution is calculated for different noise correlation times. The holonomic quantum gates seem robust not only for fast fluctuating fields but also for slow fluctuating fields. These results can be explained as due to the geometrical feature of the holonomic operator: for fast fluctuating fields the fluctuations are canceled out, for slow fluctuating fields the fluctuations do not perturb the loop in the parameter space. (author)

  20. Robust estimation and hypothesis testing

    CERN Document Server

    Tiku, Moti L

    2004-01-01

    In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...

  1. A Robust Design Applicability Model

    DEFF Research Database (Denmark)

    Ebro, Martin; Lars, Krogstie; Howard, Thomas J.

    2015-01-01

    to be applicable in organisations assigning a high importance to one or more factors that are known to be impacted by RD, while also experiencing a high level of occurrence of this factor. The RDAM supplements existing maturity models and metrics to provide a comprehensive set of data to support management......This paper introduces a model for assessing the applicability of Robust Design (RD) in a project or organisation. The intention of the Robust Design Applicability Model (RDAM) is to provide support for decisions by engineering management considering the relevant level of RD activities...

  2. Ins-Robust Primitive Words

    OpenAIRE

    Srivastava, Amit Kumar; Kapoor, Kalpesh

    2017-01-01

    Let Q be the set of primitive words over a finite alphabet with at least two symbols. We characterize a class of primitive words, Q_I, referred to as ins-robust primitive words, which remain primitive on insertion of any letter from the alphabet and present some properties that characterizes words in the set Q_I. It is shown that the language Q_I is dense. We prove that the language of primitive words that are not ins-robust is not context-free. We also present a linear time algorithm to reco...

  3. Adaptive Education.

    Science.gov (United States)

    Anderson, Lorin W.

    1979-01-01

    Schools have devised several ways to adapt instruction to a wide variety of student abilities and needs. Judged by criteria for what adaptive education should be, most learning for mastery programs look good. (Author/JM)

  4. Time-variant random interval natural frequency analysis of structures

    Science.gov (United States)

    Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

    2018-02-01

    This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

  5. Essays on robust asset pricing

    NARCIS (Netherlands)

    Horváth, Ferenc

    2017-01-01

    The central concept of this doctoral dissertation is robustness. I analyze how model and parameter uncertainty affect financial decisions of investors and fund managers, and what their equilibrium consequences are. Chapter 1 gives an overview of the most important concepts and methodologies used in

  6. Robust visual hashing via ICA

    International Nuclear Information System (INIS)

    Fournel, Thierry; Coltuc, Daniela

    2010-01-01

    Designed to maximize information transmission in the presence of noise, independent component analysis (ICA) could appear in certain circumstances as a statistics-based tool for robust visual hashing. Several ICA-based scenarios can attempt to reach this goal. A first one is here considered.

  7. Robustness of raw quantum tomography

    Science.gov (United States)

    Asorey, M.; Facchi, P.; Florio, G.; Man'ko, V. I.; Marmo, G.; Pascazio, S.; Sudarshan, E. C. G.

    2011-01-01

    We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.

  8. Robustness of raw quantum tomography

    Energy Technology Data Exchange (ETDEWEB)

    Asorey, M. [Departamento de Fisica Teorica, Facultad de Ciencias, Universidad de Zaragoza, 50009 Zaragoza (Spain); Facchi, P. [Dipartimento di Matematica, Universita di Bari, I-70125 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Florio, G. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Man' ko, V.I., E-mail: manko@lebedev.r [P.N. Lebedev Physical Institute, Leninskii Prospect 53, Moscow 119991 (Russian Federation); Marmo, G. [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , I-80126 Napoli (Italy); INFN, Sezione di Napoli, I-80126 Napoli (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Pascazio, S. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Sudarshan, E.C.G. [Department of Physics, University of Texas, Austin, TX 78712 (United States)

    2011-01-31

    We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.

  9. Aspects of robust linear regression

    NARCIS (Netherlands)

    Davies, P.L.

    1993-01-01

    Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact

  10. Manipulation Robustness of Collaborative Filtering

    OpenAIRE

    Benjamin Van Roy; Xiang Yan

    2010-01-01

    A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions and hence have become targets of manipulation by unscrupulous vendors. We demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust.

  11. Robustness Regions for Dichotomous Decisions.

    Science.gov (United States)

    Vijn, Pieter; Molenaar, Ivo W.

    1981-01-01

    In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

  12. Theoretical Framework for Robustness Evaluation

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2011-01-01

    This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, althou...

  13. Robust control design with MATLAB

    CERN Document Server

    Gu, Da-Wei; Konstantinov, Mihail M

    2013-01-01

    Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: ·        rewritten and simplified presentation of theoretical and meth...

  14. Robust Portfolio Optimization Using Pseudodistances

    Science.gov (United States)

    2015-01-01

    The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

  15. Facial Symmetry in Robust Anthropometrics

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 57, č. 3 (2012), s. 691-698 ISSN 0022-1198 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : forensic science * anthropology * robust image analysis * correlation analysis * multivariate data * classification Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.244, year: 2012

  16. Sparse and Robust Factor Modelling

    NARCIS (Netherlands)

    C. Croux (Christophe); P. Exterkate (Peter)

    2011-01-01

    textabstractFactor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having

  17. Robust distributed cognitive relay beamforming

    KAUST Repository

    Pandarakkottilil, Ubaidulla; Aissa, Sonia

    2012-01-01

    design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can

  18. Approximability of Robust Network Design

    NARCIS (Netherlands)

    Olver, N.K.; Shepherd, F.B.

    2014-01-01

    We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the

  19. Using the confidence interval confidently.

    Science.gov (United States)

    Hazra, Avijit

    2017-10-01

    Biomedical research is seldom done with entire populations but rather with samples drawn from a population. Although we work with samples, our goal is to describe and draw inferences regarding the underlying population. It is possible to use a sample statistic and estimates of error in the sample to get a fair idea of the population parameter, not as a single value, but as a range of values. This range is the confidence interval (CI) which is estimated on the basis of a desired confidence level. Calculation of the CI of a sample statistic takes the general form: CI = Point estimate ± Margin of error, where the margin of error is given by the product of a critical value (z) derived from the standard normal curve and the standard error of point estimate. Calculation of the standard error varies depending on whether the sample statistic of interest is a mean, proportion, odds ratio (OR), and so on. The factors affecting the width of the CI include the desired confidence level, the sample size and the variability in the sample. Although the 95% CI is most often used in biomedical research, a CI can be calculated for any level of confidence. A 99% CI will be wider than 95% CI for the same sample. Conflict between clinical importance and statistical significance is an important issue in biomedical research. Clinical importance is best inferred by looking at the effect size, that is how much is the actual change or difference. However, statistical significance in terms of P only suggests whether there is any difference in probability terms. Use of the CI supplements the P value by providing an estimate of actual clinical effect. Of late, clinical trials are being designed specifically as superiority, non-inferiority or equivalence studies. The conclusions from these alternative trial designs are based on CI values rather than the P value from intergroup comparison.

  20. Designing Robustness to Temperature in a Feedforward Loop Circuit

    OpenAIRE

    Sen, Shaunak; Kim, Jongmin; Murray, Richard M.

    2013-01-01

    Incoherent feedforward loops represent important biomolecular circuit elements capable of a rich set of dynamic behavior including adaptation and pulsed responses. Temperature can modulate some of these properties through its effect on the underlying reaction rate parameters. It is generally unclear how to design such a circuit where the properties are robust to variations in temperature. Here, we address this issue using a combination of tools from control and dynamical systems theory as wel...

  1. Direct Interval Forecasting of Wind Power

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Pinson, Pierre

    2013-01-01

    This letter proposes a novel approach to directly formulate the prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization, where prediction intervals are generated through direct optimization of both the coverage probability and sharpness...

  2. A note on birth interval distributions

    International Nuclear Information System (INIS)

    Shrestha, G.

    1989-08-01

    A considerable amount of work has been done regarding the birth interval analysis in mathematical demography. This paper is prepared with the intention of reviewing some probability models related to interlive birth intervals proposed by different researchers. (author). 14 refs

  3. Delay-Dependent Guaranteed Cost H∞ Control of an Interval System with Interval Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Zhongke Shi

    2009-01-01

    Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost H∞ control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

  4. Optimal Data Interval for Estimating Advertising Response

    OpenAIRE

    Gerard J. Tellis; Philip Hans Franses

    2006-01-01

    The abundance of highly disaggregate data (e.g., at five-second intervals) raises the question of the optimal data interval to estimate advertising carryover. The literature assumes that (1) the optimal data interval is the interpurchase time, (2) too disaggregate data causes a disaggregation bias, and (3) recovery of true parameters requires assumption of the underlying advertising process. In contrast, we show that (1) the optimal data interval is what we call , (2) too disaggregate data do...

  5. An Adequate First Order Logic of Intervals

    DEFF Research Database (Denmark)

    Chaochen, Zhou; Hansen, Michael Reichhardt

    1998-01-01

    This paper introduces left and right neighbourhoods as primitive interval modalities to define other unary and binary modalities of intervals in a first order logic with interval length. A complete first order logic for the neighbourhood modalities is presented. It is demonstrated how the logic can...... support formal specification and verification of liveness and fairness, and also of various notions of real analysis....

  6. Consistency and refinement for Interval Markov Chains

    DEFF Research Database (Denmark)

    Delahaye, Benoit; Larsen, Kim Guldstrand; Legay, Axel

    2012-01-01

    Interval Markov Chains (IMC), or Markov Chains with probability intervals in the transition matrix, are the base of a classic specification theory for probabilistic systems [18]. The standard semantics of IMCs assigns to a specification the set of all Markov Chains that satisfy its interval...

  7. Multivariate interval-censored survival data

    DEFF Research Database (Denmark)

    Hougaard, Philip

    2014-01-01

    Interval censoring means that an event time is only known to lie in an interval (L,R], with L the last examination time before the event, and R the first after. In the univariate case, parametric models are easily fitted, whereas for non-parametric models, the mass is placed on some intervals, de...

  8. Adaptive Lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper

    2015-01-01

    Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled in ways that meaningfully adapt according to people’s situations and design intentions. This book discusses...... differently into an architectural body. We also examine what might occur when light is dynamic and able to change colour, intensity and direction, and when it is adaptive and can be brought into interaction with its surroundings. In short, what happens to an architectural space when artificial lighting ceases...

  9. Robust Reliability or reliable robustness? - Integrated consideration of robustness and reliability aspects

    DEFF Research Database (Denmark)

    Kemmler, S.; Eifler, Tobias; Bertsche, B.

    2015-01-01

    products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...

  10. Adaptive vehicle motion estimation and prediction

    Science.gov (United States)

    Zhao, Liang; Thorpe, Chuck E.

    1999-01-01

    Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

  11. Robust Watermarking of Video Streams

    Directory of Open Access Journals (Sweden)

    T. Polyák

    2006-01-01

    Full Text Available In the past few years there has been an explosion in the use of digital video data. Many people have personal computers at home, and with the help of the Internet users can easily share video files on their computer. This makes possible the unauthorized use of digital media, and without adequate protection systems the authors and distributors have no means to prevent it.Digital watermarking techniques can help these systems to be more effective by embedding secret data right into the video stream. This makes minor changes in the frames of the video, but these changes are almost imperceptible to the human visual system. The embedded information can involve copyright data, access control etc. A robust watermark is resistant to various distortions of the video, so it cannot be removed without affecting the quality of the host medium. In this paper I propose a video watermarking scheme that fulfills the requirements of a robust watermark. 

  12. Robust Decentralized Formation Flight Control

    Directory of Open Access Journals (Sweden)

    Zhao Weihua

    2011-01-01

    Full Text Available Motivated by the idea of multiplexed model predictive control (MMPC, this paper introduces a new framework for unmanned aerial vehicles (UAVs formation flight and coordination. Formulated using MMPC approach, the whole centralized formation flight system is considered as a linear periodic system with control inputs of each UAV subsystem as its periodic inputs. Divided into decentralized subsystems, the whole formation flight system is guaranteed stable if proper terminal cost and terminal constraints are added to each decentralized MPC formulation of the UAV subsystem. The decentralized robust MPC formulation for each UAV subsystem with bounded input disturbances and model uncertainties is also presented. Furthermore, an obstacle avoidance control scheme for any shape and size of obstacles, including the nonapriorily known ones, is integrated under the unified MPC framework. The results from simulations demonstrate that the proposed framework can successfully achieve robust collision-free formation flights.

  13. Inefficient but robust public leadership.

    OpenAIRE

    Matsumura, Toshihiro; Ogawa, Akira

    2014-01-01

    We investigate endogenous timing in a mixed duopoly in a differentiated product market. We find that private leadership is better than public leadership from a social welfare perspective if the private firm is domestic, regardless of the degree of product differentiation. Nevertheless, the public leadership equilibrium is risk-dominant, and it is thus robust if the degree of product differentiation is high. We also find that regardless of the degree of product differentiation, the public lead...

  14. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  15. Robust power system frequency control

    CERN Document Server

    Bevrani, Hassan

    2014-01-01

    This updated edition of the industry standard reference on power system frequency control provides practical, systematic and flexible algorithms for regulating load frequency, offering new solutions to the technical challenges introduced by the escalating role of distributed generation and renewable energy sources in smart electric grids. The author emphasizes the physical constraints and practical engineering issues related to frequency in a deregulated environment, while fostering a conceptual understanding of frequency regulation and robust control techniques. The resulting control strategi

  16. ADAPT Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Diagnostics and Prognostics Testbed (ADAPT) Project Lead: Scott Poll Subject Fault diagnosis in electrical power systems Description The Advanced...

  17. Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

    Science.gov (United States)

    Steiner, Christopher F.

    2012-01-01

    The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

  18. Himalayan Adaptation, Water, and Resilience | CRDI - Centre de ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    To help the people of Pakistan, India, Bangladesh, and Nepal adapt, this project will develop robust evidence to inform climate change adaptation policies and practices. ... -promote decision-makers' use of knowledge and adaptation practices at various scales to reduce vulnerabilities and build livelihood resilience; and

  19. Robust Optimization for Time-Cost Tradeoff Problem in Construction Projects

    OpenAIRE

    Li, Ming; Wu, Guangdong

    2014-01-01

    Construction projects are generally subject to uncertainty, which influences the realization of time-cost tradeoff in project management. This paper addresses a time-cost tradeoff problem under uncertainty, in which activities in projects can be executed in different construction modes corresponding to specified time and cost with interval uncertainty. Based on multiobjective robust optimization method, a robust optimization model for time-cost tradeoff problem is developed. In order to illus...

  20. Probability Distribution for Flowing Interval Spacing

    International Nuclear Information System (INIS)

    Kuzio, S.

    2001-01-01

    The purpose of this analysis is to develop a probability distribution for flowing interval spacing. A flowing interval is defined as a fractured zone that transmits flow in the Saturated Zone (SZ), as identified through borehole flow meter surveys (Figure 1). This analysis uses the term ''flowing interval spacing'' as opposed to fractured spacing, which is typically used in the literature. The term fracture spacing was not used in this analysis because the data used identify a zone (or a flowing interval) that contains fluid-conducting fractures but does not distinguish how many or which fractures comprise the flowing interval. The flowing interval spacing is measured between the midpoints of each flowing interval. Fracture spacing within the SZ is defined as the spacing between fractures, with no regard to which fractures are carrying flow. The Development Plan associated with this analysis is entitled, ''Probability Distribution for Flowing Interval Spacing'', (CRWMS M and O 2000a). The parameter from this analysis may be used in the TSPA SR/LA Saturated Zone Flow and Transport Work Direction and Planning Documents: (1) ''Abstraction of Matrix Diffusion for SZ Flow and Transport Analyses'' (CRWMS M and O 1999a) and (2) ''Incorporation of Heterogeneity in SZ Flow and Transport Analyses'', (CRWMS M and O 1999b). A limitation of this analysis is that the probability distribution of flowing interval spacing may underestimate the effect of incorporating matrix diffusion processes in the SZ transport model because of the possible overestimation of the flowing interval spacing. Larger flowing interval spacing results in a decrease in the matrix diffusion processes. This analysis may overestimate the flowing interval spacing because the number of fractures that contribute to a flowing interval cannot be determined from the data. Because each flowing interval probably has more than one fracture contributing to a flowing interval, the true flowing interval spacing could be

  1. Robustness Analysis of Timber Truss Structure

    DEFF Research Database (Denmark)

    Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning

    2010-01-01

    The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....

  2. Robust nonlinear control of nuclear reactors under model uncertainty

    International Nuclear Information System (INIS)

    Park, Moon Ghu

    1993-02-01

    A nonlinear model-based control method is developed for the robust control of a nuclear reactor. The nonlinear plant model is used to design a unique control law which covers a wide operating range. The robustness is a crucial factor for the fully automatic control of reactor power due to time-varying, uncertain parameters, and state estimation error, or unmodeled dynamics. A variable structure control (VSC) method is introduced which consists of an adaptive performance specification (fime control) after the tracking error reaches the narrow boundary-layer by a time-optimal control (coarse control). Variable structure control is a powerful method for nonlinear system controller design which has inherent robustness to parameter variations or external disturbances using the known uncertainty bounds, and it requires very low computational efforts. In spite of its desirable properties, conventional VSC presents several important drawbacks that limit its practical applicability. One of the most undesirable phenomena is chattering, which implies extremely high control activity and may excite high-frequency unmodeled dynamics. This problem is due to the neglected actuator time-delay or sampling effects. The problem was partially remedied by replacing chattering control by a smooth control inter-polation in a boundary layer neighnboring a time-varying sliding surface. But, for the nuclear reactor systems which has very fast dynamic response, the sampling effect may destroy the narrow boundary layer when a large uncertainty bound is used. Due to the very short neutron life time, large uncertainty bound leads to the high gain in feedback control. To resolve this problem, a derivative feedback is introduced that gives excellent performance by reducing the uncertainty bound. The stability of tracking error dynamics is guaranteed by the second method of Lyapunov using the two-level uncertainty bounds that are obtained from the knowledge of uncertainty bound and the estimated

  3. Correct Bayesian and frequentist intervals are similar

    International Nuclear Information System (INIS)

    Atwood, C.L.

    1986-01-01

    This paper argues that Bayesians and frequentists will normally reach numerically similar conclusions, when dealing with vague data or sparse data. It is shown that both statistical methodologies can deal reasonably with vague data. With sparse data, in many important practical cases Bayesian interval estimates and frequentist confidence intervals are approximately equal, although with discrete data the frequentist intervals are somewhat longer. This is not to say that the two methodologies are equally easy to use: The construction of a frequentist confidence interval may require new theoretical development. Bayesians methods typically require numerical integration, perhaps over many variables. Also, Bayesian can easily fall into the trap of over-optimism about their amount of prior knowledge. But in cases where both intervals are found correctly, the two intervals are usually not very different. (orig.)

  4. Restricted Interval Valued Neutrosophic Sets and Restricted Interval Valued Neutrosophic Topological Spaces

    Directory of Open Access Journals (Sweden)

    Anjan Mukherjee

    2016-08-01

    Full Text Available In this paper we introduce the concept of restricted interval valued neutrosophic sets (RIVNS in short. Some basic operations and properties of RIVNS are discussed. The concept of restricted interval valued neutrosophic topology is also introduced together with restricted interval valued neutrosophic finer and restricted interval valued neutrosophic coarser topology. We also define restricted interval valued neutrosophic interior and closer of a restricted interval valued neutrosophic set. Some theorems and examples are cites. Restricted interval valued neutrosophic subspace topology is also studied.

  5. Ambiguous Adaptation

    DEFF Research Database (Denmark)

    Møller Larsen, Marcus; Lyngsie, Jacob

    2017-01-01

    We investigate the connection between contract duration, relational mechanisms, and premature relationship termination. Based on an analysis of a large sample of exchange relationships in the global service-provider industry, we argue that investments in either longer contract duration or more in...... ambiguous reference points for adaption and thus increase the likelihood of premature termination by restricting the parties' set of adaptive actions....

  6. Climate adaptation

    Science.gov (United States)

    Kinzig, Ann P.

    2015-03-01

    This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.

  7. Soliton robustness in optical fibers

    International Nuclear Information System (INIS)

    Menyuk, C.R.

    1993-01-01

    Simulations and experiments indicate that solitons in optical fibers are robust in the presence of Hamiltonian deformations such as higher-order dispersion and birefringence but are destroyed in the presence of non-Hamiltonian deformations such as attenuation and the Raman effect. Two hypotheses are introduced that generalize these observations and give a recipe for when deformations will be Hamiltonian. Concepts from nonlinear dynamics are used to make these two hypotheses plausible. Soliton stabilization with frequency filtering is also briefly discussed from this point of view

  8. Robust and Sparse Factor Modelling

    DEFF Research Database (Denmark)

    Croux, Christophe; Exterkate, Peter

    Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...

  9. Robustness Evaluation of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; čizmar, D.

    2010-01-01

    The present paper outlines results from working group 3 (WG3) in the EU COST Action E55 – ‘Modelling of the performance of timber structures’. The objectives of the project are related to the three main research activities: the identification and modelling of relevant load and environmental...... exposure scenarios, the improvement of knowledge concerning the behaviour of timber structural elements and the development of a generic framework for the assessment of the life-cycle vulnerability and robustness of timber structures....

  10. Sustainable Resilient, Robust & Resplendent Enterprises

    DEFF Research Database (Denmark)

    Edgeman, Rick

    to their impact. Resplendent enterprises are introduced with resplendence referring not to some sort of public or private façade, but instead refers to organizations marked by dual brilliance and nobility of strategy, governance and comportment that yields superior and sustainable triple bottom line performance....... Herein resilience, robustness, and resplendence (R3) are integrated with sustainable enterprise excellence (Edgeman and Eskildsen, 2013) or SEE and social-ecological innovation (Eskildsen and Edgeman, 2012) to aid progress of a firm toward producing continuously relevant performance that proceed from...

  11. Adaptive steganography

    Science.gov (United States)

    Chandramouli, Rajarathnam; Li, Grace; Memon, Nasir D.

    2002-04-01

    Steganalysis techniques attempt to differentiate between stego-objects and cover-objects. In recent work we developed an explicit analytic upper bound for the steganographic capacity of LSB based steganographic techniques for a given false probability of detection. In this paper we look at adaptive steganographic techniques. Adaptive steganographic techniques take explicit steps to escape detection. We explore different techniques that can be used to adapt message embedding to the image content or to a known steganalysis technique. We investigate the advantages of adaptive steganography within an analytical framework. We also give experimental results with a state-of-the-art steganalysis technique demonstrating that adaptive embedding results in a significant number of bits embedded without detection.

  12. Adaptive Lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper

    2015-01-01

    the investigations of lighting scenarios carried out in two test installations: White Cube and White Box. The test installations are discussed as large-scale experiential instruments. In these test installations we examine what could potentially occur when light using LED technology is integrated and distributed......Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... differently into an architectural body. We also examine what might occur when light is dynamic and able to change colour, intensity and direction, and when it is adaptive and can be brought into interaction with its surroundings. In short, what happens to an architectural space when artificial lighting ceases...

  13. Robust Instrumentation[Water treatment for power plant]; Robust Instrumentering

    Energy Technology Data Exchange (ETDEWEB)

    Wik, Anders [Vattenfall Utveckling AB, Stockholm (Sweden)

    2003-08-01

    Cementa Slite Power Station is a heat recovery steam generator (HRSG) with moderate steam data; 3.0 MPa and 420 deg C. The heat is recovered from Cementa, a cement industry, without any usage of auxiliary fuel. The Power station commenced operation in 2001. The layout of the plant is unusual, there are no similar in Sweden and very few world-wide, so the operational experiences are limited. In connection with the commissioning of the power plant a R and D project was identified with the objective to minimise the manpower needed for chemistry management of the plant. The lean chemistry management is based on robust instrumentation and chemical-free water treatment plant. The concept with robust instrumentation consists of the following components; choice of on-line instrumentation with a minimum of O and M and a chemical-free water treatment. The parameters are specific conductivity, cation conductivity, oxygen and pH. In addition to that, two fairly new on-line instruments were included; corrosion monitors and differential pH calculated from specific and cation conductivity. The chemical-free water treatment plant consists of softening, reverse osmosis and electro-deionisation. The operational experience shows that the cycle chemistry is not within the guidelines due to major problems with the operation of the power plant. These problems have made it impossible to reach steady state and thereby not viable to fully verify and validate the concept with robust instrumentation. From readings on the panel of the online analysers some conclusions may be drawn, e.g. the differential pH measurements have fulfilled the expectations. The other on-line analysers have been working satisfactorily apart from contamination with turbine oil, which has been noticed at least twice. The corrosion monitors seem to be working but the lack of trend curves from the mainframe computer system makes it hard to draw any clear conclusions. The chemical-free water treatment has met all

  14. Adaptation improves face trustworthiness discrimination

    Directory of Open Access Journals (Sweden)

    Bruce D Keefe

    2013-06-01

    Full Text Available Adaptation to facial characteristics, such as gender and viewpoint, has been shown to both bias our perception of faces and improve facial discrimination. In this study, we examined whether adapting to two levels of face trustworthiness improved sensitivity around the adapted level. Facial trustworthiness was manipulated by morphing between trustworthy and untrustworthy prototypes, each generated by morphing eight trustworthy and eight untrustworthy faces respectively. In the first experiment, just-noticeable differences (JNDs were calculated for an untrustworthy face after participants adapted to an untrustworthy face, a trustworthy face, or did not adapt. In the second experiment, the three conditions were identical, except that JNDs were calculated for a trustworthy face. In the third experiment we examined whether adapting to an untrustworthy male face improved discrimination to an untrustworthy female face. In all experiments, participants completed a two-interval forced-choice adaptive staircase procedure, in which they judged which face was more untrustworthy. JNDs were derived from a psychometric function fitted to the data. Adaptation improved sensitivity to faces conveying the same level of trustworthiness when compared to no adaptation. When adapting to and discriminating around a different level of face trustworthiness there was no improvement in sensitivity and JNDs were equivalent to those in the no adaptation condition. The improvement in sensitivity was found to occur even when adapting to a face with different gender and identity. These results suggest that adaptation to facial trustworthiness can selectively enhance mechanisms underlying the coding of facial trustworthiness to improve perceptual sensitivity. These findings have implications for the role of our visual experience in the decisions we make about the trustworthiness of other individuals.

  15. Adaptive Controller Effects on Pilot Behavior

    Science.gov (United States)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  16. Perspective: Evolution and detection of genetic robustness

    NARCIS (Netherlands)

    Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.

    2003-01-01

    Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms

  17. Robust lyapunov controller for uncertain systems

    KAUST Repository

    Laleg-Kirati, Taous-Meriem; Elmetennani, Shahrazed

    2017-01-01

    Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust

  18. Robust Matching Pursuit Extreme Learning Machines

    Directory of Open Access Journals (Sweden)

    Zejian Yuan

    2018-01-01

    Full Text Available Extreme learning machine (ELM is a popular learning algorithm for single hidden layer feedforward networks (SLFNs. It was originally proposed with the inspiration from biological learning and has attracted massive attentions due to its adaptability to various tasks with a fast learning ability and efficient computation cost. As an effective sparse representation method, orthogonal matching pursuit (OMP method can be embedded into ELM to overcome the singularity problem and improve the stability. Usually OMP recovers a sparse vector by minimizing a least squares (LS loss, which is efficient for Gaussian distributed data, but may suffer performance deterioration in presence of non-Gaussian data. To address this problem, a robust matching pursuit method based on a novel kernel risk-sensitive loss (in short KRSLMP is first proposed in this paper. The KRSLMP is then applied to ELM to solve the sparse output weight vector, and the new method named the KRSLMP-ELM is developed for SLFN learning. Experimental results on synthetic and real-world data sets confirm the effectiveness and superiority of the proposed method.

  19. Robust Force Control of Series Elastic Actuators

    Directory of Open Access Journals (Sweden)

    Andrea Calanca

    2014-07-01

    Full Text Available Force-controlled series elastic actuators (SEA are widely used in novel human-robot interaction (HRI applications, such as assistive and rehabilitation robotics. These systems are characterized by the presence of the “human in the loop”, so that control response and stability depend on uncertain human dynamics, including reflexes and voluntary forces. This paper proposes a force control approach that guarantees the stability and robustness of the coupled human-robot system, based on sliding-mode control (SMC, considering the human dynamics as a disturbance to reject. We propose a chattering free solution that employs simple task models to obtain high performance, comparable with second order solutions. Theoretical stability is proven within the sliding mode framework, and predictability is reached by avoiding the reaching phase by design. Furthermore, safety is introduced by a proper design of the sliding surface. The practical feasibility of the approach is shown using an SEA prototype coupled with a human impedance in severe stress tests. To show the quality of the approach, we report a comparison with state-of-the-art second order SMC, passivity-based control and adaptive control solutions.

  20. Robust distributed cognitive relay beamforming

    KAUST Repository

    Pandarakkottilil, Ubaidulla

    2012-05-01

    In this paper, we present a distributed relay beamformer design for a cognitive radio network in which a cognitive (or secondary) transmit node communicates with a secondary receive node assisted by a set of cognitive non-regenerative relays. The secondary nodes share the spectrum with a licensed primary user (PU) node, and each node is assumed to be equipped with a single transmit/receive antenna. The interference to the PU resulting from the transmission from the cognitive nodes is kept below a specified limit. The proposed robust cognitive relay beamformer design seeks to minimize the total relay transmit power while ensuring that the transceiver signal-to-interference- plus-noise ratio and PU interference constraints are satisfied. The proposed design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can be reformulated as a tractable convex optimization problem that can be solved efficiently. Numerical results are provided and illustrate the performance of the proposed designs for different network operating conditions and parameters. © 2012 IEEE.