Directory of Open Access Journals (Sweden)
Ehsan Maani Miandoab
2013-01-01
Full Text Available Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.
Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter
Zhang, Zhen; Ma, Yaopeng
2016-01-01
A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349
On rate-dependent mechanical model for adaptive magnetorheological elastomer base isolator
Li, Yancheng; Li, Jianchun
2017-04-01
This paper presents research on the phenomenological model of an adaptive base isolator. The adaptive base isolator is made of field-dependent magnetorheological elastomer (MRE) which can alter its physical property under application of magnetic field. Experimental testing demonstrated that the developed MRE base isolator possesses an amazing ability to vary its stiffness under applied magnetic field. However, several challenges have been encountered when it comes modeling such novel device. For example, under a large deformation, the MRE base isolator exhibits a clear strain stiffening effect and this behavior escalates with the increasing of applied current. In addition, the MRE base isolator has also shown typical rate-dependent behavior. Following a review on mechanical models for viscos-elastic rubber devices, a novel rate-dependent model is proposed in this paper to capture the behavior of the new MRE base isolator. To develop a generalized model, the proposed model was evaluated using its performance under random displacement input and a seismic input. It shows that the proposed rate-dependent model can successfully describe the complex behavior of the device.
DEFF Research Database (Denmark)
Fazio, Alessandro; Jewett, Michael Christopher; Daran-Lapujade, Pascale
2008-01-01
Background: Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of Saccharomyces cerevisiae. The three...... factors we considered were specific growth rate, nutrient limitation, and oxygen availability. Results: We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which m......RNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed de novo synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known...
Adaptive Vehicle Traction Control
Lee, Hyeongcheol; Tomizuka, Masayoshi
1995-01-01
This report presents two different control algorithms for adaptive vehicle traction control, which includes wheel slip control, optimal time control, anti-spin acceleration and anti-skid control, and longitudinal platoon control. The two control algorithms are respectively based on adaptive fuzzy logic control and sliding mode control with on-line road condition estimation. Simulations of the two control methods are conducted using a complex nonlinear vehicle model as well as a simple linear ...
Myravyova, E. A.; Sharipov, M. I.; Radakina, D. S.
2017-10-01
During writing this work, the fuzzy controller with a double base of rules was studied, which was applied for the synthesis of the automated control system. A method for fuzzy controller adaptation has been developed. The adaptation allows the fuzzy controller to automatically compensate for parametric interferences that occur at the control object. Specifically, the fuzzy controller controlled the outlet steam temperature in the boiler unit BKZ-75-39 GMA. The software code was written in the programming support environment Unity Pro XL designed for fuzzy controller adaptation.
Stable Hybrid Adaptive Control,
1982-07-01
STABLE HYBRID ADAPTIVE CONTROL(U) YALE UNIV NEW HAVEN i/i CT CENTER FOR SYSTEMS SCIENCE K S NARENDRA ET AL. JUL 82 8286 Ne@04-76-C-8e7 UNCLASSIFIED...teasrallepsaaw1tflbe~ll b ydd Il"t 5 As is the comtanuous Case cistral to the stability analysis of the hybrid ~IVt* COnRol PO* IMare the sur Models
Adaptive Structural Mode Control Project
National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...
Adaptive filtering prediction and control
Goodwin, Graham C
2009-01-01
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o
Maritime adaptive optics beam control
Corley, Melissa S.
2010-01-01
The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...
Aircraft adaptive learning control
Lee, P. S. T.; Vanlandingham, H. F.
1979-01-01
The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.
Albers, Willem/Wim; Kallenberg, W. C. M.
2004-01-01
When the distributional form of the observations differs from normality, standard control charts are often seriously in error. Such model errors can be avoided with (modified) nonparametric control charts. Unfortunately, these control charts suffer from large stochastic errors due to estimation. In between are so called parametric control charts. All three of them are discussed in this paper as well as a combined chart, which chooses one of the three control charts according to the appropriat...
Hybrid Adaptive Flight Control with Model Inversion Adaptation
Nguyen, Nhan
2011-01-01
This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.
Controlling smart grid adaptivity
Toersche, Hermen; Nykamp, Stefan; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria
2012-01-01
Methods are discussed for planning oriented smart grid control to cope with scenarios with limited predictability, supporting an increasing penetration of stochastic renewable resources. The performance of these methods is evaluated with simulations using measured wind generation and consumption
Adaptive Extremum Control and Wind Turbine Control
DEFF Research Database (Denmark)
Ma, Xin
1997-01-01
This thesis is divided into two parts, i.e., adaptive extremum control and modelling and control of a wind turbine. The rst part of the thesis deals with the design of adaptive extremum controllers for some processes which have the behaviour that process should have as high e ciency as possible...... in parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important...... role. If it can be emphasis on control design. The models have beenvalidated by experimental data obtained from an existing wind turbine. The e ective wind speed experienced by the rotor of a wind turbine, which is often required by some control methods, is estimated by using a wind turbine as a wind...
Criticality of Adaptive Control Dynamics
Patzelt, Felix; Pawelzik, Klaus
2011-12-01
We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.
Adaptive controller for hyperthermia robot
Energy Technology Data Exchange (ETDEWEB)
Kress, R.L.
1997-03-01
This paper describes the development of an adaptive computer control routine for a robotically, deployed focused, ultrasonic hyperthermia cancer treatment system. The control algorithm developed herein uses physiological models of a tumor and the surrounding healthy tissue regions and transient temperature data to estimate the treatment region`s blood perfusion. This estimate is used to vary the specific power profile of a scanned, focused ultrasonic transducer to achieve a temperature distribution as close as possible to an optimal temperature distribution. The controller is evaluated using simulations of diseased tissue and using limited experiments on a scanned, focused ultrasonic treatment system that employs a 5-Degree-of-Freedom (D.O.F.) robot to scan the treatment transducers over a simulated patient. Results of the simulations and experiments indicate that the adaptive control routine improves the temperature distribution over standard classical control algorithms if good (although not exact) knowledge of the treated region is available. Although developed with a scanned, focused ultrasonic robotic treatment system in mind, the control algorithm is applicable to any system with the capability to vary specific power as a function of volume and having an unknown distributed energy sink proportional to temperature elevation (e.g., other robotically deployed hyperthermia treatment methods using different heating modalities).
Adaptive stochastic disturbance accommodating control
George, Jemin; Singla, Puneet; Crassidis, John L.
2011-02-01
This article presents a Kalman filter based adaptive disturbance accommodating stochastic control scheme for linear uncertain systems to minimise the adverse effects of both model uncertainties and external disturbances. Instead of dealing with system uncertainties and external disturbances separately, the disturbance accommodating control scheme lumps the overall effects of these errors in a to-be-determined model-error vector and then utilises a Kalman filter in the feedback loop for simultaneously estimating the system states and the model-error vector from noisy measurements. Since the model-error dynamics is unknown, the process noise covariance associated with the model-error dynamics is used to empirically tune the Kalman filter to yield accurate estimates. A rigorous stochastic stability analysis reveals a lower bound requirement on the assumed system process noise covariance to ensure the stability of the controlled system when the nominal control action on the true plant is unstable. An adaptive law is synthesised for the selection of stabilising system process noise covariance. Simulation results are presented where the proposed control scheme is implemented on a two degree-of-freedom helicopter.
Adaptive Controller Effects on Pilot Behavior
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.
Almost optimal adaptive LQ control: SISO case
Polderman, Jan W.; Daams, Jasper
2002-01-01
In this paper an almost optimal indirect adaptive controller for input/output dynamical systems is proposed. The control part of the adaptive control scheme is based on a modified LQ control law: by adding a time-varying gain to the certainty equivalent control law the conflict between
Heart rate dependency of JT interval sections.
Hnatkova, Katerina; Johannesen, Lars; Vicente, Jose; Malik, Marek
2017-08-09
Little experience exists with the heart rate correction of J-Tpeak and Tpeak-Tend intervals. In a population of 176 female and 176 male healthy subjects aged 32.3±9.8 and 33.1±8.4years, respectively, curve-linear and linear relationship to heart rate was investigated for different sections of the JT interval defined by the proportions of the area under the vector magnitude of the reconstructed 3D vectorcardiographic loop. The duration of the JT sub-section between approximately just before the T peak and almost the T end was found heart rate independent. Most of the JT heart rate dependency relates to the beginning of the interval. The duration of the terminal T wave tail is only weakly heart rate dependent. The Tpeak-Tend is only minimally heart rate dependent and in studies not showing substantial heart rate changes does not need to be heart rate corrected. For any correction formula that has linear additive properties, heart rate correction of JT and JTpeak intervals is practically the same as of the QT interval. However, this does not apply to the formulas in the form of Int/RR(a) since they do not have linear additive properties. Copyright © 2017 Elsevier Inc. All rights reserved.
Adaptive control of port-Hamiltonian systems
Dirksz, Daniel; Scherpen, Jacquelien M.A.
2010-01-01
Adaptive control is an alternative approach for controlling systems which are sensitive to parameter uncertainty. With adaptive control it is possible to estimate parameter errors and to compensate for those errors. This can result in a better performance of the controlled system. Some techniques
Adaptive, predictive controller for optimal process control
Energy Technology Data Exchange (ETDEWEB)
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Li, Wei; Yu, Ying; Hou, Jian-Wen; Zhou, Zhi-Wen; Guo, Kai; Zhang, Peng-Pai; Wang, Zhi-Quan; Yan, Jian-Hua; Sun, Jian; Zhou, Qing; Wang, Yue-Peng; Li, Yi-Gang
2017-03-01
Purkinje cells (PCs) have a steeper rate dependence of repolarization and are more susceptible to arrhythmic activity than do ventricular myocytes (VMs). Late sodium current (INaL) is rate dependent and contributes to rate dependence of repolarization. This study sought to test our hypothesis that PCs have a larger rate dependence of INaL, contributing to their steeper rate dependence of repolarization and higher susceptibility to arrhythmic activity, than do VMs. INaL was recorded in isolated rabbit PCs and VMs with the whole-cell patch clamp technique. Action potential was examined using the microelectrode technique. Compared with VMs, PCs exhibited a significantly larger rate dependence of INaL with a larger INaL to basic cycle length (BCL) slope. Moreover, PCs had a larger rate dependence of INaL decay and slower recovery kinetics. Interestingly, the larger rate dependence of INaL matched to a steeper rate dependence of action potential duration (APD) in PCs. The INaL blocker tetrodotoxin significantly blunted, while the INaL enhancer anemone toxin (ATX-II) significantly increased, the rate dependence of INaL and APD in PCs and VMs. In the presence of ATX-II, the rate dependence of INaL in PCs was markedly larger than that in VMs, causing a much steeper rate dependence of APD in PCs. Accordingly, PCs exhibited greater rate-dependent electrical instability and were more prone to ATX-II-induced early afterdepolarizations, which were completely inhibited by the INaL inhibitor ranolazine. PCs have a significantly larger rate dependence of INaL than do VMs because of distinctive INaL decay and recovery kinetics, which contributes to their larger rate adaptation, and simultaneously predisposes them to a higher risk of arrhythmogenesis. Copyright Â© 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.
Stochastic predictive control with adaptive model maintenance
Bavdekar, VA; Ehlinger, V; Gidon, D; Mesbah, A.
2016-01-01
© 2016 IEEE. The closed-loop performance of model-based controllers often degrades over time due to increased model uncertainty. Some form of model maintenance must be performed to regularly adapt the system model using closed-loop data. This paper addresses the problem of control-oriented model adaptation in the context of predictive control of stochastic linear systems. A stochastic predictive control approach is presented that integrates stochastic optimal control with control-oriented inp...
Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting
Trujillo, Anna; Gregory, Irene
2013-01-01
Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.
Adaptive Method Using Controlled Grid Deformation
Directory of Open Access Journals (Sweden)
Florin FRUNZULICA
2011-09-01
Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.
Quantum Transduction with Adaptive Control.
Zhang, Mengzhen; Zou, Chang-Ling; Jiang, Liang
2018-01-12
Quantum transducers play a crucial role in hybrid quantum networks. A good quantum transducer can faithfully convert quantum signals from one mode to another with minimum decoherence. Most investigations of quantum transduction are based on the protocol of direct mode conversion. However, the direct protocol requires the matching condition, which in practice is not always feasible. Here we propose an adaptive protocol for quantum transducers, which can convert quantum signals without requiring the matching condition. The adaptive protocol only consists of Gaussian operations, feasible in various physical platforms. Moreover, we show that the adaptive protocol can be robust against imperfections associated with finite squeezing, thermal noise, and homodyne detection, and it can be implemented to realize quantum state transfer between microwave and optical modes.
Predictor-Based Model Reference Adaptive Control
Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.
2009-01-01
This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.
Digital adaptive control laws for VTOL aircraft
Hartmann, G. L.; Stein, G.
1979-01-01
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
Adaptive nonlinear control for autonomous ground vehicles
Black, William S.
We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design nonlinear disturbance observers for both single-input-single-output and multi-input-multi-output systems. Finally, we show the performance of these observers with simulation results.
Congestion Control Based on Multiple Model Adaptive Control
Directory of Open Access Journals (Sweden)
Xinhao Yang
2013-01-01
Full Text Available The congestion controller based on the multiple model adaptive control is designed for the network congestion in TCP/AQM network. As the conventional congestion control is sensitive to the variable network condition, the adaptive control method is adopted in our congestion control. The multiple model adaptive control is introduced in this paper based on the weight calculation instead of the parameter estimation in past adaptive control. The model set is composed by the dynamic model based on the fluid flow. And three “local” congestion controllers are nonlinear output feedback controller based on variable RTT, H2 output feedback controller, and proportional-integral controller, respectively. Ns-2 simulation results in section 4 indicate that the proposed algorithm restrains the congestion in variable network condition and maintains a high throughput together with a low packet drop ratio.
Adaptive Feedfoward Feedback Control Framework Project
National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...
A computer-controlled adaptive antenna system
Fetterolf, P. C.; Price, K. M.
The problem of active pattern control in multibeam or phased array antenna systems is one that is well suited to technologies based upon microprocessor feedback control systems. Adaptive arrays can be realized by incorporating microprocessors as control elements in closed-loop feedback paths. As intelligent controllers, microprocessors can detect variations in arrays and implement suitable configuration changes. The subject of this paper is the application of the Howells-Applebaum power inversion algorithm in a C-band multibeam antenna system. A proof-of-concept, microprocessor controlled, adaptive beamforming network (BFN) was designed, assembled, and subsequent tests were performed demonstrating the algorithm's capacity for nulling narrowband jammers.
Adaptive Sliding Mode Control for Hydraulic Drives
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.
2013-01-01
This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...
Switching Control for Adaptive Disturbance Attenuation
Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
The problem of adaptive disturbance attenuation is addressed in this paper using a switching control approach. A finite family of stabilizing controllers is pre-designed, with the assumption that, for any possible operating condition, at least one controller is able to achieve a prescribed level of
Genetic algorithms in adaptive fuzzy control
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
2008-01-01
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Intelligent Engine Systems: Adaptive Control
Gibson, Nathan
2008-01-01
We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.
Full Gradient Solution to Adaptive Hybrid Control
Bean, Jacob; Schiller, Noah H.; Fuller, Chris
2017-01-01
This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.
Language control in bilinguals: The adaptive control hypothesis.
Green, David W; Abutalebi, Jubin
2013-08-01
Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual.
Reinforcer magnitude and rate dependency: evaluation of resistance-to-change mechanisms.
Pinkston, Jonathan W; Ginsburg, Brett C; Lamb, Richard J
2014-10-01
Under many circumstances, reinforcer magnitude appears to modulate the rate-dependent effects of drugs such that when schedules arrange for relatively larger reinforcer magnitudes rate dependency is attenuated compared with behavior maintained by smaller magnitudes. The current literature on resistance to change suggests that increased reinforcer density strengthens operant behavior, and such strengthening effects appear to extend to the temporal control of behavior. As rate dependency may be understood as a loss of temporal control, the effects of reinforcer magnitude on rate dependency may be due to increased resistance to disruption of temporally controlled behavior. In the present experiments, pigeons earned different magnitudes of grain during signaled components of a multiple FI schedule. Three drugs, clonidine, haloperidol, and morphine, were examined. All three decreased overall rates of key pecking; however, only the effects of clonidine were attenuated as reinforcer magnitude increased. An analysis of within-interval performance found rate-dependent effects for clonidine and morphine; however, these effects were not modulated by reinforcer magnitude. In addition, we included prefeeding and extinction conditions, standard tests used to measure resistance to change. In general, rate-decreasing effects of prefeeding and extinction were attenuated by increasing reinforcer magnitudes. Rate-dependent analyses of prefeeding showed rate-dependency following those tests, but in no case were these effects modulated by reinforcer magnitude. The results suggest that a resistance-to-change interpretation of the effects of reinforcer magnitude on rate dependency is not viable.
Adaptive output feedback control of flexible systems
Yang, Bong-Jun
Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in
Modeling and (adaptive) control of greenhouse climates
Udink ten Cate, A.J.
1983-01-01
The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.
System concepts
In Chapters 1 and 2 an overview of the problem formulation
Simulation analysis of adaptive cruise prediction control
Zhang, Li; Cui, Sheng Min
2017-09-01
Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.
Neuronal control of adaptive thermogenesis
Directory of Open Access Journals (Sweden)
Xiaoyong eYang
2015-09-01
Full Text Available The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT, dysfunction of which lie at the core of obesity and associated metabolic disorders. In contrast, brown adipose tissue (BAT burns fat and dissipates chemical energy as heat. The development and activation of brown-like adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system (CNS drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation.
Adaptive Control Algorithm of the Synchronous Generator
Directory of Open Access Journals (Sweden)
Shevchenko Victor
2017-01-01
Full Text Available The article discusses the the problem of controlling a synchronous generator, namely, maintaining the stability of the control object in the conditions of occurrence of noise and disturbances in the regulatory process. The model of a synchronous generator is represented by a system of differential equations of Park-Gorev, where state variables are computed relative to synchronously rotating d, q-axis. Management of synchronous generator is proposed to organize on the basis of the position-path control using algorithms to adapt with the reference model. Basic control law directed on the stabilizing indicators the frequency generated by the current and the required power level, which is achieved by controlling the mechanical torque on the shaft of the turbine and the value of the excitation voltage of the synchronous generator. Modification of the classic adaptation algorithm using the reference model, allowing to minimize the error of the reference regulation and the model under investigation within the prescribed limits, produced by means of the introduction of additional variables controller adaptation in the model. Сarried out the mathematical modeling of control provided influence on the studied model of continuous nonlinear and unmeasured the disturbance. Simulation results confirm the high level accuracy of tracking and adaptation investigated model with respect to the reference, and the present value of the loop error depends on parameters performance of regulator.
Adaptive control of saccades via internal feedback.
Chen-Harris, Haiyin; Joiner, Wilsaan M; Ethier, Vincent; Zee, David S; Shadmehr, Reza
2008-03-12
Ballistic movements like saccades require the brain to generate motor commands without the benefit of sensory feedback. Despite this, saccades are remarkably accurate. Theory suggests that this accuracy arises because the brain relies on an internal forward model that monitors the motor commands, predicts their sensory consequences, and corrects eye trajectory midflight. If control of saccades relies on a forward model, then the forward model should adapt whenever its predictions fail to match sensory feedback at the end of the movement. Using optimal feedback control theory, we predicted how this adaptation should alter saccade trajectories. We trained subjects on a paradigm in which the horizontal target jumped vertically during the saccade. With training, the final position of the saccade moved toward the second target. However, saccades became increasingly curved, i.e., suboptimal, as oculomotor commands were corrected on-line to steer the eye toward the second target. The adaptive response had two components: (1) the motor commands that initiated the saccades changed slowly, aiming the saccade closer to the jumped target. The adaptation of these earliest motor commands displayed little forgetting during the rest periods. (2) Late in saccade trajectory, another adaptive response steered it still closer to the jumped target, producing curvature. Adaptation of these late motor commands showed near-complete forgetting during the rest periods. The two components adapted at different timescales, with the late-acting component displaying much faster rates. It appears that in controlling saccades, the brain relies on an internal feedback that has the characteristics of a fast-adapting forward model.
Robust Adaptive Control Using a Filtering Action
2009-09-01
Control and Signal Processing (ALCOSP 2007). Saint Petersburg, RUSSIA August 2007. [65] R. K. Miller and G. R. Sell, Volterra Integral Equations and...Experimental Results with Modified L1 Adaptive Controller and FSS. .........82 Figure C.1. Region of Integration for Equation (C.2...is that 1 1 ( ) ( ) D p E p is a PID controller, with the integral action to satisfy Equation (4.3), and the derivative action to make its inverse
Adaptive control of solar energy collector systems
Lemos, João M; Igreja, José M
2014-01-01
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Adaptive Control with Approximated Policy Search Approach
Directory of Open Access Journals (Sweden)
Agus Naba
2010-05-01
Full Text Available Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive control scheme that involves manipulating a controller of a general type to improve its performance as measured by an evaluation function. The developed method is closely related to a theory of Reinforcement Learning (RL but imposes a practical assumption made for faster learning. We assume that a value function of RL can be approximated by a function of Euclidean distance from a goal state and an action executed at the state. And, we propose to use it for the gradient search as an evaluation function. Simulation results provided through application of the proposed scheme to a pole-balancing problem using a linear state feedback controller and fuzzy controller verify the scheme’s efficacy.
Adaptive control of nonlinear underwater robotic systems
Directory of Open Access Journals (Sweden)
Thor I. Fossen
1991-04-01
Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.
Adaptive Critic Nonlinear Robust Control: A Survey.
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.
Simple adaptive control system design trades
Mooij, E.
2017-01-01
In the design of a Model Reference Adaptive Control system, a reference model serves as the (well-known) basis through which system and user requirements can find their way into the design. By tuning the design parameters, the response of the actual vehicle should track the response of the
Reference model decomposition in direct adaptive control
Butler, H.; Honderd, G.; van Amerongen, J.
1991-01-01
This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely
Robust Adaptive Control In Hilbert Space
Wen, John Ting-Yung; Balas, Mark J.
1990-01-01
Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.
Tip-over Prevention: Adaptive Control Development
2015-05-30
and tested on an iRobot Packbot and a Segway RMP 440. Experimental results show that the controllers are able to stabilize the robot under a variety...VALIDATION The adaptive roll and pitch controllers, or advanced control, were implemented on both an iRobot Packbot and a Segway RMP 440, each equipped...measure. Threshold for tip-over warning set to 0.38. 1) Segway RMP 440: Figure 5 demonstrates the advanced control active on the Segway RMP440. The
Multivariable adaptive control of bio process
Energy Technology Data Exchange (ETDEWEB)
Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique
1995-12-31
This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.
Robust and Adaptive Control With Aerospace Applications
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 ...
Improvement of Adaptive Cruise Control Performance
Directory of Open Access Journals (Sweden)
Nakagami Takashi
2010-01-01
Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.
On adaptive control of mobile slotted aloha networks
Directory of Open Access Journals (Sweden)
Lim J.-T.
1995-01-01
Full Text Available An adaptive control scheme for mobile slotted ALOHA is presented and the effect of capture on the adaptive control scheme is investigated. It is shown that with the proper choice of adaptation parameters the adaptive control scheme can be made independent of the effect of capture.
Adaptive wing and flow control technology
Stanewsky, E.
2001-10-01
The development of the boundary layer and the interaction of the boundary layer with the outer “inviscid” flow field, exacerbated at high speed by the occurrence of shock waves, essentially determine the performance boundaries of high-speed flight. Furthermore, flight and freestream conditions may change considerably during an aircraft mission while the aircraft itself is only designed for multiple but fixed design points thus impairing overall performance. Consequently, flow and boundary layer control and adaptive wing technology may have revolutionary new benefits for take-off, landing and cruise operating conditions for many aircraft by enabling real-time effective geometry optimization relative to the flight conditions. In this paper we will consider various conventional and novel means of boundary layer and flow control applied to moderate-to-large aspect ratio wings, delta wings and bodies with the specific objectives of drag reduction, lift enhancement, separation suppression and the improvement of air-vehicle control effectiveness. In addition, adaptive wing concepts of varying complexity and corresponding aerodynamic performance gains will be discussed, also giving some examples of possible structural realizations. Furthermore, penalties associated with the implementation of control and adaptation mechanisms into actual aircraft will be addressed. Note that the present contribution is rather application oriented.
Model reference adaptive control of robots
Steinvorth, Rodrigo
1991-01-01
This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.
Directory of Open Access Journals (Sweden)
Saikat Kumar Shome
2015-01-01
Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.
Adaptive LQ control: Conflict between identification and control
Polderman, Jan W.
1989-01-01
We consider one of the fundamental limitations of indirect adaptive control based on the minimization of a quadratic cost criterion and the certainty equivalence principle. We show that the interaction between (closed-loop) identification and optimal control is conflictive in the sense that almost
Adaptive Control with Reference Model Modification
Stepanyan, Vahram; Krishnakumar, Kalmanje
2012-01-01
This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example
Adaptive traffic control systems for urban networks
Directory of Open Access Journals (Sweden)
Radivojević Danilo
2017-01-01
Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.
Rail Vehicle Vibrations Control Using Parameters Adaptive PID Controller
Directory of Open Access Journals (Sweden)
Muzaffer Metin
2014-01-01
Full Text Available In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5-DOF quarter-rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.
ADAPTIVE SUBOPTIMAL CONTROL OF INPUT CONSTRAINED PLANTS
Directory of Open Access Journals (Sweden)
Valerii Azarskov
2011-03-01
Full Text Available Abstract. This paper deals with adaptive regulation of a discrete-time linear time-invariant plant witharbitrary bounded disturbances whose control input is constrained to lie within certain limits. The adaptivecontrol algorithm exploits the one-step-ahead control strategy and the gradient projection type estimationprocedure using the modified dead zone. The convergence property of the estimation algorithm is shown tobe ensured. The sufficient conditions guaranteeing the global asymptotical stability and simultaneously thesuboptimality of the closed-loop systems are derived. Numerical examples and simulations are presented tosupport the theoretical results.
Structure Preserving Adaptive Control of Port-Hamiltonian Systems
Dirksz, Daniel A.; Scherpen, Jacquelien M. A.
2012-01-01
In this technical note, an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation
Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator
Directory of Open Access Journals (Sweden)
Xin Zuo
2017-01-01
Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.
Robust adaptive control for Unmanned Aerial Vehicles
Kahveci, Nazli E.
The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with
A Methodology for Investigating Adaptive Postural Control
McDonald, P. V.; Riccio, G. E.
1999-01-01
Our research on postural control and human-environment interactions provides an appropriate scientific foundation for understanding the skill of mass handling by astronauts in weightless conditions (e.g., extravehicular activity or EVA). We conducted an investigation of such skills in NASA's principal mass-handling simulator, the Precision Air-Bearing Floor, at the Johnson Space Center. We have studied skilled movement-body within a multidisciplinary context that draws on concepts and methods from biological and behavioral sciences (e.g., psychology, kinesiology and neurophysiology) as well as bioengineering. Our multidisciplinary research has led to the development of measures, for manual interactions between individuals and the substantial environment, that plausibly are observable by human sensory systems. We consider these methods to be the most important general contribution of our EVA investigation. We describe our perspective as control theoretic because it draws more on fundamental concepts about control systems in engineering than it does on working constructs from the subdisciplines of biomechanics and motor control in the bio-behavioral sciences. At the same time, we have attempted to identify the theoretical underpinnings of control-systems engineering that are most relevant to control by human beings. We believe that these underpinnings are implicit in the assumptions that cut across diverse methods in control-systems engineering, especially the various methods associated with "nonlinear control", "fuzzy control," and "adaptive control" in engineering. Our methods are based on these theoretical foundations rather than on the mathematical formalisms that are associated with particular methods in control-systems engineering. The most important aspects of the human-environment interaction in our investigation of mass handling are the functional consequences that body configuration and stability have for the pick up of information or the achievement of
Blowdown wind tunnel control using an adaptive fuzzy PI controller
Directory of Open Access Journals (Sweden)
Corneliu Andrei NAE
2013-09-01
Full Text Available The paper presents an approach towards the control of a supersonic blowdown wind tunnel plant (as evidenced by experimental data collected from “INCAS Supersonic Blowdown Wind Tunnel” using a PI type controller. The key to maintain the imposed experimental conditions is the control of the air flow using the control valve of the plant. A proposed mathematical model based on the control valve will be analyzed using the PI controller. This control scheme will be validated using experimental data collected from real test cases. In order to improve the control performances an adaptive fuzzy PI controller will be implemented in SIMULINK in the present paper. The major objective is to reduce the transient regimes and the global reduction of the start-up loads on the models during this phase.
Adaptive control of space based robot manipulators
Walker, Michael W.; Wee, Liang-Boon
1991-01-01
For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.
Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller
Directory of Open Access Journals (Sweden)
Omur Can Ozguney
2017-08-01
Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.
PI controller based model reference adaptive control for nonlinear
African Journals Online (AJOL)
user
using MRAC for autonomous robot systems with random friction. An adaptive output-feedback control scheme is developed for a class of nonlinear Single Input Single Output (SISO) dynamic systems with time delays (Mirkin et al, 2010). A neuro-sliding mode approach based on MRAC is proposed in (Huh and Bien, 2007).
Mechanosensation and Adaptive Motor Control in Insects.
Tuthill, John C; Wilson, Rachel I
2016-10-24
The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing. Copyright © 2016 Elsevier Ltd. All rights reserved.
Error-controlled adaptive finite elements in solid mechanics
National Research Council Canada - National Science Library
Stein, Erwin; Ramm, E
2003-01-01
... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Error-controlled Adaptive Finite-element-methods . . . . . . . . . . . . Missing Features and Properties of Today's General Purpose FE Programs for Structural...
Adaptive Control Using Residual Mode Filters Applied to Wind Turbines
Frost, Susan A.; Balas, Mark J.
2011-01-01
Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.
Adaptive tracking control of nonholonomic systems: an example
Lefeber, A.A.J.; Nijmeijer, Henk
1999-01-01
We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not
Reference-shaping adaptive control by using gradient descent optimizers.
Alagoz, Baris Baykant; Kavuran, Gurkan; Ates, Abdullah; Yeroglu, Celaleddin
2017-01-01
This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC) method for several test scenarios. An experimental study demonstrates application of method for rotor control.
Adaptive Control of Flexible Structures Using Residual Mode Filters
Balas, Mark J.; Frost, Susan
2010-01-01
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.
Norman, D. A.; And Others
"Machine controlled adaptive training is a promising concept. In adaptive training the task presented to the trainee varies as a function of how well he performs. In machine controlled training, adaptive logic performs a function analogous to that performed by a skilled operator." This study looks at the ways in which gain-effective time…
Adaptive Torque Control of Variable Speed Wind Turbines
Energy Technology Data Exchange (ETDEWEB)
Johnson, K. E.
2004-08-01
The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry for variable speed wind turbines below rated power. This adaptive controller uses a simple, highly intuitive gain adaptation law designed to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds.
Driver behaviour with adaptive cruise control.
Stanton, Neville A; Young, Mark S
2005-08-15
This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.
Adaptive powertrain control for plugin hybrid electric vehicles
Kedar-Dongarkar, Gurunath; Weslati, Feisel
2013-10-15
A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.
Biofeedback systems and adaptive control hemodialysis treatment
Directory of Open Access Journals (Sweden)
Azar Ahmad
2008-01-01
Full Text Available On-line monitoring devices to control functions such as volume, body temperature, and ultrafiltration, were considered more toys than real tools for routine clinical application. However, bio-feedback blood volume controlled hemodialysis (HD is now possible in routine dialysis, allowing the delivery of a more physiologically acceptable treatment. This system has proved to reduce the incidence of intra-HD hypotension episodes significantly. Ionic dialysance and the patient′s plasma conductivity can be calculated easily from on-line measurements at two different steps of dialysate conductivity. A bio-feedback system has been devised to calculate the patient′s plasma conductivity and modulate the conductivity of the dialysate continuously in order to achieve a desired end-dialysis patient plasma conductivity corresponding to a desired end-dialysis plasma sodium concentration. Another bio-feedback system can control the body tempe-rature by measuring it at the arterial and venous lines of the extra-corporeal circuit, and then modulating the dialysate temperature in order to stabilize the patients′ temperature at constant values that result in improved intra-HD cardiovascular stability. The module can also be used to quantify vascular access recirculation. Finally, the simultaneous computer control of ultrafiltration has proven the most effective means for automatic blood pressure stabilization during hemo-dialysis treatment. The application of fuzzy logic in the blood-pressure-guided biofeedback con-trol of ultrafiltration during hemodialysis is able to minimize HD-induced hypotension. In con-clusion, online monitoring and adaptive control of the patient during the dialysis session using the bio-feedback systems is expected to render the process of renal replacement therapy more physiological and less eventful.
Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.
Fei, Juntao; Zhou, Jian
2012-12-01
In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.
Adaptive Dynamic Surface Control for Generator Excitation Control System
Directory of Open Access Journals (Sweden)
Zhang Xiu-yu
2014-01-01
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Effect of Adaptation Gain in Model Reference Adaptive Controlled Second Order System
Directory of Open Access Journals (Sweden)
R. K. Nema
2011-06-01
Full Text Available Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. Nature of adaptation mechanism for controlling the system performance is greatly affected by the value of adaptation gain. It is observed that for the lower order system wide range of adaptation gain can be used to study the performance of the system. As the order of the system increases the applicable range of adaptation gain becomes narrow. This paper deals with application of model reference adaptive control scheme to second order system with different values of adaptation gain. The rule which is used for this application is MIT rule. Simulation is done in MATLAB and simulink and the results are compared for varying adaptation mechanism due to variation in adaptation gain.
Monitoring and Adaptive Control of Laser Processes
Purtonen, Tuomas; Kalliosaari, Anne; Salminen, Antti
Monitoring of laser processes has been researched actively since the 1980's in several institutes around the world. The goal of process monitoring is to gather information on the process and to improve the understanding of the occurring phenomena, and to use the gathered data to createquality control methods and adaptive, closed loop control of the process. The methods used forlaser process monitoring can be divided into optical and acoustic methods of which the optical methods are more common. Today, monitoring has been commercially applied to even the newest laser processes, e.g. additive manufacturing. For laser welding, the process monitoring has been developed even further and closed-loop systems have been demonstrated several years ago. The improvements in digital camera technology and data processing have resulted in development of systems that use feature recognition for determining certain features of the process. Monitoring systems have developed from simple systems using single sensors to a more sophisticated systems utilizing a multitude of different detectors and detection methods.
Adaptive Controller Design for Continuous Stirred Tank Reactor
K. Prabhu; V. Murali Bhaskaran
2014-01-01
Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...
System Dynamics and Adaptive Control for MEMS Gyroscope Sensor
Directory of Open Access Journals (Sweden)
Juntao Fei
2010-12-01
Full Text Available This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the proposed adaptive control strategy. Numerical simulation is investigated to verify the effectiveness of the proposed control scheme.
Model reference adaptive control and adaptive stability augmentation
DEFF Research Database (Denmark)
Henningsen, Arne; Ravn, Ole
1993-01-01
stability augmented model reference design is proposed. By utilizing the closed-loop control error, a simple auxiliary controller is tuned, using a normalized MIT rule for the parameter adjustment. The MIT adjustment is protected against the effects of unmodelled dynamics by lowpass filtering...... of the gradient. The proposed method is verified through simulation results indicating that the method may lead to an improvement of the model reference controller in the presence of unmodelled dynamics...
Modular and Adaptive Control of Sound Processing
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
Adaptive wavefront control with asynchronous stochastic parallel gradient descent clusters.
Vorontsov, Mikhail A; Carhart, Gary W
2006-10-01
A scalable adaptive optics (AO) control system architecture composed of asynchronous control clusters based on the stochastic parallel gradient descent (SPGD) optimization technique is discussed. It is shown that subdivision of the control channels into asynchronous SPGD clusters improves the AO system performance by better utilizing individual and/or group characteristics of adaptive system components. Results of numerical simulations are presented for two different adaptive receiver systems based on asynchronous SPGD clusters-one with a single deformable mirror with Zernike response functions and a second with tip-tilt and segmented wavefront correctors. We also discuss adaptive wavefront control based on asynchronous parallel optimization of several local performance metrics-a control architecture referred to as distributed adaptive optics (DAO). Analysis of the DAO system architecture demonstrated the potential for significant increase of the adaptation process convergence rate that occurs due to partial decoupling of the system control clusters optimizing individual performance metrics.
Neural network based adaptive control for nonlinear dynamic regimes
Shin, Yoonghyun
Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.
Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement
Grzegorz Mikułowski; Łukasz Jankowski
2009-01-01
An adaptive landing gear is a landing gear (LG) capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~va...
Adaptation in the fuzzy self-organising controller
DEFF Research Database (Denmark)
Jantzen, Jan; Poulsen, Niels Kjølstad
2003-01-01
This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies...
Neural Control of Chronic Stress Adaptation
Directory of Open Access Journals (Sweden)
James eHerman
2013-08-01
Full Text Available Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process.
Adaptive Linear Parameter Varying Control for Aeroservoelastic Suppression Project
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...
Adaptive Linear Parameter Varying Control for Aeroservoelastic Suppression Project
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill present and future aircraft safety objectives though automated vehicle recovery while maintaining performance and...
DEFF Research Database (Denmark)
Ravn, Ole
1998-01-01
The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....
Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems
Directory of Open Access Journals (Sweden)
Tain-Sou Tsay
2014-01-01
Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.
Strain rate dependence in plasticized and un-plasticized PVC
Kendall, M. J.; Siviour, C. R.
2012-08-01
An experimental and analytical investigation has been made into the mechanical behaviour of two poly (vinyl chloride) (PVC) polymers - an un-plasticized PVC and a diisononyl phthalate (DINP)-plasticized PVC. Measurements of the compressive stress-strain behaviour of the PVCs at strain rates ranging from 10-3 to 103s-1 and temperatures from - 60 to 100∘C are presented. Dynamic Mechanical Analysis was also performed in order to understand the material transitions observed in compression testing as the strain rate is increased. This investigation develops a better understanding of the interplay between the temperature dependence and rate dependence of polymers, with a focus on locating the temperature and rate-dependent material transitions that occur during high rate testing.
Strain rate dependence in plasticized and un-plasticized PVC
Directory of Open Access Journals (Sweden)
Siviour C.R.
2012-08-01
Full Text Available An experimental and analytical investigation has been made into the mechanical behaviour of two poly (vinyl chloride (PVC polymers – an un-plasticized PVC and a diisononyl phthalate (DINP-plasticized PVC. Measurements of the compressive stress-strain behaviour of the PVCs at strain rates ranging from 10−3 to 103s−1 and temperatures from − 60 to 100∘C are presented. Dynamic Mechanical Analysis was also performed in order to understand the material transitions observed in compression testing as the strain rate is increased. This investigation develops a better understanding of the interplay between the temperature dependence and rate dependence of polymers, with a focus on locating the temperature and rate-dependent material transitions that occur during high rate testing.
Micromechanical modeling of rate-dependent behavior of Connective tissues.
Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M
2017-03-07
In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.
Adaptive slope compensation for high bandwidth digital current mode controller
DEFF Research Database (Denmark)
Taeed, Fazel; Nymand, Morten
2015-01-01
An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations...... in converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter...
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...... 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...
Applications of adaptive filters in active noise control
Darlington, Paul
The active reduction of acoustic noise is achieved by the addition of a cancelling acoustic signal to the unwanted sound. Successful definition of the cancelling signal amounts to a system identification problem. Recent advances in adaptive signal processing have allowed this problem to be tackled using adaptive filters, which offer significant advantages over conventional solutions. The extension of adaptive noise cancelling techniques, which were developed in the electrical signal conditioning context, to the control of acoustic systems is studied. An analysis is presented of the behavior of the Widrow-Hoff LMS adaptive noise canceller with a linear filter in its control loop. The active control of plane waves propagating axially in a hardwalled duct is used as a motivating model problem. The model problem also motivates the study of the effects of feedback around an LMS adaptive filter. An alternative stochastic gradient algorithm for controlling adaptive filters in the presence of feedback is presented.
Adaptive Intelligent Ventilation Noise Control Project
National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Adaptive Intelligent Ventilation Noise Control Project
National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Fuzzy adaptive speed control of a permanent magnet synchronous motor
Choi, Han Ho; Jung, Jin-Woo; Kim, Rae-Young
2012-05-01
A fuzzy adaptive speed controller is proposed for a permanent magnet synchronous motor (PMSM). The proposed fuzzy adaptive speed regulator is insensitive to model parameter and load torque variations because it does not need any accurate knowledge about the motor parameter and load torque values. The stability of the proposed control system is also proven. The proposed adaptive speed regulator system is implemented by using a TMS320F28335 floating point DSP. Simulation and experimental results are presented to verify the effectiveness of the proposed fuzzy adaptive speed controller under uncertainties such as motor parameter and load torque variations using a prototype PMSM drive system.
Fractional adaptive control for an automatic voltage regulator.
Aguila-Camacho, Norelys; Duarte-Mermoud, Manuel A
2013-11-01
This paper presents the application of a direct Fractional Order Model Reference Adaptive Controller (FOMRAC) to an Automatic Voltage Regulator (AVR). A direct FOMRAC is a direct Model Reference Adaptive Control (MRAC), whose controller parameters are adjusted using fractional order differential equations. Four realizations of the FOMRAC were designed in this work, each one considering different orders for the plant model. The design procedure consisted of determining the optimal values of the fractional order and the adaptive gains for each adaptive law, using Genetic algorithm optimization. Comparisons were made among the four FOMRAC designs, a fractional order PID (FOPID), a classical PID, and four Integer Order Model Reference Adaptive Controllers (IOMRAC), showing that the FOMRAC can improve the controlled system behavior and its robustness with respect to model uncertainties. Finally, some performance indices are presented here for the controlled schemes, in order to show the advantages and disadvantages of the FOMRAC. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Hierarchical Robust and Adaptive Nonlinear Control Design
National Research Council Canada - National Science Library
Haddad, Wassim
2003-01-01
The authors proposed the development of a general multiechelon hierarchical nonlinear switching control design framework that minimizes control law complexity subject to the achievement of control law robustness...
Connection adaption for control of networked mobile chaotic agents.
Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S
2017-11-22
In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.
Systems and Methods for Derivative-Free Adaptive Control
Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)
2015-01-01
An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.
Parameter testing for lattice filter based adaptive modal control systems
Sundararajan, N.; Williams, J. P.; Montgomery, R. C.
1983-01-01
For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.
Adaptive control with variable dead-zone nonlinearities
Orlicki, D.; Valavani, L.; Athans, M.; Stein, G.
1984-01-01
It has been found that fixed error dead-zones as defined in the existing literature result in serious degradation of performance, due to the conservativeness which characterizes the determination of their width. In the present paper, variable width dead-zones are derived for the adaptive control of plants with unmodeled dynamics. The derivation makes use of information available about the unmodeled dynamics both a priori as well as during the adaptation process, so as to stabilize the adaptive loop and at the same time overcome the conservativeness and performance limitations of fixed-dead zone adaptive or fixed gain controllers.
Rate dependence of dry, oil- or water-saturated chalk
DEFF Research Database (Denmark)
Andreassen, Katrine Alling; Al-Alwan, A.
The rate dependence of dry, oil- or water-saturated high-porosity outcrop chalk is investigated based on whether the fluid effect could be excluded from a governing material parameter, the b-factor. The b-factor is used in geotechnical engineering to establish the difference in evolution of load...... between stress-strain curves when applying different loading rates. The material investigated is outcrop chalk from Stevns, Southern part of Denmark, with a porosity of 43 to 44% and subjected to varying loading rates. The Biot critical frequency is a function of the fluid properties viscosity and density...
Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators
DEFF Research Database (Denmark)
Andersen, T.O.; Hansen, M.R.; Conrad, Finn
2004-01-01
A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...... control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each...
Hormesis and adaptive cellular control systems
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
A Unified Approach to High-Gain Adaptive Controllers
Directory of Open Access Journals (Sweden)
Ian A. Gravagne
2009-01-01
Full Text Available It has been known for some time that proportional output feedback will stabilize MIMO, minimum-phase, linear time-invariant systems if the feedback gain is sufficiently large. High-gain adaptive controllers achieve stability by automatically driving up the feedback gain monotonically. More recently, it was demonstrated that sample-and-hold implementations of the high-gain adaptive controller also require adaptation of the sampling rate. In this paper, we use recent advances in the mathematical field of dynamic equations on time scales to unify and generalize the discrete and continuous versions of the high-gain adaptive controller. We prove the stability of high-gain adaptive controllers on a wide class of time scales.
Adaptive Feature Based Control of Compact Disk Players
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez
2005-01-01
of the Compact Disc. The problem is to design servo controllers which are well suited for handling surface faults which disturb the position measurement and still react sufficiently against normal disturbances like mechanical shocks. In previous work of the same authors a feature based control scheme for CD......-players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...... in contrast with the other scheme adapt to the given fault. The adaptive scheme recomputes the feature extraction bases which is used to remove fault components from the measurements, at each encounter of the given fault. The improvements of this adaptive scheme are illustrated by simulations, with the clear...
Active adaptive sound control in a duct - A computer simulation
Burgess, J. C.
1981-09-01
A digital computer simulation of adaptive closed-loop control for a specific application (sound cancellation in a duct) is discussed. The principal element is an extension of Sondhi's adaptive echo canceler and Widrow's adaptive noise canceler from signal processing to control. Thus, the adaptive algorithm is based on the LMS gradient search method. The simulation demonstrates that one or more pure tones can be canceled down to the computer bit noise level (-120 dB). When additive white noise is present, pure tones can be canceled to at least 10 dB below the noise spectrum level for SNRs down to at least 0 dB. The underlying theory suggests that the algorithm allows tracking tones with amplitudes and frequencies that change more slowly with time than the adaptive filter adaptation rate. It also implies that the method can cancel narrow-band sound in the presence of spectrally overlapping broadband sound.
Robust Adaptive Speed Control of Induction Motor Drives
DEFF Research Database (Denmark)
Bidstrup, N.
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......This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly...... dependent of the operating point, which is characterised by the speed and load. If the requirements to the controller performance is large, then it is difficult to maintain specified controller performance with a fixed controller, because of the open loop variations. An auto-tuner based on least squares...
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...... 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...
Revisionist integral deferred correction with adaptive step-size control
Christlieb, Andrew
2015-03-27
© 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-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.
Design of Low Complexity Model Reference Adaptive Controllers
Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan
2012-01-01
Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.
Adaptive optimization and control using neural networks
Energy Technology Data Exchange (ETDEWEB)
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Disturbance Accommodating Adaptive Control with Application to Wind Turbines
Frost, Susan
2012-01-01
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Adaptive Automation Based on Air Traffic Controller Decision-Making
IJtsma (Student TU Delft), Martijn; Borst, C.; Mercado Velasco, G.A.; Mulder, M.; van Paassen, M.M.; Tsang, P.S.; Vidulich, M.A.
2017-01-01
Through smart scheduling and triggering of automation support, adaptive automation has the potential to balance air traffic controller workload. The challenge in the design of adaptive automation systems is to decide how and when the automation should provide support. This paper describes the design
Energy Technology Data Exchange (ETDEWEB)
Aljanaideh, Omar, E-mail: omaryanni@gmail.com [Department of Mechanical Engineering, The University of Jordan, Amman 11942 (Jordan); Habineza, Didace; Rakotondrabe, Micky [AS2M department, FEMTO-ST Institute, Univ. Bourgogne Franche-Comté, Univ. de Franche-Comté/CNRS/ENSMM, 25000 Besançon (France); Al Janaideh, Mohammad [Department of Mechanical and Industrial Engineering, The Mechatronics and Microsystems Design Laboratory, University of Toronto (Canada); Department of Mechatronics Engineering, The University of Jordan, Amman 11942 (Jordan)
2016-04-01
An experimental study has been carried out to characterize rate-dependent hysteresis of a piezoelectric tube actuator at different excitation frequencies. The experimental measurements were followed by modeling and compensation of the hysteresis nonlinearities of the piezoelectric tube actuator using both the inverse rate-dependent Prandtl–Ishlinskii model (RDPI) and inverse rate-independent Prandtl–Ishlinskii model (RIPI) coupled with a controller. The comparison of hysteresis modeling and compensation of the actuator with both models is presented.
Adaptive LQ Cascade Control of a Tubular Chemical Reactor
Directory of Open Access Journals (Sweden)
Petr Dostal
2016-01-01
Full Text Available The paper deals with adaptive LQ cascade control design of a tubular chemical reactor with an exothermic consecutive reaction. The control is performed in primary and secondary control-loops where the primary controlled output of the reactor is the concentration of a main reaction product and the secondary output is the mean temperature of the reactant. A common control input is the coolant flow rate. The controller in the primary control-loop is a nonlinear P-controller with the gain calculated using simulated or measured steady-state characteristics of the reactor. The controller in the secondary control-loop is a LQ adaptive controller. The proposed method is verified by control simulations.
Strain rate dependency of laser sintered polyamide 12
Directory of Open Access Journals (Sweden)
Cook J.E.T.
2015-01-01
Full Text Available Parts processed by Additive Manufacturing can now be found across a wide range of applications, such as those in the aerospace and automotive industry in which the mechanical response must be optimised. Many of these applications are subjected to high rate or impact loading, yet it is believed that there is no prior research on the strain rate dependence in these materials. This research investigates the effect of strain rate and laser energy density on laser sintered polyamide 12. In the study presented here, parts produced using four different laser sintered energy densities were exposed to uniaxial compression tests at strain rates ranging from 10−3 to 10+3 s−1 at room temperature, and the dependence on these parameters is presented.
Strain rate dependency of laser sintered polyamide 12
Cook, J. E. T.; Goodridge, R. D.; Siviour, C. R.
2015-09-01
Parts processed by Additive Manufacturing can now be found across a wide range of applications, such as those in the aerospace and automotive industry in which the mechanical response must be optimised. Many of these applications are subjected to high rate or impact loading, yet it is believed that there is no prior research on the strain rate dependence in these materials. This research investigates the effect of strain rate and laser energy density on laser sintered polyamide 12. In the study presented here, parts produced using four different laser sintered energy densities were exposed to uniaxial compression tests at strain rates ranging from 10-3 to 10+3 s-1 at room temperature, and the dependence on these parameters is presented.
Novel hybrid adaptive controller for manipulation in complex perturbation environments.
Directory of Open Access Journals (Sweden)
Alex M C Smith
Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.
1992-01-01
A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).
Integrated Damage-Adaptive Control System (IDACS) Project
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system is...
Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor
Directory of Open Access Journals (Sweden)
Wenjie Lou
2016-02-01
Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.
Control and adaptation in telecommunication systems mathematical foundations
Popovskij, Vladimir; Titarenko, Larysa
2011-01-01
This book is devoted to mathematical foundations providing synthesis and analysis of control and adaptation algorithms targeting modern telecommunication systems (TCS). The most popular technologies and network management methods are discussed.
High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project
National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...
High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project
National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...
Integrated Damage-Adaptive Control System (IDACS) Project
National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...
Vehicle-to-infrastructure program cooperative adaptive cruise control.
2015-03-01
This report documents the work completed by the Crash Avoidance Metrics Partners LLC (CAMP) Vehicle to Infrastructure (V2I) Consortium during the project titled Cooperative Adaptive Cruise Control (CACC). Participating companies in the V2I Cons...
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
Adaptive Semiactive Cable Vibration Control: A Frequency Domain Perspective
Directory of Open Access Journals (Sweden)
Z. H. Chen
2017-01-01
Full Text Available An adaptive solution to semiactive control of cable vibration is formulated by extending the linear quadratic Gaussian (LQG control from time domain to frequency domain. Frequency shaping is introduced via the frequency dependent weights in the cost function to address the control effectiveness and robustness. The Hilbert-Huang transform (HHT technique is further synthesized for online tuning of the controller gain adaptively to track the cable vibration evolution, which also obviates the iterative optimal gain selection for the trade-off between control performance and energy in the conventional time domain LQG (T-LQG control. The developed adaptive frequency-shaped LQG (AF-LQG control is realized by collocated self-sensing magnetorheological (MR dampers considering the nonlinear damper dynamics for force tracking control. Performance of the AF-LQG control is numerically validated on a bridge cable transversely attached with a self-sensing MR damper. The results demonstrate the adaptivity in gain tuning of the AF-LQG control to target for the dominant cable mode for vibration energy dissipation, as well as its enhanced control efficacy over the optimal passive MR damping control and the T-LQG control for different excitation modes and damper locations.
Adaptive Non-linear Control of Hydraulic Actuator Systems
DEFF Research Database (Denmark)
Hansen, Poul Erik; Conrad, Finn
1998-01-01
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Design of a digital adaptive control system for reentry vehicles.
Picon-Jimenez, J. L.; Montgomery, R. C.; Grigsby, L. L.
1972-01-01
The flying qualities of atmospheric reentry vehicles experience considerable variations due to the wide changes in flight conditions characteristic of reentry trajectories. A digital adaptive control system has been designed to modify the vehicle's dynamic characteristics and to provide desired flying qualities for all flight conditions. This adaptive control system consists of a finite-memory identifier which determines the vehicle's unknown parameters, and a gain computer which calculates feedback gains to satisfy flying quality requirements.
Scalable Harmonization of Complex Networks With Local Adaptive Controllers
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav; Herzallah, R.
2017-01-01
Roč. 47, č. 3 (2017), s. 394-404 ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Feedback * Feedforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.350, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf
Adaptive control with an expert system based supervisory level. Thesis
Sullivan, Gerald A.
1991-01-01
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up
Dissemination Protocols to Support Cooperative Adaptive Cruise Control (CACC) Merging
Klein Wolterink, W.; Heijenk, Geert; Karagiannis, Georgios
2011-01-01
Cooperative adaptive cruise control (CACC) is a form of cruise control in which vehicles cooperatively control their speed using wireless communication. Previously we have implemented CACC using beaconing: the regular broadcasting of status information using 802.11p. Currently we are concerned with
Spectrum management considerations of adaptive power control in satellite networks
Sawitz, P.; Sullivan, T.
1983-01-01
Adaptive power control concepts for the compensation of rain attenuation are considered for uplinks and downlinks. The performance of example power-controlled and fixed-EIRP uplinks is compared in terms of C/Ns and C/Is. Provisional conclusions are drawn with regard to the efficacy of uplink and downlink power control orbit/spectrum utilization efficiency.
Adaptive Process Control with Fuzzy Logic and Genetic Algorithms
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Adaptive process control using fuzzy logic and genetic algorithms
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
An adaptive learning control system for aircraft
Mekel, R.; Nachmias, S.
1978-01-01
A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.
Cognitive control adjustments and conflict adaptation in major depressive disorder.
Clawson, Ann; Clayson, Peter E; Larson, Michael J
2013-08-01
Individuals with major depressive disorder (MDD) show alterations in the cognitive control function of conflict processing. We examined the influence of these deficits on behavioral and event-related potential (ERP) indices of conflict adaptation, a cognitive control process wherein previous-trial congruency modulates current-trial performance, in 55 individuals with MDD and 55 matched controls. ERPs were calculated while participants completed a modified flanker task. There were nonsignificant between-groups differences in response time, error rate, and N2 indices of conflict adaptation. Higher depressive symptom scores were associated with smaller mean N2 conflict adaptation scores for individuals with MDD and when collapsed across groups. Results were consistent when comorbidity and medications were analyzed. These findings suggest N2 conflict adaptation is associated with depressive symptoms rather than clinical diagnosis alone. Copyright © 2013 Society for Psychophysiological Research.
Adaptive Feedfoward Feedback Control Framework Project
National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...
ADAPTIVE CONTROL OF FEED LOAD CHANGES IN ALCOHOL FERMENTATION
Directory of Open Access Journals (Sweden)
Folly R.
1997-01-01
Full Text Available A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control system was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter
Adaptive neuro-fuzzy controller of switched reluctance motor
Directory of Open Access Journals (Sweden)
Tahour Ahmed
2007-01-01
Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.
Hybrid adaptive ascent flight control for a flexible launch vehicle
Lefevre, Brian D.
For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the
Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network
Directory of Open Access Journals (Sweden)
Kazuhiko Hiramoto
2018-01-01
Full Text Available We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN. Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA. The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.
Adaptive and real-time optimal control for adaptive optics systems
Doelman, N.J.; Fraanje, P.R.; Houtzager, I.; Verhaegen, M.
2009-01-01
An optimal control method to reject turbulence-induced wavefront distortions in an Adaptive Optics system is discussed. Details of a data-driven control approach are presented where the emphasis is put on the estimation of the optimal predictor of the wavefront disturbance. Several algorithms
Stress state and strain rate dependence of the human placenta.
Weed, Benjamin C; Borazjani, Ali; Patnaik, Sourav S; Prabhu, R; Horstemeyer, M F; Ryan, Peter L; Franz, Thomas; Williams, Lakiesha N; Liao, Jun
2012-10-01
Maternal trauma (MT) in automotive collisions is a source of injury, morbidity, and mortality for both mothers and fetuses. The primary associated pathology is placental abruption in which the placenta detaches from the uterus leading to hemorrhaging and termination of pregnancy. In this study, we focused on the differences in placental tissue response to different stress states (tension, compression, and shear) and different strain rates. Human placentas were obtained (n = 11) for mechanical testing and microstructure analysis. Specimens (n = 4+) were tested in compression, tension, and shear, each at three strain rates (nine testing protocols). Microstructure analysis included scanning electron microscopy, histology, and interrupted mechanical tests to observe tissue response to various loading states. Our data showed the greatest stiffness in tension, followed by compression, and then by shear. The study concludes that mechanical behavior of human placenta tissue (i) has a strong stress state dependence and (ii) behaves in a rate dependent manner in all three stress states, which had previously only been shown in tension. Interrupted mechanical tests revealed differences in the morphological microstructure evolution that was driven by the kinematic constraints from the different loading states. Furthermore, these structure-property data can be used to develop high fidelity constitutive models for MT simulations.
Shear-rate-dependent transport coefficients in granular suspensions
Garzó, Vicente
2017-06-01
A recent model for monodisperse granular suspensions is used to analyze transport properties in spatially inhomogeneous states close to the simple (or uniform) shear flow. The kinetic equation is based on the inelastic Boltzmann (for low-density gases) with the presence of a viscous drag force that models the influence of the interstitial gas phase on the dynamics of grains. A normal solution is obtained via a Chapman-Enskog-like expansion around a (local) shear flow distribution which retains all the hydrodynamic orders in the shear rate. To first order in the expansion, the transport coefficients characterizing momentum and heat transport around shear flow are given in terms of the solutions of a set of coupled linear integral equations which are approximately solved by using a kinetic model of the Boltzmann equation. To simplify the analysis, the steady-state conditions when viscous heating is compensated by the cooling terms arising from viscous friction and collisional dissipation are considered to get the explicit forms of the set of generalized transport coefficients. The shear-rate dependence of some of the transport coefficients of the set is illustrated for several values of the coefficient of restitution.
Directory of Open Access Journals (Sweden)
Guoliang Zhao
2013-01-01
Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.
ADAPTIVE CONTROL SYSTEM OF INDUSTRIAL REACTORS
Directory of Open Access Journals (Sweden)
Vyacheslav K. Mayevski
2014-01-01
Full Text Available This paper describes a mathematical model of an industrial chemical reactor for production of synthetic rubber. During reactor operation the model parameters vary considerably. To create a control algorithm performed transformation of mathematical model of the reactor in order to obtain a dependency that can be used to determine the model parameters are changing during reactor operation.
Developing eco-adaptive cruise control systems.
2014-01-01
The study demonstrates the feasibility of two eco-driving applications which reduces vehicle fuel consumption and greenhouse gas emissions. In particular, the study develops an eco-drive system that combines eco-cruise control logic with state-of-the...
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
Directory of Open Access Journals (Sweden)
Alejandro Carrasco Elizalde
2008-01-01
Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
Parameter Identification and Adaptive Control Applied to the Inverted Pendulum
Directory of Open Access Journals (Sweden)
Carlos A. Saldarriaga-Cortés
2012-06-01
Full Text Available This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The results show that the above methodology was implemented satisfactorily in terms of estimation, stability and control of such a system. It was established that adaptive techniques have a proper performance even in systems with complex features such as nonlinearity and instability.
Design of adaptive switching control for hypersonic aircraft
Directory of Open Access Journals (Sweden)
Xin Jiao
2015-10-01
Full Text Available This article proposes a novel adaptive switching control of hypersonic aircraft based on type-2 Takagi–Sugeno–Kang fuzzy sliding mode control and focuses on the problem of stability and smoothness in the switching process. This method uses full-state feedback to linearize the nonlinear model of hypersonic aircraft. Combining the interval type-2 Takagi–Sugeno–Kang fuzzy approach with sliding mode control keeps the adaptive switching process stable and smooth. For rapid stabilization of the system, the adaptive laws use a direct constructive Lyapunov analysis together with an established type-2 Takagi–Sugeno–Kang fuzzy logic system. Simulation results indicate that the proposed control scheme can maintain the stability and smoothness of switching process for the hypersonic aircraft.
Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement
Directory of Open Access Journals (Sweden)
Grzegorz Mikułowski
2009-01-01
Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.
ADAPTIVE OUTPUT CONTROL: SUBJECT MATTER, APPLICATION TASKS AND SOLUTIONS
Directory of Open Access Journals (Sweden)
Alexey A. Bobtsov
2013-01-01
Full Text Available The problem of adaptive output control for parametric and functionally uncertain plants is considered. Application examples illustrating the practical use of the discussed theory are given along with the mathematical formulation of the problem. A brief review of adaptive output control methods, by both linear and non-linear systems, is presented and an extensive bibliography, in which the reader will find a detailed description of the specific algorithms and their properties, is represented. A new approach to the output control problem - a method of consecutive compensator - is considered in detail.
Frequency based design of modal controllers for adaptive optics systems.
Agapito, Guido; Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
2012-11-19
This paper addresses the problem of reducing the effects of wavefront distortions in ground-based telescopes within a "Modal-Control" framework. The proposed approach allows the designer to optimize the Youla parameter of a given modal controller with respect to a relevant adaptive optics performance criterion defined on a "sampled" frequency domain. This feature makes it possible to use turbulence/vibration profiles of arbitrary complexity (even empirical power spectral densities from data), while keeping the controller order at a moderate value. Effectiveness of the proposed solution is also illustrated through an adaptive optics numerical simulator.
An Adaptive Multivariable Control System for Hydroelectric Generating Units
Directory of Open Access Journals (Sweden)
Gunne J. Hegglid
1983-04-01
Full Text Available This paper describes an adaptive multivariable control system for hydroelectric generating units. The system is based on a detailed mathematical model of the synchronous generator, the water turbine, the exiter system and turbine control servo. The models of the water penstock and the connected power system are static. These assumptions are not considered crucial. The system uses a Kalman filter for optimal estimation of the state variables and the parameters of the electric grid equivalent. The multivariable control law is computed from a Riccatti equation and is made adaptive to the generators running condition by means of a least square technique.
Real-time control system for adaptive resonator
Energy Technology Data Exchange (ETDEWEB)
Flath, L; An, J; Brase, J; Hurd, R; Kartz, M; Sawvel, R; Silva, D
2000-07-24
Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.
Set Valued Calculus in Problems of Adaptive Control
Kurzhanski, A.B.
1987-01-01
This paper deals with feedback control for a linear nonstationary system whose objective is to reach a preassigned set in the state space while satisfying a certain state constraint. The state constraint to be fulfilled cannot be predicted in advance being available only on the basis of observations. It is specified through an adaptive procedure of "guaranteed estimation" and the objective of the basic process is to adapt to this constraint. The problems considered in the paper are motiv...
Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2012-01-01
We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a pre-computed set of plant-controller candidates and choosing the one that is best able to reproduce observed in- and output...
Algorithms for Optimal Model Distributions in Adaptive Switching Control Schemes
Ghosh, D.; Baldi, S.
2016-01-01
Several multiple model adaptive control architectures have been proposed in the literature. Despite many advances in theory, the crucial question of how to synthesize the pairs model/controller in a structurally optimal way is to a large extent not addressed. In particular, it is not clear how to
Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System
Klein Wolterink, W.; Karagiannis, Georgios; Brogle, Marc; Masip Bruin, Xavier; Braun, Torsten; Heijenk, Gerhard J.
Cooperative Adaptive Cruise Control (CACC) is a form of cruise control in which a vehicle maintains a constant headway to its preceding vehicle using radar and vehicle-to-vehicle (V2V) communication. Within the Connect & Drive1 project we have implemented and tested a prototype of such a system,
Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System
Klein Wolterink, W.; Heijenk, Geert; Karagiannis, Georgios
2011-01-01
Cooperative Adaptive Cruise Control (CACC) is a form of cruise control in which a vehicle maintains a constant headway to its preceding vehicle using radar and vehicle-to-vehicle (V2V) communication. Within the Connect & Drive1 project we have implemented and tested a prototype of such a system,
Digital adaptive control laws for the F-8
Hartmann, G. L.; Harvey, C. A.
1976-01-01
NASA is conducting a flight control research program in digital fly-by-wire technology using a modified F-8C aircraft. The first phase of this program used Apollo hardware to demonstrate the practicality of digital fly-by-wire in an actual test vehicle. For the second phase, conventional aircraft sensors and a large floating point digital computer are being utilized to test advanced control laws and redundancy concepts. As part of NASA's research in digital fly-by-wire technology, Honeywell developed digital adaptive flight control laws for flight test in the F-8C. Adaptation of the control laws was to be based on information sensed from conventional aircraft sensors excluding air data. The control laws were constrained to use only existing elevator, rudder, and ailerons as control effectors, each powered by existing actuators. Three adaptive control laws were successfully designed using maximum likelihood estimation, a Liapunov stable model tracker and a self-excited limit cycle concept. The maximum likelihood estimation design was selected as the most promising because of its capability to identify more than surface effectiveness parameters. The adaptive concepts, the control laws and comparisons of predicted performance are described.
Unfalsified Adaptive Switching Supervisory Control of Time Varying Systems
Battistelli, Giorgio; Hespanha, João; Mosca, Edoardo; Tesi, Pietro
2009-01-01
In recent years, unfalsified adaptive switching supervisory control (UASSC) has emerged as an effective technique for tackling the problem of controlling uncertain plants only on the basis of the plant I/O data. The aim of this paper is to construct a novel switching logic, which, when combined with
Continuous use of an adaptive lung ventilation controller in critically ...
African Journals Online (AJOL)
1995-05-05
May 5, 1995 ... Adaptive lung ventilation (ALV) refers to closed-loop mechanical ventilation designed to work in paralysed as well as spontaneously breathing patients, enabling variable ventilatory support as required, breath by breath, in each individual patient.',2. The ALV controller utilises pressure-controlled.
Robust Adaptive PID Control of Robot Manipulator with Bounded Disturbances
Directory of Open Access Journals (Sweden)
Jian Xu
2013-01-01
Full Text Available To solve the strong nonlinearity and coupling problems in robot manipulator control, two novel robust adaptive PID control schemes are proposed in this paper with known or unknown upper bound of the external disturbances. Invoking the two proposed controllers, the unknown bounded external disturbances can be compensated and the global asymptotical stability with respect to the manipulator positions and velocities is able to be guaranteed. As compared with the existing adaptive PD control methods, the designed control laws can enlarge the tolerable external disturbances, enhance the accuracy in finite-time trajectory tracking control, and improve the dynamic performance of the manipulator systems. The stability and convergence properties of the closed-loop system are analytically proved using Lyapunov stability theory and Barbalat’s lemma. Simulations are performed for a planner manipulator with two rotary degrees of freedom to illustrate the viability and the advantages of the proposed controllers.
Adaptive Contingency Control: Wind Turbine Operation Integrated with Blade Condition Monitoring
National Aeronautics and Space Administration — We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller...
Adapting End Host Congestion Control for Mobility
Eddy, Wesley M.; Swami, Yogesh P.
2005-01-01
Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP.
Baer-Riedhart, Jennifer L.; Landy, Robert J.
1987-01-01
The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.
VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER
Directory of Open Access Journals (Sweden)
P. N. Filippenko
2013-03-01
Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.
Neuro adaptive control for aerospace and distributed systems
Das, Abhijit
Nonlinear and adaptive control is generally considered one of the most effective techniques for stabilizing complex nonlinear systems, where linear control techniques may fail completely. Thousands of research papers are published on either theory or applications of nonlinear and adaptive control. But often one obvious question arises how to implement these techniques in real life model? The best answer that one can think of is to develop simple nonlinear control laws which are easy to implement. Moreover for controlling multi-agent systems, it is often required to distribute the control laws based on limited information available among the agents. This research provides some of these issues in the following way. a) Autopilot design for Aerospace systems: this research developes adaptive backstepping and dynamic inversion methods with internal dynamics stabilization for the quadrotor. Quadrotor helicopter models usually show two main characteristics. First, strong coupling among the system states and second, under-actuation where many states are to be controlled with few control inputs. Due to these unique characteristics, the design of stabilizing control inputs is always challenging for quadrotor models. To confront these problems, first, a dynamic inversion technique with zero dynamics stabilization loop is introduced to a practical quadrotor model, second, an adaptive-backstepping technique is developed to a lagrangian quadrotor model. The stabilizing control laws for both of these techniques are developed using on Lyapunov based method; and b) Coordination of multi-agent systems: coordination among multiple agents is generally done based on balanced or bi-directed communication graph models. If the agents are nonlinear and passive then for a balanced graph model synchronization is possible. But, for other than balanced and bi-directed graph models, it is difficult to synchronize nonlinear systems. Moreover, the performance of synchronization is normally
Design of Adaptive Switching Controller for Robotic Manipulators with Disturbance
Directory of Open Access Journals (Sweden)
Zhen Yang
2016-01-01
Full Text Available Two adaptive switching control strategies are proposed for the trajectory tracking problem of robotic manipulator in this paper. The first scheme is designed for the supremum of the bounded disturbance for robot manipulator being known; while the supremum is not known, the second scheme is proposed. Each proposed scheme consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theorem, it is shown that two new schemes can guarantee tracking performance of the robotic manipulator and be adapted to the alternating unknown loads. Simulations for two-link robotic manipulator are carried out and show that the two schemes can avoid the overlarge input torque, and the feasibility and validity of the proposed control schemes are proved.
Boiler operation with adaptive control; Kesselbetrieb mit adaptiver Fuehrungsregelung
Energy Technology Data Exchange (ETDEWEB)
Blens, Christian; Schreiber, Michael; Voss, Alexander [EUtech Scientific Engineering GmbH, Aachen (Germany)
2008-07-01
With EUcontrol, EUtech Scientific engineering GmbH (Aachen, Federal Republic of Germany) developed an adaptive control for the optimized operation of a large steam generator. Superior regulations undertake the tasks of process optimization for the increase of availability and efficiency as well as for the control and reduction of emissions. Changing boundary conditions on different time scales constantly are identified and considered in the adaptive modelling. Like that, it is possible to operate a boiler constantly in an optimal instrument range. Thus, optimization goals and boundary conditions can be formulated flexibly and adapted rapidly to the operational requirements. EUcontrol is designed to serve different interfaces to the control technology and is suitable for the optimization of already existing plants.
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.
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
An adaptive fuzzy logic controller for robot-manipulator
Directory of Open Access Journals (Sweden)
Tran Thu Ha
2008-11-01
Full Text Available In this paper, an adaptive fuzzy controller is designed for the robot-manipulator. The synthesized controller ensures that 1 the close-loop system is globally stable and 2 the tracking error converges to zero asymptotically and a cost function is minimized. The fuzzy controller is synthesized from a collection of IF-THEN rules. The parameters of the membership functions characterizing the linguistic terms change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. The proposed control scheme is demonstrated in a typical nonlinear plant two link manipulator. The computer simulation of control is done by the language MATLAB. The results of simulation show that the adaptipresented results are analyzed.
Kopasakis, George
1997-01-01
Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.
Adaptive Neuro-Fuzzy Inference System based DVR Controller Design
Directory of Open Access Journals (Sweden)
Brahim FERDI
2011-06-01
Full Text Available PI controller is very common in the control of DVRs. However, one disadvantage of this conventional controller is its inability to still working well under a wider range of operating conditions. So, as a solution fuzzy controller is proposed in literature. But, the main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy Inference System (ANFIS based controller design is proposed. The resulted controller is composed of Sugeno fuzzy controller with two inputs and one output. According to the error and error rate of the control system and the output data, ANFIS generates the appropriate fuzzy controller. The simulation results have proved that the proposed design method gives reliable powerful fuzzy controller with a minimum number of membership functions.
Rotor Field Oriented Control with adaptive Iron Loss Compensation
DEFF Research Database (Denmark)
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
1999-01-01
of the motor referenced to the rotor magnetizing current, and with the extension of an iron loss resistor added in parallel to the magnetizing inductance. The resistor estimator is based on the observation that the actual applied stator voltages deviates from the voltage estimated, when a motor is current...... controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....
Decentralized model reference adaptive control of large flexible structures
Lee, Fu-Ming; Fong, I-Kong; Lin, Yu-Hwan
1988-01-01
A decentralized model reference adaptive control (DMRAC) method is developed for large flexible structures (LFS). The development follows that of a centralized model reference adaptive control for LFS that have been shown to be feasible. The proposed method is illustrated using a simply supported beam with collocated actuators and sensors. Results show that the DMRAC can achieve either output regulation or output tracking with adequate convergence, provided the reference model inputs and their time derivatives are integrable, bounded, and approach zero as t approaches infinity.
Adaptive control strategies for interlimb coordination in legged robots
DEFF Research Database (Denmark)
Aoi, Shinya; Manoonpong, Poramate; Ambe, Yuichi
2017-01-01
Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear....... Recently, investigations of the adaptationmechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination...... for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms...
Global Adaptation Controlled by an Interactive Consistency Protocol
Directory of Open Access Journals (Sweden)
Alina Lenz
2017-05-01
Full Text Available Static schedules for systems can lead to an inefficient usage of the resources, because the system’s behavior cannot be adapted at runtime. To improve the runtime system performance in current time-triggered Multi-Processor System on Chip (MPSoC, a dynamic reaction to events is performed locally on the cores. The effects of this optimization can be increased by coordinating the changes globally. To perform such global changes, a consistent view on the system state is needed, on which to base the adaptation decisions. This paper proposes such an interactive consistency protocol with low impact on the system w.r.t. latency and overhead. We show that an energy optimizing adaptation controlled by the protocol can enable a system to save up to 43% compared to a system without adaptation.
Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control
Directory of Open Access Journals (Sweden)
Simone Baldi
2013-05-01
Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.
Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks
Jorgensen, Charles C.
1997-01-01
A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.
Evaluation-Function-based Model-free Adaptive Fuzzy Control
Directory of Open Access Journals (Sweden)
Agus Naba
2016-12-01
Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark veriﬁed the proposed scheme’s efficacy.
An Improved Adaptive Tracking Controller of Permanent Magnet Synchronous Motor
Directory of Open Access Journals (Sweden)
Tat-Bao-Thien Nguyen
2014-01-01
Full Text Available This paper proposes a new adaptive fuzzy neural control to suppress chaos and also to achieve the speed tracking control in a permanent magnet synchronous motor (PMSM drive system with unknown parameters and uncertainties. The control scheme consists of fuzzy neural and compensatory controllers. The fuzzy neural controller with online parameter tuning is used to estimate the unknown nonlinear models and construct linearization feedback control law, while the compensatory controller is employed to attenuate the estimation error effects of the fuzzy neural network and ensure the robustness of the controlled system. Moreover, due to improvement in controller design, the singularity problem is surely avoided. Finally, numerical simulations are carried out to demonstrate that the proposed control scheme can successfully remove chaotic oscillations and allow the speed to follow the desired trajectory in a chaotic PMSM despite the existence of unknown models and uncertainties.
Adaptive Control of Artificial Pancreas Systems - A Review
Directory of Open Access Journals (Sweden)
Kamuran Turksoy
2014-01-01
Full Text Available Artificial pancreas (AP systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.
Adaptive control of artificial pancreas systems - a review.
Turksoy, Kamuran; Cinar, Ali
2014-01-01
Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.
Model-free adaptive control of advanced power plants
Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang
2015-08-18
A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
Adaptive Sliding Mode Control of MEMS AC Voltage Reference Source
Directory of Open Access Journals (Sweden)
Ehsan Ranjbar
2017-01-01
Full Text Available The accuracy of physical parameters of a tunable MEMS capacitor, as the major part of MEMS AC voltage reference, is of great importance to achieve an accurate output voltage free of the malfunctioning noise and disturbance. Even though strenuous endeavors are made to fabricate MEMS tunable capacitors with desiderated accurate physical characteristics and ameliorate exactness of physical parameters’ values, parametric uncertainties ineluctably emerge in fabrication process attributable to imperfections in micromachining process. First off, this paper considers applying an adaptive sliding mode controller design in the MEMS AC voltage reference source so that it is capable of giving off a well-regulated output voltage in defiance of jumbling parametric uncertainties in the plant dynamics and also aggravating external disturbance imposed on the system. Secondly, it puts an investigatory comparison with the designed model reference adaptive controller and the pole-placement state feedback one into one’s prospective. Not only does the tuned adaptive sliding mode controller show remarkable robustness against slow parameter variation and external disturbance being compared to the pole-placement state feedback one, but also it immensely gets robust against the external disturbance in comparison with the conventional adaptive controller. The simulation results are promising.
Liquid-crystal intraocular adaptive lens with wireless control
Simonov, A.N.; Vdovine, G.V.; Loktev, M.
2007-01-01
We present a prototype of an adaptive intraocular lens based on a modal liquid-crystal spatial phase modulator with wireless control. The modal corrector consists of a nematic liquid-crystal layer sandwiched between two glass substrates with transparent low- and high-ohmic electrodes, respectively.
Adaptive control and synchronization of a fractional-order chaotic ...
Indian Academy of Sciences (India)
journal of. April 2013 physics pp. 583–592. Adaptive control and synchronization of a fractional-order chaotic system. CHUNLAI LI1,∗ and YAONAN TONG2. 1College of Physics and Electronics; 2School of Information and Communication Engineering,. Hunan Institute of Science and Technology, Yueyang 414006, China.
Fuzzy adaptive PID control for six rotor eppo UAV
Directory of Open Access Journals (Sweden)
Yongwei LI
2017-02-01
Full Text Available Six rotor eppo drones's load change itself in the job process will reduce the aircraft flight control performance and make the resistance to environmental disturbance being poor. In order to improve the six rotor eppo unmanned aerial vehicle (UAV control performance, the UAV in the process of spraying pesticide is analyzed and the model is constructed, then the eppo UAV time-varying dynamics mathematical model is deduced, and a fuzzy adaptive PID control algorithm is proposed. Fuzzy adaptive PID algorithm has good adaptability and the parameter setting is simple, which improves the system dynamic response and steady state performance, realizing the stability of the six rotor eppo UAV flight. With measured parameters of each sensor input in to the fuzzy adaptive PID algorithm, the corresponding control quality is obtained, and the stable operation of aircraft is realized. Through using Matlab to simulate the flight system and combining the practical experiments, it shows that the dynamic performance and stability of the system is improved effetively.
Physiological effects of Adaptive Cruise Control behaviour in real driving
Brouwer, A.M.; Snelting, A.F.; Jaswa, M.; Flascher, O.; Krol, L.R.; Zander, T.O.
2017-01-01
We examined physiological responses to behavior of an Adaptive Cruise Control (ACC) system during real driving. ACC is an example of automating a task that used to be performed by the user. In order to preserve the link between the user and an automated system such that they work together optimally,
Optimal adaptive scheduling and control of beer membrane filtration
Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.
2015-01-01
An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the
Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks
DEFF Research Database (Denmark)
Fafoutis, Xenofon; Dragoni, Nicola
2012-01-01
ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever...
Model-free adaptive sliding mode controller design for generalized ...
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 89; Issue 3. Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks. L M WANG. Research Article Volume 89 Issue 3 September 2017 Article ID 38 ...
Adaptive Leader-Follower Formation Control for Autonomous Mobile Robots
Guo, Jing; Lin, Zhiyun; Cao, Ming; Yan, Gangfeng
2010-01-01
In this paper, adaptive formation control is addressed for a network of autonomous mobile robots in which there are only two leaders knowing the prescribed reference velocity while the others just play the role of followers. Assuming that each follower has only two neighbors to form a cascade
Vision-based adaptive cruise control using pattern matching
CSIR Research Space (South Africa)
Kanjee, R
2013-10-01
Full Text Available Adaptive Cruise Control (ACC) is a relatively new system designed to assist automobile drivers in maintaining a safe following distance. This paper proposes and validates a vision-based ACC system which uses a single camera to obtain the clearance...
LFC based adaptive PID controller using ANN and ANFIS techniques
Directory of Open Access Journals (Sweden)
Mohamed I. Mosaad
2014-12-01
Full Text Available This paper presents an adaptive PID Load Frequency Control (LFC for power systems using Neuro-Fuzzy Inference Systems (ANFIS and Artificial Neural Networks (ANN oriented by Genetic Algorithm (GA. PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.
Cascaded adaptive control of ocean vehicles with significant actuator dynamics
Directory of Open Access Journals (Sweden)
Thor I. Fossen
1994-04-01
Full Text Available This paper presents a cascade adaptive control scheme for marine vehicles where the non-linear equations of motion include a model of the actuator dynamics. The adaptive controller does not require the parameters of the vehicle dynamics and the actuator time constants to be known a priori. Both the velocity and position tracking errors are shown to converge to zero by applying Barbalat's lemma. Global asymptotic stability is proven for the velocity scheme while the position/attitude controller is only proven to be convergent. Furthermore, all parameter estimates are shown to be bounded. Computer simulations of an ROV speed control system and an autopilot for automatic ship steering are used to illustrate the design methodology.
Dual adaptive dynamic control of mobile robots using neural networks.
Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato
2009-02-01
This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.
Neural network based adaptive output feedback control: Applications and improvements
Kutay, Ali Turker
Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in
Adaptive PID control based on orthogonal endocrine neural networks.
Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D
2016-12-01
A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.
Adaptive Control of Robotic arm with Hysteretic Joint
Kannan, Somasundar; Bezzaoucha, Souad; Quintanar Guzman, Serket; Olivares Mendez, Miguel Angel; Voos, Holger
2016-01-01
This article addresses the problem of control of robotic arm with a hysteretic joint behavior. The mechanical design of the one-degree of freedom robotic arm is presented where the joint is actuated by a Shape Memory Alloy (SMA) wire. The SMA wire based actuation of the joint makes the robotic arm lightweight but at the same time introduces hysteresis type nonlinearities. The nonlinear dynamic model of the robotic arm is introduced and an Adaptive control solution is pres...
Adaptive Control of the Chaotic System via Singular System Approach
Directory of Open Access Journals (Sweden)
Yudong Li
2014-01-01
Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
Robust Adaptive Control via Neural Linearization and Compensation
Directory of Open Access Journals (Sweden)
Roberto Carmona Rodríguez
2012-01-01
Full Text Available We propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure the stability of neural identification. Then four types of compensator are addressed. The stability of closed-loop system is also proven.
Adaptive piezoelectric sensoriactuators for active structural acoustic control
Vipperman, Jeffrey Stuart
1997-09-01
A new transducer technology with application to active control systems, modal analysis, and autonomous system health monitoring, is brought to fruition in this work. It has the advantages of being lightweight, potentially cost-effective, self-tuning, has negligible dynamics, and most importantly (from a robustness perspective), it provides a colocated sensor/actuator pair. The transducer consists of a piezoceramic element which serves as both an actuator and a sensor and will be referred to in this work as a sensoriactuator. Simple, adaptive signal processing in conjunction with a voltage controlled amplifier, reference capacitor, and a common-mode rejection circuit extract the mechanical response from the total response of the piezoelectric sensoriactuator for sensing. The digital portion of the adaptive piezoelectric sensoriactuator merely serves to tune the circuit, avoiding the potentially destabilizing effects of introducing a digital delay in the signal path, when used for feedback control applications. Adaptive compensation of the sensoriactuator is necessary since the signal to noise ratio is typically greater than 40 dB, making it prohibitive to tune the circuit manually. In addition, the constitutive properties of piezoceramics vary with time and environment, necessitating that the circuit be periodically re-tuned. The analog portion of the hardware is based upon op-amp circuits and an AD632 analog multiplier chip, which serves as both a voltage controlled amplifier (VCA) and a common mode rejection (CMR) circuit. A single coefficient least-mean square (LMS) adaptive filter continuously adjusts the gain of the VCA circuit as necessary. Nonideal behavior of piezoceramics is discussed along with methods to counter the consequential deterioration in circuit performance. A multiple input multiple output (MIMO) implementation of the adaptive piezoelectric sensoriactuator is developed using orthogonal white noise training signals for each sensoriactuator. Two
Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems
Esogbue, Augustine O.
1998-01-01
The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of
Divided attention impairs human motor adaptation but not feedback control.
Taylor, Jordan A; Thoroughman, Kurt A
2007-07-01
When humans experience externally induced errors in a movement, the motor system's feedback control compensates for those errors within the movement. The motor system's predictive control then uses information about those errors to inform future movements. The role of attention in these two distinct motor processes is unclear. Previous experiments have revealed a role for attention in motor learning over the course of many movements; however, these experimental paradigms do not determine how attention influences within-movement feedback control versus across-movement adaptation. Here we develop a dual-task paradigm, consisting of movement and audio tasks, which can differentiate and expose attention's role in these two processes of motor control. Over the course of several days, subjects performed horizontal reaching movements, with and without the audio task; movements were occasionally subjected to transient force perturbations. On movements with a force perturbation, subjects compensated for the force-induced movement errors, and on movements immediately after the force perturbation subjects exhibited adaptation. On every movement trial, subjects performed a two-tone frequency-discrimination task. The temporal specificity of the frequency-discrimination task allowed us to divide attention within and across movements. We find that divided attention did not impair the within-movement feedback control of the arm, but did reduce subsequent movement adaptation. We suggest that the secondary task interfered with the encoding and transformation of errors into changes in predictive control.
Enhanced adaptive fuzzy sliding mode control for uncertain nonlinear systems
Roopaei, Mehdi; Zolghadri, Mansoor; Meshksar, Sina
2009-09-01
In this article, a novel Adaptive Fuzzy Sliding Mode Control (AFSMC) methodology is proposed based on the integration of Sliding Mode Control (SMC) and Adaptive Fuzzy Control (AFC). Making use of the SMC design framework, we propose two fuzzy systems to be used as reaching and equivalent parts of the SMC. In this way, we make use of the fuzzy logic to handle uncertainty/disturbance in the design of the equivalent part and provide a chattering free control for the design of the reaching part. To construct the equivalent control law, an adaptive fuzzy inference engine is used to approximate the unknown parts of the system. To get rid of the chattering, a fuzzy logic model is assigned for reaching control law, which acting like the saturation function technique. The main advantage of our proposed methodology is that the structure of the system is unknown and no knowledge of the bounds of parameters, uncertainties and external disturbance are required in advance. Using Lyapunov stability theory and Barbalat's lemma, the closed-loop system is proved to be stable and convergence properties of the system is assured. Simulation examples are presented to verify the effectiveness of the method. Results are compared with some other methods proposed in the past research.
Petit, Cyril; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François
2009-06-01
We present a comprehensive analysis of the linear quadratic Gaussian control approach applied to adaptive optics (AO) and multiconjugated AO (MCAO) based on numerical and experimental validations. The structure of the control law is presented and its main properties discussed. We then propose an extended experimental validation of this control law in AO and a simplified MCAO configuration. Performance is compared with end-to-end numerical simulations. Sensitivity of the performance regarding tuning parameters is tested. Finally, extension to full MCAO and laser tomographic AO (LTAO) through numerical simulation is presented and analyzed.
DEFF Research Database (Denmark)
Alphinas, Robert A.; Hansen, Hans Henrik; Tambo, Torben
2017-01-01
Non-adaptive proportional controllers suffer from the ability to handle a system disturbance leading to a large steady-state error and undesired transient behavior. On the other hand, they are easy to implement and tune. This article examines whether an adaptive controller based on the MIT...... and Lyapunov principle leads to a more robust and accurate regulation. Both controllers have been tested on a thermodynamic system exposed to a disturbance. The experiment shows that the adaptive controller handles the disturbance faster and more accurate....
Adaptive Algorithm for the Quality Control of Braided Sleeving
Directory of Open Access Journals (Sweden)
Miha Pipan
2014-09-01
Full Text Available We describe the development and application of a robot vision based adaptive algorithm for the quality control of the braided sleeving of high pressure hydraulic pipes. With our approach, we can successfully overcome the limitations, such as low reliability and repeatability of braided quality, which result from the visual observation of the braided pipe surface. The braids to be analyzed come in different dimensions, colors, and braiding densities with different types of errors to be detected, as presented in this paper. Therefore, our machine vision system, consisting of a mathematical algorithm for the automatic adaptation to different types of braids and dimensions of pipes, enables the accurate quality control of braided pipe sleevings and offers the potential to be used in the production of braiding lines of pipes. The principles of the measuring method and the required equipment are given in the paper, also containing the mathematical adaptive algorithm formulation. The paper describes the experiments conducted to verify the accuracy of the algorithm. The developed machine vision adaptive control system was successfully tested and is ready for the implementation in industrial applications, thus eliminating human subjectivity.
Implementation of Adaptive Digital Controllers on Programmable Logic Devices
Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)
2002-01-01
Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment
Biologically-inspired Adaptive Movement Control for a Quadrupedal Robot
Directory of Open Access Journals (Sweden)
Haojun Zheng
2013-08-01
Full Text Available Biologically-inspired robot motion control has attracted a lot of interests because of its potential to make a robot perform better and the value of such study to understand animals' behaviors. This paper presented a quadrupedal robot, Biosbot, with variety of motion abilities and adaptability to its environment. We employed biological neural mechanisms, such as central pattern generator, flexor reflex and postural reflex as Biosbot's control system, meanwhile designed its acts after its animal counterpart, a cat. Biosbot can walk in different gaits, transfer from one gait to another, turn, clear obstacles and walk up and down hill autonomously, to adapt to its environment. The successful walking experiments with Biosbot prove the approach and control model has the ability to improve legged robot's performances.
Adaptive nonlinear control of missiles using neural networks
McFarland, Michael Bryan
Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear
Block Algorithms for the Control of Adaptive Antenna Arrays
Directory of Open Access Journals (Sweden)
Z. Tobes
1995-09-01
Full Text Available Presented paper deals with the reduction of computational requirements of gradient algorithms for the control of adaptive antenna arrays. Reduction of arithmetical complexity is reached here by the application of a block signal processing to adaptive algorithms. Block versions of the classical Least Mean Square (LMS algorithm and the Simplified Kalman Filter (SKF are described in this submission. Adaptation parameters of the presented algorithms are illustrated by results of computer simulations. The block SKF (BSKF exhibits twice higher computational requirements than LMS, the same misadjustment as LMS and lower rate of convergence than LMS when transversal filters have great number of taps and when relatively high block length of BSKF is used.
Adaptive Vibration Control System for MR Damper Faults
Directory of Open Access Journals (Sweden)
Juan C. Tudón-Martínez
2015-01-01
Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.
Adaptation with disturbance attenuation in nonlinear control systems
Energy Technology Data Exchange (ETDEWEB)
Basar, T. [Univ. of Illinois, Urbana, IL (United States)
1997-12-31
We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.
Zhou, Miaolei; Zhang, Yannan; Ji, Kun; Zhu, Dong
2017-06-16
Magnetically controlled shape memory alloy (MSMA) actuators take advantages of their large deformation and high controllability. However, the intricate hysteresis nonlinearity often results in low positioning accuracy and slow actuator response. In this paper, a modified Krasnosel'skii-Pokrovskii model was adopted to describe the complicated hysteresis phenomenon in the MSMA actuators. Adaptive recursive algorithm was employed to identify the density parameters of the adopted model. Subsequently, to further eliminate the hysteresis nonlinearity and improve the positioning accuracy, the model reference adaptive control method was proposed to optimize the model and inverse model compensation. The simulation experiments show that the model reference adaptive control adopted in the paper significantly improves the control precision of the actuators, with a maximum tracking error of 0.0072 mm. The results prove that the model reference adaptive control method is efficient to eliminate hysteresis nonlinearity and achieves a higher positioning accuracy of the MSMA actuators.
Adaptive and Robust Sliding Mode Position Control of IPMSM Drives
Directory of Open Access Journals (Sweden)
ZAKY, M.
2017-02-01
Full Text Available This paper proposes an adaptive and robust sliding mode control (SMC for the position control of Interior Permanent Magnet Synchronous Motor (IPMSM drives. A switching surface of SMC is designed using a Linear Quadratic Regulator (LQR technique to simultaneously control the tracking trajectory and load torque changes. The quadratic optimal control method is used to select the state feedback control gain that constitutes the system dynamic performance under uncertainties and disturbances. Feedback and switching gains are selected to satisfy both stability and fast convergence of the IPMSM. Matlab/Simulink is used to build the drive system. Experimental implementation of the IPMSM drive is carried out using DSP-DS1102 control board. The efficacy of the proposed position control method is validated using theoretical analysis and simulation and experimental results.
Adaptive Tracking Control for Robots With an Interneural Computing Scheme.
Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang
2017-01-24
Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.
Flexible Joints Robotic Manipulator Control By Adaptive Gain Smooth Sliding Observer-Controller
Directory of Open Access Journals (Sweden)
A. FILIPESCU
2003-12-01
Full Text Available An adaptive gain sliding observer for uncertain parameter nonlinear systems together with an adaptive gain sliding controller is proposed in this paper. It considered nonlinear, SISO affine systems, with uncertainties in steady-state functions and parameters. A further parameter term, adaptively updated, has been introduced in steady state space model of the controlled system, in order to obtain useful information despite fault detection and isolation. By using of the sliding observer with adaptive gain, the robustness to uncertainties is increased and the parameters adaptively updated can provide useful information in fault detection. Also, the state estimation error is bounded accordingly with bound limits of the uncertainties. The both of them, the sliding adaptive observer and sliding controller are designed to fulfill the attractiveness condition of its corresponding switching surface. An application to a single arm with flexible joint robot is presented. In order to alleviate chattering, a parameterized tangent hyperbolic has been used as switching function, instead of pure relay one, to the observer and the controller. Also, the gains of the switching functions, to the sliding observer and sliding controller are adaptively updated depending of estimation error and tracking error, respectively. By the using adaptive gains, the transient and tracking response can be improved.
Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control
Eshak, Peter B.
Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to
Adaptive suboptimal second-order sliding mode control for microgrids
Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella
2016-09-01
This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.
Direct model reference adaptive control of a flexible robotic manipulator
Meldrum, D. R.
1985-01-01
Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.
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...... 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...
Towards feasible and effective predictive wavefront control for adaptive optics
Energy Technology Data Exchange (ETDEWEB)
Poyneer, L A; Veran, J
2008-06-04
We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.
Dynamic Performance of Grid Converters using Adaptive DC Voltage Control
DEFF Research Database (Denmark)
Trintis, Ionut; Sun, Bo; Guerrero, Josep M.
2014-01-01
This paper investigates a controller that ensures minimum operating dc-link voltage of a back-to-back converter system. The dc-link voltage adapts its reference based on the system state, reference given by an outer loop to the dc-link voltage controller. The operating dc-link voltage should...... be kept as low as possible to increase the power conversion efficiency and increase the reliability of converters. The dynamic performance of the proposed controller is investigated by simulations and experiments....
Adaptive Superheat Control of a Refrigeration Plant using Backstepping
DEFF Research Database (Denmark)
Rasmussen, Henrik
2008-01-01
. A new low order nonlinear model of the evaporator is developed and used in a backstepping design of an adaptive nonlinear controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results shows the performance of the system for a wide range......This paper proposes a novel method for superheat and capacity control of refrigeration systems. The new idea is to control the superheat by the compressor speed and capacity by the refrigerant flow. This gives a highly nonlinear transfer operator from compressor speed input to the superheat output...
Adaptive and predictive control of a simulated robot arm.
Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo
2013-06-01
In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs).
An adaptive learning control system for large flexible structures
Thau, F. E.
1985-01-01
The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.
Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller
Engel, E.; Kovalev, I. V.; Karandeev, D.
2015-10-01
The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.
Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems
Volyanskyy, Kostyantyn Y.
Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance
Adaptive model predictive process control using neural networks
Buescher, K.L.; Baum, C.C.; Jones, R.D.
1997-08-19
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.
SECONDARY VOLTAGE CONTROL BASED ON ADAPTIVE NEURAL PI CONTROLLERS
Directory of Open Access Journals (Sweden)
RUBEN TAPIA
2010-01-01
Full Text Available Este trabajo tiene como objetivo presentar el desempeño de un controlador basado en redes neuronales Bspline que regula el aporte de potencia reactiva de las máquinas síncronas. Debido a que los sistemas de potencia operan con parámetros no estacionarios y configuración cambiante, es preferible utilizar esquemas de control adaptativos. La tecnología de control debe asegurar su desempeño en términos de condiciones operativas prácticas de los sistemas de potencia, que considere la diversidad de cargas conectadas a la red y maximice la disponibilidad de recursos. La red neuronal Bspline es una herramienta conveniente para implementar el control adaptativo de voltaje, con la posibilidad de llevar a cabo ésta tarea enlínea considerando las no linealidades del sistema. El despacho de potencia reactiva se basa en la premisa de que cada máquina debe aportar en proporción a su capacidad nominal de operación. La aplicabilidad de la propuesta se demuestra mediante simulación en un sistema de potencia multimáquinas.
Adaptive sliding mode formation control of multiple underwater robots
Directory of Open Access Journals (Sweden)
Das Bikramaditya
2014-12-01
Full Text Available This paper proposes a new adaptive sliding mode control scheme for achieving coordinated motion control of a group of autonomous underwater vehicles with variable added mass. The control law considers the communication constraints in the acoustic medium. A common reference frame for velocity is assigned to a virtual leader dynamically. The performances of the proposed adaptive SMC were compared with that of a passivity based controller. To save the time and traveling distance for reaching the FRP by the follower AUVs, a sliding mode controller is proposed in this paper that drives the state trajectory of the AUV into a switching surface in the state space. It is observed from the obtained results that the proposed SMC provides improved performance in terms of accurately tracking the desired trajectory within less time compared to the passivity based controller. A communication consensus is designed ensuring the transfer of information among the AUVs so that they move collectively as a group. The stability of the overall closed-loop systems are analysed using Lyapunov theory and simulation results confirmed the robustness and efficiency of proposed controller.
Digital control of high performance aircraft using adaptive estimation techniques
Van Landingham, H. F.; Moose, R. L.
1977-01-01
In this paper, an adaptive signal processing algorithm is joined with gain-scheduling for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance STOL aircraft. The actual controller views the nonlinear behavior of the aircraft as equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. Nonlinear behavior is approximated by effective switching of the linear models at random times, with durations reflecting aircraft motion in response to pilot commands.
Input error versus output error model reference adaptive control
Bodson, Marc; Sastry, Shankar
1987-01-01
Algorithms for model reference adaptive control were developed in recent years, and their stability and convergence properties have been investigated. Typical algorithms in continuous time involve strictly positive real conditions on the reference model, while similar discrete time algorithms do not require such conditions. It is shown how algorithms differ by the use of an input error versus an output error, and present a continuous time input error adaptive control algorithm which does not involve SPR conditions. The connections with other schemes are discussed. The input error scheme has general stability and ocnvergence properties that are similar to the output error scheme. However, analysis using averaging methods reveals some preferable convergence properties of the input error scheme. Several other advantages are also discussed.
Robust Adaptive Algorithm by an Adaptive Zero Attractor Controller of ZA-LMS Algorithm
Directory of Open Access Journals (Sweden)
Radhika Sivashanmugam
2016-01-01
Full Text Available This paper proposes a new approach to identify time varying sparse systems. The proposed approach uses Zero-Attracting Least Mean Square (ZA-LMS algorithm with an adaptive optimal zero attractor controller which can adapt dynamically to the sparseness level and provide appreciable performance in all environments ranging from sparse to nonsparse conditions. The optimal zero attractor controller is derived based on the criterion that confirms largest decrease in mean square deviation (MSD error. A simple update rule is also proposed to change the zero attractor controller based on the level of sparsity. It is found that, for nonsparse system, the proposed approach converges to LMS (as ZA-LMS cannot outperform LMS when the system is nonsparse and, for highly sparse system, as the proposed approach is based on optimal zero attractor controller, it converges either similar to ZA-LMS or even better than ZA-LMS (depending on the value of zero attractor controller chosen for ZA-LMS algorithm. The performance of the proposed algorithm is better than ZA-LMS and LMS when the system is semisparse. Simulations were performed to prove that the proposed algorithm is robust against variable sparsity level.
Control algorithms and applications of the wavefront sensorless adaptive optics
Ma, Liang; Wang, Bin; Zhou, Yuanshen; Yang, Huizhen
2017-10-01
Compared with the conventional adaptive optics (AO) system, the wavefront sensorless (WFSless) AO system need not to measure the wavefront and reconstruct it. It is simpler than the conventional AO in system architecture and can be applied to the complex conditions. Based on the analysis of principle and system model of the WFSless AO system, wavefront correction methods of the WFSless AO system were divided into two categories: model-free-based and model-based control algorithms. The WFSless AO system based on model-free-based control algorithms commonly considers the performance metric as a function of the control parameters and then uses certain control algorithm to improve the performance metric. The model-based control algorithms include modal control algorithms, nonlinear control algorithms and control algorithms based on geometrical optics. Based on the brief description of above typical control algorithms, hybrid methods combining the model-free-based control algorithm with the model-based control algorithm were generalized. Additionally, characteristics of various control algorithms were compared and analyzed. We also discussed the extensive applications of WFSless AO system in free space optical communication (FSO), retinal imaging in the human eye, confocal microscope, coherent beam combination (CBC) techniques and extended objects.
Adaptive Dynamics, Control, and Extinction in Networked Populations
2015-07-09
Adaptive Dynamics, Control, and Extinction in Networked Populations Ira B. Schwartz US Naval Research Laboratory Code 6792 Nonlinear System Dynamics...theory of large deviations to stochastic network extinction to predict extinction times. In particular, we use the theory to find the most probable...paths leading to extinction . We then apply the methodology to network models and discover how mean extinction times scale with network parameters in Erdos
Power Control Imperfection in CDMA Systems with Adaptive Antennas
Directory of Open Access Journals (Sweden)
V. Wieser
2002-12-01
Full Text Available This paper deals with a simulation of cellular CDMA system usingbase station adaptive antennas. The model assumes two tiers area, fourtypes of antennas, lognormal shadowing corresponding to three types ofenvironments and perfect power control or two values of power controlerror, respectively. The capacity of system in up-link is evaluated bya number of mobile stations with higher signal to interference ratiothan threshold with given outage probability.
Synthesis of adaptive traffic control discrete neminimalno-phase system
Directory of Open Access Journals (Sweden)
В.М. Азарсков
2007-01-01
Full Text Available An adaptive approach to synthesizing the digital tracking system with direct set-point coupling is extended under conditions when a plant is non-minimum phase. Some bounded set of belonging of servo drive unknown parameters vector is believed to be known. The object’s model non-singularity condition is established. The asymptotical properties of control system are studied. Simulation results are given.
Laser diodes for sensing applications: adaptive cruise control and more
Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian
2005-02-01
Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.
Comparison of Adaptive Antenna Arrays Controlled by Gradient Algorithms
Directory of Open Access Journals (Sweden)
Z. Raida
1994-09-01
Full Text Available The paper presents the Simple Kalman filter (SKF that has been designed for the control of digital adaptive antenna arrays. The SKF has been applied to the pilot signal system and the steering vector one. The above systems based on the SKF are compared with adaptive antenna arrays controlled by the classical LMS and the Variable Step Size (VSS LMS algorithms and by the pure Kalman filter. It is shown that the pure Kalman filter is the most convenient for the control of the adaptive arrays because it does not require any a priori information about noise statistics and excels in high rate of convergence and low misadjustment. Extremely high computational requirements are drawback of this filter. Hence, if low computational power of signal processors is at the disposal, the SKF is recommended to be used. Computational requirements of the SKF are of the same order as the classical LMS algorithm exhibits. On the other hand, all the important features of the pure Kalman filter are inherited by the SKF. The paper shows that presented Kalman filters can be regarded as special gradient algorithms. That is why they can be compared with the LMS family.
Adaptive Proactive Inhibitory Control for Embedded Real-time Applications
Directory of Open Access Journals (Sweden)
Shufan eYang
2012-06-01
Full Text Available Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real time while achieving behavioural performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control.
Frequency Adaptability of Harmonics Controllers for Grid-Interfaced Converters
DEFF Research Database (Denmark)
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
2017-01-01
A wider spread adoption of power electronic converters interfaced renewable energy systems has brought more attention to harmonic issues to the electrical grid, and means are taken to improve it in the control. More advanced closed-loop harmonic controllers are thus demanded to enhance...... sensitivity of the most popular harmonic controllers for grid-interfaced converters. The frequency adaptability of these harmonic controllers is evaluated in the presence of a variable grid frequency within a specified reasonable range, e.g., +-1% of the nominal grid frequency (50 Hz). Solutions...... the renewable energy integration in order to be grid-friendly. However, usually being treated as a constant factor in the design of harmonic controllers, the grid frequency varies with the generation-load imbalance, and thus may lead to deterioration of the power quality. This paper explores the frequency...
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.
Lei, Meizhen; Wang, Liqiang
2018-01-01
The halbach-type linear oscillatory motor (HT-LOM) is multi-variable, highly coupled, nonlinear and uncertain, and difficult to get a satisfied result by conventional PID control. An incremental adaptive fuzzy controller (IAFC) for stroke tracking was presented, which combined the merits of PID control, the fuzzy inference mechanism and the adaptive algorithm. The integral-operation is added to the conventional fuzzy control algorithm. The fuzzy scale factor can be online tuned according to the load force and stroke command. The simulation results indicate that the proposed control scheme can achieve satisfied stroke tracking performance and is robust with respect to parameter variations and external disturbance.
Piccinini, Giulio Francesco; Simões, Anabela; Rodrigues, Carlos Manuel; Leitão, Miguel
2012-01-01
The introduction of Adaptive Cruise Control (ACC) could be very helpful for making the longitudinal driving task more comfortable for the drivers and, as a consequence, it could have a global beneficial effect on road safety. However, before or during the usage of the device, due to several reasons, drivers might generate in their mind incomplete or flawed mental representations about the fundamental operation principles of ACC; hence, the resulting usage of the device might be improper, negatively affecting the human-machine interaction and cooperation and, in some cases, leading to negative behavioural adaptations to the system that might neutralise the desirable positive effects on road safety. Within this context, this paper will introduce the methodology which has been developed in order to analyse in detail the topic and foresee, in the future, adequate actions for the recovery of inaccurate mental representations of the system.
Driver's behavioral adaptation to adaptive cruise control (ACC): the case of speed and time headway.
Bianchi Piccinini, Giulio Francesco; Rodrigues, Carlos Manuel; Leitão, Miguel; Simões, Anabela
2014-06-01
The Adaptive Cruise Control is an Advanced Driver Assistance System (ADAS) that allows maintaining given headway and speed, according to settings pre-defined by the users. Despite the potential benefits associated to the utilization of ACC, previous studies warned against negative behavioral adaptations that might occur while driving with the system activated. Unfortunately, up to now, there are no unanimous results about the effects induced by the usage of ACC on speed and time headway to the vehicle in front. Also, few studies were performed including actual users of ACC among the subjects. This research aimed to investigate the effect of the experience gained with ACC on speed and time headway for a group of users of the system. In addition, it explored the impact of ACC usage on speed and time headway for ACC users and regular drivers. A matched sample driving simulator study was planned as a two-way (2×2) repeated measures mixed design, with the experience with ACC as between-subjects factor and the driving condition (with ACC and manually) as within-subjects factor. The results show that the usage of ACC brought a small but not significant reduction of speed and, especially, the maintenance of safer time headways, being the latter result greater for ACC users, probably as a consequence of their experience in using the system. The usage of ACC did not cause any negative behavioral adaptations to the system regarding speed and time headway. Based on this research work, the Adaptive Cruise Control showed the potential to improve road safety for what concerns the speed and the time headway maintained by the drivers. The speed of the surrounding traffic and the minimum time headway settable through the ACC seem to have an important effect on the road safety improvement achievable with the system. Copyright © 2014 Elsevier Ltd. All rights reserved.
On flexible CAD of adaptive control and identification algorithms
DEFF Research Database (Denmark)
Christensen, Anders; Ravn, Ole
1988-01-01
SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...... a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define...
Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System
Klein Wolterink, W.; Heijenk, Geert; Karagiannis, Georgios
2011-01-01
Cooperative Adaptive Cruise Control (CACC) is a form of cruise control in which a vehicle maintains a constant headway to its preceding vehicle using radar and vehicle-to-vehicle (V2V) communication. Within the Connect & Drive1 project we have implemented and tested a prototype of such a system, with IEEE 802.11p as the enabling communication technology. In this paper we present an extension of our CACC system that allows vehicles to merge inside a platoon of vehicles at a junction, i.e., at ...
Adaptive Reference Control for Pressure Management in Water Networks
DEFF Research Database (Denmark)
Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal
2015-01-01
Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
Directory of Open Access Journals (Sweden)
Xuhui Bu
2012-01-01
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Adaptive Fractional Fuzzy Sliding Mode Control for Multivariable Nonlinear Systems
Directory of Open Access Journals (Sweden)
Junhai Luo
2014-01-01
Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.
Berkhoff, Arthur P.; Wesselink, J.M.
2011-01-01
Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control(HAC)and low-authority control (LAC)is considered for improved
Li, Le-Bao; Sun, Ling-Ling; Zhang, Sheng-Zhou; Yang, Qing-Quan
2015-09-01
A new control approach for speed tracking and synchronization of multiple motors is developed, by incorporating an adaptive sliding mode control (ASMC) technique into a ring coupling synchronization control structure. This control approach can stabilize speed tracking of each motor and synchronize its motion with other motors' motion so that speed tracking errors and synchronization errors converge to zero. Moreover, an adaptive law is exploited to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort and attenuate chattering. Performance comparisons with parallel control, relative coupling control and conventional PI control are investigated on a four-motor synchronization control system. Extensive simulation results show the effectiveness of the proposed control scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Attaining the rate-independent limit of a rate-dependent strain gradient plasticity theory
DEFF Research Database (Denmark)
El-Naaman, Salim Abdallah; Nielsen, Kim Lau; Niordson, Christian Frithiof
2016-01-01
The existence of characteristic strain rates in rate-dependent material models, corresponding to rate-independent model behavior, is studied within a back stress based rate-dependent higher order strain gradient crystal plasticity model. Such characteristic rates have recently been observed...... rates for a selected quantity are identified through numerical analysis. Evidently, the concept of a characteristic rate, within the rate-dependent material models, may help unlock an otherwise inaccessible parameter space....
Non-linear and adaptive control of a refrigeration system
DEFF Research Database (Denmark)
Rasmussen, Henrik; Larsen, Lars F. S.
2011-01-01
In a refrigeration process heat is absorbed in an evaporator by evaporating a flow of liquid refrigerant at low pressure and temperature. Controlling the evaporator inlet valve and the compressor in such a way that a high degree of liquid filling in the evaporator is obtained at all compressor...... are capable of adapting to variety of systems. This paper proposes a novel method for superheat and capacity control of refrigeration systems; namely by controlling the superheat by the compressor speed and capacity by the refrigerant flow. A new low order nonlinear model of the evaporator is developed...... capacities ensures a high energy efficiency. The level of liquid filling is indirectly measured by the superheat. Introduction of variable speed compressors and electronic expansion valves enables the use of more sophisticated control algorithms, giving a higher degree of performance and just as important...
Stiffness control of magnetorheological gels for adaptive tunable vibration absorber
Kim, Hyun Kee; Kim, Hye Shin; Kim, Young-Keun
2017-01-01
In this study, a stiffness feedback control system for magnetorheological (MR) gel—a smart material of variable stiffness—is proposed, toward the design of a tunable vibration absorber that can adaptively tune to a time varying disturbance in real time. A PID controller was designed to track the required stiffness of the MR gel by controlling the magnitude of the target external magnetic field pervading the MR gel. This paper proposes a novel magnetic field generator that could produce a variable magnetic field with low energy consumption. The performance of the MR gel stiffness control was validated through experiments that showed the MR gel absorber system could be automatically tuned from 56 Hz to 67 Hz under a field of 100 mT to minimize the vibration of the primary system.
Frequency Adaptive Selective Harmonic Control for Grid-Connected Inverters
DEFF Research Database (Denmark)
Yang, Yongheng; Zhou, Keliang; Wang, Huai
2015-01-01
In this paper, a Frequency Adaptive Selective Harmonic Control (FA-SHC) scheme is proposed. The FA-SHC method is developed from a hybrid SHC scheme based on the internal model principle, which can be designed for gridconnected inverters to optimally mitigate feed-in current harmonics. The hybrid...... SHC scheme consists of multiple parallel recursive (nk±m)-order (k = 0, 1, 2, . . ., and m ≤ n/2) harmonic control modules with independent control gains, which can be optimally weighted in accordance with the harmonic distribution. The hybrid SHC thus offers an optimal trade-off among cost...... into the FA-SHC, being the proposed fractional order controller, when it is implemented with a fixed sampling rate. The FASHC is implemented by substituting the fractional order elements with the Lagrange polynomial based interpolation filters. The proposed FA-SHC scheme provides fast on-line computation...
Adaptive Control of a Vibratory Angle Measuring Gyroscope
Park, Sungsu
2010-01-01
This paper presents an adaptive control algorithm for realizing a vibratory angle measuring gyroscope so that rotation angle can be directly measured without integration of angular rate, thus eliminating the accumulation of numerical integration errors. The proposed control algorithm uses a trajectory following approach and the reference trajectory is generated by an ideal angle measuring gyroscope driven by the estimate of angular rate and the auxiliary sinusoidal input so that the persistent excitation condition is satisfied. The developed control algorithm can compensate for all types of fabrication imperfections such as coupled damping and stiffness, and mismatched stiffness and un-equal damping term in an on-line fashion. The simulation results show the feasibility and effectiveness of the developed control algorithm that is capable of directly measuring rotation angle without the integration of angular rate. PMID:22163667
Adaptive decoupled power control method for inverter connected DG
DEFF Research Database (Denmark)
Sun, Xiaofeng; Tian, Yanjun; Chen, Zhe
2014-01-01
The integration of renewable energy technology is making the power distribution system more flexible, but also introducing challenges for traditional technology. With the nature of intermittent and less inertial, renewable energy-based generations need effective control methods to cooperate...... an adaptive droop control method based on online evaluation of power decouple matrix for inverter connected distributed generations in distribution system. Traditional decoupled power control is simply based on line impedance parameter, but the load characteristics also cause the power coupling, and alter...... with other devices, such as storage, loads and the utility grid. The widely used power frequency (P–f) droop control is based on the precondition of inductive line impedance, but the low-voltage system is mainly resistive, and also the different load character needs to be considered. This study presents...
Direct model reference adaptive control of robotic arms
Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.
1993-01-01
The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.
Driver usage and understanding of adaptive cruise control.
Larsson, Annika F L
2012-05-01
Automation, in terms of systems such as adaptive/active cruise control (ACC) or collision warning systems, is increasingly becoming a part of everyday driving. These systems are not perfect though, and the driver has to be prepared to reclaim control in situations very similar to those the system easily handles by itself. This paper uses a questionnaire answered by 130 ACC users to discuss future research needs in the area of driver assistance systems. Results show that the longer drivers use their systems, the more aware of its limitations they become. Moreover, the drivers report that ACC forces them to take control intermittently. According to theory, this might actually be better than a more perfect system, as it provides preparation for unexpected situations requiring the driver to reclaim control. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Design and implementation of adaptive inverse control algorithm for a micro-hand control system
Directory of Open Access Journals (Sweden)
Wan-Cheng Wang
2014-01-01
Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.
Mullakkal Babu, F.A.; Wang, M.; van Arem, B.; Happee, R.; Rosetti, R.; Wolf, D.
2016-01-01
Current Full Range Adaptive Cruise Control (FRACC) systems switch between separate adaptive cruise control and collision avoidance systems. This can lead to jerky responses and discomfort during the transition between the two control modes. We propose a Full Range Adaptive Cruise Control (FRACC)
Synchronization of Fractional Chaotic Systems via Fractional-Order Adaptive Controller
Hosseinnia, S. H.; Ghaderi, R.; N., A. Ranjbar; Sadati, J.; Momani, S.
2012-01-01
In this paper, an adaptive fractional controller has been designed to control chaotic systems. In fact, this controller is a fractional PID controller, which the coefficients will be tuned according to a proper adaptation mechanism. The adaptation law will be constructed from a sliding surface via gradient method. The adaptive fractional controller is implemented on a gyro system to signify the performance of the proposed technique.
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Controls on Extreme Droughts and Adaptation Strategies in Semiarid Regions
Scanlon, B. R.; Cook, C.; Fernando, D. N.; LeBlanc, M.
2012-12-01
Increasing vulnerability to droughts with reduced per capita water storage, particularly in semiarid regions, underscores the need for predictive understanding of drought controls and development of adaptation strategies for water resources management. In this study we evaluate causes of major droughts in southwest and southcentral US (California and Texas) and southeast Australia (Murray Darling Basin). Impacts of climate cycles (ENSO, PDO, AMO, NAO, IOD) and atmospheric circulation on drought initiation and persistence are examined. Effects of drought on surface water reservoir storage, groundwater storage, irrigation, and crop production are compared. Adaptation strategies being evaluated include water transfers among sectors, particularly from irrigated agriculture to other groups, increasing storage using managed aquifer recharge, water reuse, and development of new water sources (e.g. seawater desalination). It is critical to develop a broad portfolio of water sources to increase resilience to future droughts.
Adaptive control for solar energy based DC microgrid system development
Zhang, Qinhao
During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)'s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed.
Adaptive control of systems in cascade with saturation
Kannan, Suresh K.
This thesis extends the use of neural-network-based model reference adaptive control to systems that occur as cascades. In general, these systems are not feedback linearizable. The approach taken is that of approximate feedback linearization of upper subsystems whilst treating the lower-subsystem states as virtual actuators. Similarly, lower-subsystems are also feedback linearized. Typically, approximate inverses are used for linearization purposes. Model error arising from the use of an approximate inverse is minimized using a neural-network as an adaptive element. Incorrect adaptation due to (virtual) actuator saturation and dynamics is avoided using the Pseudocontrol Hedging method. Using linear approximate inverses and linear reference models generally result in large desired pseudocontrol for large external commands. Even if the provided external command is feasible (null-controllable), there is no guarantee that the reference model trajectory is feasible. In order to mitigate this, nonlinear reference models based on nested-saturation methods are used to constrain the evolution of the reference model and thus the plant states. The method presented in this thesis lends itself to the inner-outer loop control of air vehicles, where the inner-loop controls attitude dynamics and the outer-loop controls the translational dynamics of the vehicle. The outer-loop treats the closed loop attitude dynamics as an actuator. Adaptation to uncertainty in the attitude, as well as the translational dynamics, is introduced, thus minimizing the effects of model error in all six degrees of freedom and leading to more accurate position tracking. A pole-placement approach is used to choose compensator gains for the tracking error dynamics. This alleviates timescale separation requirements, allowing the outer loop bandwidth to be closer to that of the inner loop, thus increasing position tracking performance. A poor model of the attitude dynamics and a basic kinematics model is
Damping Force Tracking Control of MR Damper System Using a New Direct Adaptive Fuzzy Controller
Directory of Open Access Journals (Sweden)
Xuan Phu Do
2015-01-01
Full Text Available This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR fluid based damper (MR damper in short system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition, H∞ (H infinity tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.
A new adaptive configuration of PID type fuzzy logic controller.
Fereidouni, Alireza; Masoum, Mohammad A S; Moghbel, Moayed
2015-05-01
In this paper, an adaptive configuration for PID type fuzzy logic controller (FLC) is proposed to improve the performances of both conventional PID (C-PID) controller and conventional PID type FLC (C-PID-FLC). The proposed configuration is called adaptive because its output scaling factors (SFs) are dynamically tuned while the controller is functioning. The initial values of SFs are calculated based on its well-tuned counterpart while the proceeding values are generated using a proposed stochastic hybrid bacterial foraging particle swarm optimization (h-BF-PSO) algorithm. The performance of the proposed configuration is evaluated through extensive simulations for different operating conditions (changes in reference, load disturbance and noise signals). The results reveal that the proposed scheme performs significantly better over the C-PID controller and the C-PID-FLC in terms of several performance indices (integral absolute error (IAE), integral-of-time-multiplied absolute error (ITAE) and integral-of-time-multiplied squared error (ITSE)), overshoot and settling time for plants with and without dead time. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Fault diagnosis and fault-tolerant control based on adaptive control approach
Shen, Qikun; Shi, Peng
2017-01-01
This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .
ER fluid applications to vibration control devices and an adaptive neural-net controller
Morishita, Shin; Ura, Tamaki
1993-07-01
Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.
Space Launch System Implementation of Adaptive Augmenting Control
Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.
2014-01-01
Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.
Adaptive Controller for Drive System PMSG in Wind Turbine
Directory of Open Access Journals (Sweden)
Gnanambal
2014-07-01
Full Text Available This paper proposes adaptive Maximum Power Point Tracking (MPPT controller for Permanent Magnet Synchronous Generator (PMSG wind turbine and direct power control for grid side inverter for transformer less integration of wind energy. PMSG wind turbine with two back to back voltage source converters are considered more efficient, used to make real and reactive power control. The optimal control strategy has introduced for integrated control of PMSG Maximum Power Extraction, DC link voltage control and grid voltage support controls. Simulation model using MATLAB Simulink has developed to investigate the performance of proposed control techniques for PMSG wind turbine steady and variable wind conditions. This paper shows that the direct driven grid connected PMSG system has excellent performances and confirms the feasibility of the proposed techniques. While the wind turbine market continues to be dominated by conventional gear-driven wind turbine systems, the direct drive is attracting attention. PM machines are more attractive and superior with higher efficiency and energy yield, higher reliability, and power-to-weight ratio compared with electricity-excited machines.
Nonlinear vibration with control for flexible and adaptive structures
Wagg, David
2015-01-01
This book provides a comprehensive discussion of nonlinear multi-modal structural vibration problems, and shows how vibration suppression can be applied to such systems by considering a sample set of relevant control techniques. It covers the basic principles of nonlinear vibrations that occur in flexible and/or adaptive structures, with an emphasis on engineering analysis and relevant control techniques. Understanding nonlinear vibrations is becoming increasingly important in a range of engineering applications, particularly in the design of flexible structures such as aircraft, satellites, bridges, and sports stadia. There is an increasing trend towards lighter structures, with increased slenderness, often made of new composite materials and requiring some form of deployment and/or active vibration control. There are also applications in the areas of robotics, mechatronics, micro electrical mechanical systems, non-destructive testing and related disciplines such as structural health monitoring. Two broader ...
Electro-magnetically controlled acoustic metamaterials with adaptive properties.
Malinovsky, Vladimir S; Donskoy, Dimitri M
2012-10-01
A design of actively controlled metamaterial is proposed and discussed. The metamaterial consists of layers of electrically charged nano or micro particles exposed to external magnetic field. The particles are also attached to compliant layers in a way that the designed structure exhibits two resonances: mechanical spring-mass resonance and electro-magnetic cyclotron resonance. It is shown that if the cyclotron frequency is greater than the mechanical resonance frequency, the designed structure could be highly attenuative (40-60 dB) for vibration and sound waves in very broad frequency range even for wavelength much greater than the thickness of the metamaterial. The approach opens up wide range of opportunities for design of adaptively controlled acoustic metamaterials by controlling magnetic field and/or electrical charges.
ADEX optimized adaptive controllers and systems from research to industrial practice
Martín-Sánchez, Juan M
2015-01-01
This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...
Work of breathing in adaptive pressure control continuous mandatory ventilation.
Mireles-Cabodevila, Eduardo; Chatburn, Robert L
2009-11-01
Adaptive pressure control is a mode of mechanical ventilation where inflation pressure is adjusted by the ventilator to achieve a target tidal volume (VT). This means that as patient effort increases, inflation pressure is reduced, which may or may not be clinically appropriate. The purpose of this study was to evaluate the relationship between ventilator work output and patient effort in adaptive pressure control. A lung simulator (ASL 5000) was set at compliance=0.025 L/cm H2O and resistance=10 cm H2O/L/s. Muscle pressure (Pmus) was a sine wave (20% inspiration, 5% hold, 20% release) that increased from 0-25 cm H2O in steps of 5 cm H2O. The adaptive-pressure-control modes tested were: AutoFlow (Dräger Evita XL), VC+ (Puritan Bennett 840), APV (Hamilton Galileo), and PRVC (Siemens Servo-i and Siemens Servo 300). The target VT was set at 320 mL (Pmus=15 cm H2O, inspiratory pressure=0 cm H2O) to allow delivery of a realistic VT as the simulated patient demanded more volume. All measurements were obtained from the simulator. Patient work of breathing (patient WOB) increased from 0 J/L to 1.88 J/L through the step increase in Pmus. Target VT was maintained as long as Pmus was below 10 cm H2O. VT then increased linearly with increased Pmus. The ventilators showed 3 patterns of behavior in response to an increase in Pmus: (1) ventilator WOB gradually decreased to 0 J/L as Pmus increased; (2) ventilator WOB decreased at the same rate as Pmus increased but plateaued at Pmus=10 cm H2O by delivering a minimum inspiratory pressure level of 6 cm H2O; (3) ventilator WOB decreased as in patterns 1 and 2 to Pmus=10 cm H2O, but then decreased at a much slower rate. Adaptive-pressure-control algorithms differ between ventilators in their response to increasing patient effort. Notably, some ventilators allow the patient to assume all of the WOB, and some provide a minimum level of WOB regardless of patient effort.
Tip tilt corection for astronomical telescopes using adaptive control
Energy Technology Data Exchange (ETDEWEB)
Watson, J.
1997-04-17
The greatest hindrance to modern astronomy is the effect of the Earth`s atmosphere on incoming light. The fundamental, or lowest mode of disturbance is tip and tilt.. This mode causes the focused image of a distant point source to move about in a plane (X-Y motion) as viewed form a telescope objective. Tip-tilt correction systems can be used to correct for these disturbances in real time. We propose a novel application of adaptive control to address some unique problems inherent with tip-tilt correction systems for astronomical telescopes.
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......) 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...
Direct model reference adaptive control with application to flexible robots
Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory W.
1992-01-01
A modification to a direct command generator tracker-based model reference adaptive control (MRAC) system is suggested in this paper. This modification incorporates a feedforward into the reference model's output as well as the plant's output. Its purpose is to eliminate the bounded model following error present in steady state when previous MRAC systems were used. The algorithm was evaluated using the dynamics for a single-link flexible-joint arm. The results of these simulations show a response with zero steady state model following error. These results encourage further use of MRAC for various types of nonlinear plants.
METİN, Muzaffer; GÜÇLÜ, Rahmi
2014-01-01
In this study, a conventional PID type fuzzy controller and parameter adaptive fuzzy controller are designed to control vibrations actively of a light rail transport vehicle which modeled as 6 degree-of-freedom system and compared performances of these two controllers. Rail vehicle model consists of a passenger seat and its suspension system, vehicle body, bogie, primary and secondary suspensions and wheels. The similarity between mathematical model and real system is shown by compar...
Adaptive Cruise Control for a SMART Car : A Comparison Benchmark for MPC-PWA Control Methods
Corona, D.; De Schutter, B.
2008-01-01
The design of an adaptive cruise controller for a SMART car, a type of small car, is proposed as a benchmark setup for several model predictive control methods for nonlinear and piecewise affine systems. Each of these methods has been already applied to specific case studies, different from method
A model predictive control approach to design a parameterized adaptive cruise control
Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Heemels, W.P.M.H.; Steinbuch, M.
2010-01-01
The combination of different desirable characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming and tedious. This chapter presents a systematic approach for the design and tuning of an ACC, based on model predictive control
Analysis of the Controllers for the Transitional Manoeuvres of Adaptive Cruise Control Systems
Directory of Open Access Journals (Sweden)
Dur Muhammad Pathan
2012-07-01
Full Text Available PID (Proportional-Integral-Derivative and MPC (Model Predictive Control algorithms are used to synthesize the upper-level controller of a vehicle equipped with an ACC (Adaptive Cruise Control system. Both controllers are analysed, with and without constraints, using a simple vehicle model under critical TM (Transitional Manoeuvres. A comparative analysis of both controllers’ results has been conducted. The comparison gives the suitability of MPC for ACC application over PID controller. The flaws of PID control approach for the given application are highlighted. This approach can be helpful for selecting the suitable controller for the given application
Kim, Nakwan
Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.
Directory of Open Access Journals (Sweden)
Baghdad BELABES
2008-12-01
Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.
Directory of Open Access Journals (Sweden)
Megan A Cummins
2014-03-01
Full Text Available Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP. The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz and fast (2 Hz rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of
Adaptive plasticity in vestibular influences on cardiovascular control
Yates, B. J.; Holmes, M. J.; Jian, B. J.
2000-01-01
Data collected in both human subjects and animal models indicate that the vestibular system influences the control of blood pressure. In animals, peripheral vestibular lesions diminish the capacity to rapidly and accurately make cardiovascular adjustments to changes in posture. Thus, one role of vestibulo-cardiovascular influences is to elicit changes in blood distribution in the body so that stable blood pressure is maintained during movement. However, deficits in correcting blood pressure following vestibular lesions diminish over time, and are less severe when non-labyrinthine sensory cues regarding body position in space are provided. These observations show that pathways that mediate vestibulo-sympathetic reflexes can be subject to plastic changes. This review considers the adaptive plasticity in cardiovascular responses elicited by the central vestibular system. Recent data indicate that the posterior cerebellar vermis may play an important role in adaptation of these responses, such that ablation of the posterior vermis impairs recovery of orthostatic tolerance following subsequent vestibular lesions. Furthermore, recent experiments suggest that non-labyrinthine inputs to the central vestibular system may be important in controlling blood pressure during movement, particularly following vestibular dysfunction. A number of sensory inputs appear to be integrated to produce cardiovascular adjustments during changes in posture. Although loss of any one of these inputs does not induce lability in blood pressure, it is likely that maximal blood pressure stability is achieved by the integration of a variety of sensory cues signaling body position in space.
Kalman filtering to suppress spurious signals in Adaptive Optics control
Energy Technology Data Exchange (ETDEWEB)
Poyneer, L; Veran, J P
2010-03-29
In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.
Distributed Adaptive Droop Control for DC Distribution Systems
DEFF Research Database (Denmark)
Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank
2014-01-01
A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc Microgrids. The conventional secondary control, that adjusts the voltage set point for the local droop mechanism, is replaced by a voltage regulator. A current regulator is then added to fine-tune the droop...... coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors’ data to estimate the average voltage across the Microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point. The current regulator compares...... the local perunit current of each converter with the neighbors’ on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load sharing. The proposed...
Distributed adaptive droop control for DC distribution systems
DEFF Research Database (Denmark)
Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank
2016-01-01
Summary form only given: A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc microgrids. The conventional secondary control that adjusts the voltage set point for the local droop mechanism is replaced by a voltage regulator. A current regulator is also added...... to fine-tune the droop coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors' data to estimate the average voltage across the microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point....... The current regulator compares the local per-unit current of each converter with the neighbors' on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load...
Robust adaptive cruise control of high speed trains.
Faieghi, Mohammadreza; Jalali, Aliakbar; Mashhadi, Seyed Kamal-e-ddin Mousavi
2014-03-01
The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive bridge control strategy for opinion evolution on social networks.
Qian, Cheng; Cao, Jinde; Lu, Jianquan; Kurths, Jürgen
2011-06-01
In this paper, we present an efficient opinion control strategy for complex networks, in particular, for social networks. The proposed adaptive bridge control (ABC) strategy calls for controlling a special kind of nodes named bridge and requires no knowledge of the node degrees or any other global or local knowledge, which are necessary for some other immunization strategies including targeted immunization and acquaintance immunization. We study the efficiency of the proposed ABC strategy on random networks, small-world networks, scale-free networks, and the random networks adjusted by the edge exchanging method. Our results show that the proposed ABC strategy is efficient for all of these four kinds of networks. Through an adjusting clustering coefficient by the edge exchanging method, it is found out that the efficiency of our ABC strategy is closely related with the clustering coefficient. The main contributions of this paper can be listed as follows: (1) A new high-order social network is proposed to describe opinion dynamic. (2) An algorithm, which does not require the knowledge of the nodes' degree and other global∕local network structure information, is proposed to control the "bridges" more accurately and further control the opinion dynamics of the social networks. The efficiency of our ABC strategy is illustrated by numerical examples. (3) The numerical results indicate that our ABC strategy is more efficient for networks with higher clustering coefficient.
Safety problems in vehicles with adaptive cruise control system
Directory of Open Access Journals (Sweden)
Yadav Arun K.
2017-06-01
Full Text Available In today’s world automotive industries are still putting efforts towards more autonomous vehicles (AVs. The main concern of introducing the autonomous technology is safety of driver. According to a survey 90% of accidents happen due to mistake of driver. The adaptive cruise control system (ACC is a system which combines cruise control with a collision avoidance system. The ACC system is based on laser and radar technologies. This system is capable of controlling the velocity of vehicle automatically to match the velocity of car, bus or truck in front of vehicle. If the lead vehicle gets slow down or accelerate, than ACC system automatically matches that velocity. The proposed paper is focusing on more accurate methods of detecting the preceding vehicle by using a radar and lidar sensors by considering the vehicle side slip and by controlling the distance between two vehicles. By using this approach i.e. logic for calculation of former vehicle distance and controlling the throttle valve of ACC equipped vehicle, an improvement in driving stability was achieved. The own contribution results with fuel efficient driving and with more safer and reliable driving system, but still some improvements are going on to make it more safe and reliable.
Adaptive fuzzy PID control of hydraulic servo control system for large axial flow compressor
Wang, Yannian; Wu, Peizhi; Liu, Chengtao
2017-09-01
To improve the stability of the large axial compressor, an efficient and special intelligent hydraulic servo control system is designed and implemented. The adaptive fuzzy PID control algorithm is used to control the position of the hydraulic servo cylinder steadily, which overcomes the drawback that the PID parameters should be adjusted based on the different applications. The simulation and the test results show that the system has a better dynamic property and a stable state performance.
Design of an adaptive controller for dive-plane control of a torpedo-shaped AUV
Cao, Jian; Su, Yumin; Zhao, Jinxin
2011-09-01
Underwater vehicles operating in complex ocean conditions present difficulties in determining accurate dynamic models. To guarantee robustness against parameter uncertainty, an adaptive controller for dive-plane control, based on Lyapunov theory and back-stepping techniques, was proposed. In the closed-loop system, asymptotic tracking of the reference depth and pitch angle trajectories was accomplished. Simulation results were presented which show effective dive-plane control in spite of the uncertainties in the system parameters.
Directory of Open Access Journals (Sweden)
Sayed Hamed Hosseini
2017-06-01
Full Text Available This paper presents a two-loop approach for velocity and stator currents control of an Interior-type Permanent Magnet Synchronous Motor (IPMSM. In the outer loop, the reference torque obtained from a conventional PI controller gives two-axis stator reference currents based on Maximum-Torque per Ampere (MTPA strategy. In the inner loop, an adaptive fractional order sliding mode controller is designed to reach the two-axis stator currents to their reference values obtained from the MTPA method. To achieve this idea, fractional order sliding surfaces and an adaptive controller with adjustable parameters are employed. The adaptive controller is designed to increase the robustness of the proposed method against the uncertainties in stator resistance and inductances. A Lyapunov based adaptation mechanism is proposed for adjustment of the controller parameters. The optimal value of the fractional orders are obtained by optimization of an integral time absolute error performance index. The simulation results show the robustness of the proposed method against the uncertainties in stator resistance and stator inductances.
Decentralized adaptive sliding mode control of a space robot actuated by control moment gyroscopes
Directory of Open Access Journals (Sweden)
Jia Yinghong
2016-06-01
Full Text Available An adaptive sliding mode control (ASMC law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot. Each joint of the system is a free ball joint capable of rotating with three degrees of freedom (DOF. A cluster of control moment gyroscopes (CMGs is mounted on each link and the base to actuate the system. The modified Rodrigues parameters (MRPs are employed to describe the angular displacements, and the equations of motion are derived using Kane’s equations. The controller for each link or the base is designed separately in decentralized scheme. The unknown disturbances, inertia parameter uncertainties and nonlinear uncertainties are classified as a “lumped” matched uncertainty with unknown upper bound, and a continuous sliding mode control (SMC law is proposed, in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty. A general amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input. Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov’s method. Simulation results based on a three-link system verify the effectiveness of the proposed controller.
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows.
Directory of Open Access Journals (Sweden)
Carsten Kirkeby
Full Text Available Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows.
Kirkeby, Carsten; Græsbøll, Kaare; Nielsen, Søren Saxmose; Christiansen, Lasse Engbo; Toft, Nils; Halasa, Tariq
2016-01-01
Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP) in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.
A robust adaptive load frequency control for micro-grids.
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.
Composite learning from adaptive backstepping neural network control.
Pan, Yongping; Sun, Tairen; Liu, Yiqi; Yu, Haoyong
2017-11-01
In existing neural network (NN) learning control methods, the trajectory of NN inputs must be recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN parameter convergence is obtainable. This paper focuses on command-filtered backstepping adaptive control for a class of strict-feedback nonlinear systems with functional uncertainties, where an NN composite learning technique is proposed to guarantee convergence of NN weights to their ideal values without the PE condition. In the NN composite learning, spatially localized NN approximation is employed to handle functional uncertainties, online historical data together with instantaneous data are exploited to generate prediction errors, and both tracking errors and prediction errors are employed to update NN weights. The influence of NN approximation errors on the control performance is also clearly shown. The distinctive feature of the proposed NN composite learning is that NN parameter convergence is guaranteed without the requirement of the trajectory of NN inputs being recurrent. Illustrative results have verified effectiveness and superiority of the proposed method compared with existing NN learning control methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bitrate adaptation flow control and client-based congestion control for multimedia-on-demand
Chan, Siu-Ping; Kok, Chi-Wah
2003-06-01
A flow control for streaming multimedia data over UDP on IP network is presented. The bitrate adaptation algorithm embedded in the protocol is considered to be an end-to-end mechanism in the application level. The flow control system constantly maintains the streaming buffer at a prescribed capacity even with bursty network losses by adapting the multimedia bitrate B from the streaming codec. A congestion control algorithm which is considered to be located in a lower level than that of the flow control mechanism is presented. It works together with the presented flow control to resolve network congestion problems while maintaining a degree of TCP-friendliness by changing the sending rate R at the server. Simulation results obtained from NS2 have shown better resource allocation can be obtained, and an overall incrase in the average sending rate and hence better quality of streaming media is observed.
Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.
Gordon, Keith E; Kinnaird, Catherine R; Ferris, Daniel P
2013-04-01
Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to "fight" the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations.
Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.
2016-10-01
This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.
A Density Control Based Adaptive Hexahedral Mesh Generation Algorithm
Directory of Open Access Journals (Sweden)
Xiangwei Zhang
2016-12-01
Full Text Available A density control based adaptive hexahedral mesh generation algorithm for three dimensional models is presented in this paper. The first step of this algorithm is to identify the characteristic boundary of the solid model which needs to be meshed. Secondly, the refinement fields are constructed and modified according to the conformal refinement templates, and used as a metric to generate an initial grid structure. Thirdly, a jagged core mesh is generated by removing all the elements in the exterior of the solid model. Fourthly, all of the surface nodes of the jagged core mesh are matching to the surfaces of the model through a node projection process. Finally, the mesh quality such as topology and shape is improved by using corresponding optimization techniques.
Thermotropic and Thermochromic Polymer Based Materials for Adaptive Solar Control
Directory of Open Access Journals (Sweden)
Olaf Mühling
2010-12-01
Full Text Available The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from ordinary shadow systems to intrinsic solar energy reflection materials based on phase transition components and a first remark about their realization is reported. Own current results concerning extruded films and high thermally stable casting resins with thermotropic properties make a significant contribution to this field.
Adaptive postural control for joint immobilization during multitask performance.
Hsu, Wei-Li
2014-01-01
Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21-29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements.
Adaptive postural control for joint immobilization during multitask performance.
Directory of Open Access Journals (Sweden)
Wei-Li Hsu
Full Text Available Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21-29 yr without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM stability were examined using uncontrolled manifold (UCM analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM; the second leads to COM position variability (VORT. The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements.
Considering Variable Road Geometry in Adaptive Vehicle Speed Control
Directory of Open Access Journals (Sweden)
Xinping Yan
2013-01-01
Full Text Available Adaptive vehicle speed control is critical for developing Advanced Driver Assistance Systems (ADAS. Vehicle speed control considering variable road geometry has become a hotspot in ADAS research. In this paper, first, an exploration of intrinsic relationship between vehicle operation and road geometry is made. Secondly, a collaborative vehicle coupling model, a road geometry model, and an AVSC, which can respond to variable road geometry in advance, are developed. Then, based on H∞ control method and the minimum energy principle, a performance index is specified by a cost function for the proposed AVSC, which can explicitly consider variable road geometry in its optimization process. The proposed AVSC is designed by the Hamilton-Jacobi Inequality (HJI. Finally, simulations are carried out by combining the vehicle model with the road geometry model, in an aim of minimizing the performance index of the AVSC. Analyses of the simulation results indicate that the proposed AVSC can automatically and effectively regulate speed according to variable road geometry. It is believed that the proposed AVSC can be used to improve the economy, comfort, and safety effects of current ADAS.
Design of Attitude Control System for UAV Based on Feedback Linearization and Adaptive Control
Directory of Open Access Journals (Sweden)
Wenya Zhou
2014-01-01
Full Text Available Attitude dynamic model of unmanned aerial vehicles (UAVs is multi-input multioutput (MIMO, strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range, and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.
Improving Accuracy of Processing by Adaptive Control Techniques
Directory of Open Access Journals (Sweden)
N. N. Barbashov
2016-01-01
Full Text Available When machining the work-pieces a range of scatter of the work-piece dimensions to the tolerance limit is displaced in response to the errors. To improve an accuracy of machining and prevent products from defects it is necessary to diminish the machining error components, i.e. to improve the accuracy of machine tool, tool life, rigidity of the system, accuracy of adjustment. It is also necessary to provide on-machine adjustment after a certain time. However, increasing number of readjustments reduces the performance and high machine and tool requirements lead to a significant increase in the machining cost.To improve the accuracy and machining rate, various devices of active control (in-process gaging devices, as well as controlled machining through adaptive systems for a technological process control now become widely used. Thus, the accuracy improvement in this case is reached by compensation of a majority of technological errors. The sensors of active control can provide improving the accuracy of processing by one or two quality classes, and simultaneous operation of several machines.For efficient use of sensors of active control it is necessary to develop the accuracy control methods by means of introducing the appropriate adjustments to solve this problem. Methods based on the moving average, appear to be the most promising for accuracy control, since they contain information on the change in the last several measured values of the parameter under control.When using the proposed method in calculation, the first three members of the sequence of deviations remain unchanged, therefore 1 1 x x , 2 2 x x , 3 3 x x Then, for each i-th member of the sequence we calculate that way: , ' i i i x x k x , where instead of the i x values will be populated with the corresponding values ' i x calculated as an average of three previous members:3 ' 1 2 3 i i i i x x x x .As a criterion for the estimate of the control
Directory of Open Access Journals (Sweden)
Bangcheng Han
2013-01-01
Full Text Available The double-gimbal control moment gyro (DGCMG demands that the gimbal servosystem should have fast response and small overshoot. But due to the low and nonlinear torsional stiffness of harmonic drive, the gimbal servo-system has poor dynamic performance with large overshoot and low bandwidth. In order to improve the dynamic performance of gimbal servo-system, a model reference adaptive control (MRAC law is introduced in this paper. The model of DGCMG gimbal servo-system with harmonic drive is established, and the adaptive control law based on POPOV super stable theory is designed. The MATLAB simulation results are provided to verify the effectiveness of the proposed control algorithm. The experimental results indicate that the MRAC could increase the bandwidth of gimbal servo-system to 3 Hz and improve the dynamic performance with small overshoot.
DEFF Research Database (Denmark)
Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej
1998-01-01
Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....
Analytical and experimental study of control effort associated with model reference adaptive control
Messer, R. S.; Haftka, R. T.; Cudney, H. H.
1992-01-01
Numerical simulation results presently obtained for the performance of model reference adaptive control (MRAC) are experimentally verified, with a view to accounting for differences between the plant and the reference model after the control function has been brought to bear. MRAC is both experimentally and analytically applied to a single-degree-of-freedom system, as well as analytically to a MIMO system having controlled differences between the reference model and the plant. The control effort is noted to be sensitive to differences between the plant and the reference model.
Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan
2017-01-01
This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.
Directory of Open Access Journals (Sweden)
Zhi-Lin Zeng
2014-01-01
Full Text Available This paper focuses on high precision leveling control of an underwater heavy load platform, which is viewed as an underwater parallel robot on the basis of its work pattern. The kinematic of platform with deformation is analyzed and the dynamics model of joint space is established. An adaptive backstepping controller according to Lyapunov's function is proposed for leveling control of platform based on joint space. Furthermore, the “lowest point fixed angle error” leveling scheme called “chase” is chosen for leveling control of platform. The digital simulation and practical experiment of single joint space actuator are carried out, and the results show high precision servo control of joint space. On the basis of this, the platform leveling control simulation relies on the hardware-in-loop system. The results indicate that the proposed controller can effectively restrain the influence from system parameter uncertainties and external disturbance to realize high precision leveling control of the underwater platform.
An Adaptable Power System with Software Control Algorithm
Castell, Karen; Bay, Mike; Hernandez-Pellerano, Amri; Ha, Kong
1998-01-01
A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system
Adaptive robotic control driven by a versatile spiking cerebellar network.
Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio
2014-01-01
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.
Nutrient-dependent/pheromone-controlled adaptive evolution: a model
Directory of Open Access Journals (Sweden)
James Vaughn Kohl
2013-06-01
Full Text Available Background: The prenatal migration of gonadotropin-releasing hormone (GnRH neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors. Methods: This model details how chemical ecology drives adaptive evolution via: (1 ecological niche construction, (2 social niche construction, (3 neurogenic niche construction, and (4 socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH and systems biology. Results: Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man. Conclusion: An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively
Adaptive robotic control driven by a versatile spiking cerebellar network.
Directory of Open Access Journals (Sweden)
Claudia Casellato
Full Text Available The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning, a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.
Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis
Rohrs, C. E.
1982-01-01
Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.
Adaptive control of an active seat for occupant vibration reduction
Gan, Zengkang; Hillis, Andrew J.; Darling, Jocelyn
2015-08-01
The harmful effects on human performance and health caused by unwanted vibration from vehicle seats are of increasing concern. This paper presents an active seat system to reduce the vibration level transmitted to the seat pan and the occupants' body under low frequency periodic excitation. Firstly, the detail of the mechanical structure is given and the active seat dynamics without external load are characterized by vibration transmissibility and frequency responses under different excitation forces. Owing the nonlinear and time-varying behaviour of the proposed system, a Filtered-x least-mean-square (FXLMS) adaptive control algorithm with on-line Fast-block LMS (FBLMS) identification process is employed to manage the system operation for high vibration cancellation performance. The effectiveness of the active seat system is assessed through real-time experimental tests using different excitation profiles. The system identification results show that an accurate estimation of the secondary path is achieved by using the FBLMS on-line technique. Substantial reduction is found for cancelling periodic vibration containing single and multiple frequencies. Additionally, the robustness and stability of the control system are validated through transient switching frequency tests.
Information-educational environment with adaptive control of learning process
Modjaev, A. D.; Leonova, N. M.
2017-01-01
Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.
Marcel Heerink
2011-01-01
Older adults prefer an assistive technology that can be adaptive to their needs. However, as an assistive social robot that is autonomous has the possibility of being pro-actively adaptive this could cause feelings of anxiety. Analyzing the results of a study with video’s that feature an assistive
Adaptive model-based control systems and methods for controlling a gas turbine
Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)
2004-01-01
Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).
Line-frequency phase-controlled rectifiers with adaptive digital controllers
Directory of Open Access Journals (Sweden)
Vukić Vladimir Đ.
2013-01-01
Full Text Available This article deals with the influence of PI controller linear gain scheduling on the dynamic characteristics of the line-frequency phase-controlled rectifier. The examined device has digital control electronics of the DRI 07B type, based on the Intel 80C196 microcontroller. The realized adaptive PI controllers utilize wide variations of the current gain (Kp, decreasing linearly in proportion to the increase in the rectifier output current in the area of the discontinuous currents. Reaching the threshold of the rectifier's discontinuous current, the current gain of the PI voltage controller remains constant. Beside the improvement of the thyristor rectifier's static stability during operation with small output currents, implementation of the adaptive PI control also led to improvement of the voltage controller response in the case of load disturbance in the range of 13-90 % of the nominal rectifier output current. Transfer functions were analyzed for specific parts of the phase-controlled rectifier DRI 110-100 having nominal output parameters of 116 V and 100 A. The values of the relative damping and root-locus characteristics were analyzed in detail.
VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.
2014-01-01
Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a
Ye, Linqi; Zong, Qun; Tian, Bailing; Zhang, Xiuyun; Wang, Fang
2017-09-01
In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Dongelmans, Dave A.; Veelo, Denise P.; Paulus, Frederique; de Mol, Bas A. J. M.; Korevaar, Johanna C.; Kudoga, Anna; Middelhoek, Pauline; Binnekade, Jan M.; Schultz, Marcus J.
2009-01-01
Background: Adaptive support ventilation (ASV) is a microprocessor-controlled mode of mechanical ventilation that switches automatically from controlled ventilation to assisted ventilation and selects ventilatory settings according to measured lung mechanics. Methods: In a randomized controlled
Directory of Open Access Journals (Sweden)
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang
2010-09-01
This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.
On the necessity of identifying the true parameter in adaptive LQ control
Polderman, Jan W.
1986-01-01
In adaptive control problems one may drop the requirement of identifying the true system in order to simplify the problem of control. It will be shown that in the adaptive LQ control problem this does not at all lead to an easier problem.
Adaptive tracking control of fully actuated port-Hamiltonian mechanical systems
Dirksz, D.A.; Scherpen, J.M.A.
2010-01-01
In the presence of parameter uncertainty tracking control can result in significant tracking errors. To overcome this problem adaptive control is applied, which estimates and compensates for the errors of the uncertain parameters. A new adaptive tracking control scheme is presented for standard
Control uncertain Genesio-Tesi chaotic system: Adaptive sliding mode approach
Energy Technology Data Exchange (ETDEWEB)
Dadras, Sara [Automation and Instruments Lab, Electrical Engineering Department, Tarbiat Modares University, P.O. Box 14115-143, Tehran (Iran, Islamic Republic of)], E-mail: s_dadras@modares.ac.ir; Momeni, Hamid Reza [Automation and Instruments Lab, Electrical Engineering Department, Tarbiat Modares University, P.O. Box 14115-143, Tehran (Iran, Islamic Republic of)], E-mail: momeni_h@modares.ac.ir
2009-12-15
An adaptive sliding mode control (ASMC) technique is introduced in this paper for a chaotic dynamical system (Genesio-Tesi system). Using the sliding mode control technique, a sliding surface is determined and the control law is established. An adaptive sliding mode control law is derived to make the states of the Genesio-Tesi system asymptotically track and regulate the desired state. The designed control scheme can control the uncertain chaotic behaviors to a desired state without oscillating very fast and guarantee the property of asymptotical stability. An illustrative simulation result is given to demonstrate the effectiveness of the proposed adaptive sliding mode control design.
Directory of Open Access Journals (Sweden)
Tat-Bao-Thien Nguyen
2014-01-01
Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.
Circadian modulation of QT rate dependence in healthy volunteers: gender and age differences.
Extramiana, F; Maison-Blanche, P; Badilini, F; Pinoteau, J; Deseo, T; Coumel, P
1999-01-01
QT rate dependence is known to be linked with both circadian variations of the autonomic tone and gender. However, age and heart rate variability (HRV) influences are not well established. The QT/RR relationship was evaluated, separately during the day and at night, on 24-hour electrocardiogram in 60 healthy subjects (30 men) divided into three homogeneous groups (group 1, 20-29; group 2 30-39; group 3, 40-50 years). QT rate dependence was larger during the day in both genders. Women showed stronger QT rate dependence (0.195 during the day vs. 0.154 in men P< .0001). The circadian modulation decreased with increasing age (day/night slope differences: group 1, 0.038; group 2, 0.031; group 3, 0.001; analysis of variance P<.05). In addition, QT rate dependence increased as mean RR decreased (r = -0.58, P<.0001) and decreased as HRV parameters increased. Multiple influences on QT rate dependence can be found: not only circadian and gender modulation, but also age, heart rate, and HRV interventions.
Accounting for rate-dependent category boundary shifts in speech perception.
Bosker, Hans Rutger
2017-01-01
The perception of temporal contrasts in speech is known to be influenced by the speech rate in the surrounding context. This rate-dependent perception is suggested to involve general auditory processes because it is also elicited by nonspeech contexts, such as pure tone sequences. Two general auditory mechanisms have been proposed to underlie rate-dependent perception: durational contrast and neural entrainment. This study compares the predictions of these two accounts of rate-dependent speech perception by means of four experiments, in which participants heard tone sequences followed by Dutch target words ambiguous between /ɑs/ "ash" and /a:s/ "bait". Tone sequences varied in the duration of tones (short vs. long) and in the presentation rate of the tones (fast vs. slow). Results show that the duration of preceding tones did not influence target perception in any of the experiments, thus challenging durational contrast as explanatory mechanism behind rate-dependent perception. Instead, the presentation rate consistently elicited a category boundary shift, with faster presentation rates inducing more /a:s/ responses, but only if the tone sequence was isochronous. Therefore, this study proposes an alternative, neurobiologically plausible account of rate-dependent perception involving neural entrainment of endogenous oscillations to the rate of a rhythmic stimulus.
Adaptive formation control of quadrotor unmanned aerial vehicles with bounded control thrust
Directory of Open Access Journals (Sweden)
Rui Wang
2017-04-01
Full Text Available In this paper, the flight formation control problem of a group of quadrotor unmanned aerial vehicles (UAVs with parametric uncertainties and external disturbances is studied. Unit-quaternions are used to represent the attitudes of the quadrotor UAVs. Separating the model into a translational subsystem and a rotational subsystem, an intermediary control input is introduced to track a desired velocity and extract desired orientations. Then considering the internal parametric uncertainties and external disturbances of the quadrotor UAVs, the priori-bounded intermediary adaptive control input is designed for velocity tracking and formation keeping, by which the bounded control thrust and the desired orientation can be extracted. Thereafter, an adaptive control torque input is designed for the rotational subsystem to track the desired orientation. With the proposed control scheme, the desired velocity is tracked and a desired formation shape is built up. Global stability of the closed-loop system is proven via Lyapunov-based stability analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed control scheme.
Control code for laboratory adaptive optics teaching system
Jin, Moonseob; Luder, Ryan; Sanchez, Lucas; Hart, Michael
2017-09-01
By sensing and compensating wavefront aberration, adaptive optics (AO) systems have proven themselves crucial in large astronomical telescopes, retinal imaging, and holographic coherent imaging. Commercial AO systems for laboratory use are now available in the market. One such is the ThorLabs AO kit built around a Boston Micromachines deformable mirror. However, there are limitations in applying these systems to research and pedagogical projects since the software is written with limited flexibility. In this paper, we describe a MATLAB-based software suite to interface with the ThorLabs AO kit by using the MATLAB Engine API and Visual Studio. The software is designed to offer complete access to the wavefront sensor data, through the various levels of processing, to the command signals to the deformable mirror and fast steering mirror. In this way, through a MATLAB GUI, an operator can experiment with every aspect of the AO system's functioning. This is particularly valuable for tests of new control algorithms as well as to support student engagement in an academic environment. We plan to make the code freely available to the community.
Adaptive Feed-Forward Control of Low Frequency Interior Noise
Kletschkowski, Thomas
2012-01-01
This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.
Simulation of random events for adaptive control systems calibration
Directory of Open Access Journals (Sweden)
Drăgoi Mircea Viorel
2017-01-01
Full Text Available The paper deals with a mathematical model that simulates the random occurrence of events during cutting processes by milling. The evolution of certain parameters that typify the cutting processes depends on predictable and non-predictable variables. In this context, either the material hardness that varies in different sides of billet, or cutting depth, can act as non-predictable variables. In order to design a response in terms of cutting parameters to non-predictable variations of inputs, a simulation of such phenomena is very useful. A mathematical model that generates random events, both in terms of non-uniform frequency and intensity is here described. A virtual instrument built in LabVIEW generates (pseudo random events based on a combination of random numbers, as the evolution of the simulated process to be much like a real one. Furthermore the user of virtual instrument can generate himself events at certain moments and of certain intensity. This can be a useful tool to study the algorithms of designing the response which should re-balance the process within adaptive control systems.
Effect of adaptive cruise control systems on traffic flow
Davis, L. C.
2004-06-01
The flow of traffic composed of vehicles that are equipped with adaptive cruise control (ACC) is studied using simulations. The ACC vehicles are modeled by a linear dynamical equation that has string stability. In platoons of all ACC vehicles, perturbations due to changes in the lead vehicle’s velocity do not cause jams. Simulations of merging flows near an onramp show that if the total incoming rate does not exceed the capacity of the single outgoing lane, free flow is maintained. With larger incoming flows, a state closely related to the synchronized flow phase found in manually driven vehicular traffic has been observed. This state, however, should not be considered congested because the flow is maximal for the density. Traffic composed of random sequences of ACC vehicles and manual vehicles has also been studied. At high speeds ( ˜30 m/s ) jamming occurs for concentrations of ACC vehicles of 10% or less. At 20% no jams are formed. The formation of jams is sensitive to the sequence of vehicles (ACC or manual). At lower speeds ( ˜15 m/s ) , no critical concentration for complete jam suppression is found. Rather, the average velocity in the pseudojam region increases with increasing ACC concentration. Mixing 50% ACC vehicles randomly with manually driven vehicles on the primary lane in onramp simulations shows only modestly reduced travel times and larger flow rates.
Function-valued adaptive dynamics and optimal control theory.
Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf
2013-09-01
In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.
Use patterns among early adopters of adaptive cruise control.
Xiong, Huimin; Boyle, Linda Ng; Moeckli, Jane; Dow, Benjamin R; Brown, Timothy L
2012-10-01
The objective of this study was to investigate use patterns among early adopters of adaptive cruise control (ACC). Extended use ofACC may influence a driver's behavior in the long-term, which can have unintended safety consequences. The authors examined the use of a motion-based simulator by 24 participants (15 males and 9 females). Cluster analysis was performed on drivers' use of ACC and was based on their gap settings, speed settings, number of warnings issued, and ACC disengaged. The data were then examined on the basis of driving performance measures and drivers' subjective responses to trust in ACC, understanding of system operations, and driving styles. Driving performance measures included minimum time headway, adjusted minimum time to collision, and drivers' reaction time to critical events. Three groups of drivers were observed on the basis of risky behavior, moderately risky behavior, and conservative behavior. Drivers in the conservative group stayed farther behind the lead vehicle than did drivers in the other two groups. Risky drivers responded later to critical events and had more ACC warnings issued. Safety consequences with ACC may be more prevalent in some driver groups than others. The findings suggest that these safety implications are related to trust in automation, driving styles, understanding of system operations, and personalities. Potential applications of this research include enhanced design for next-generation ACC systems and countermeasures to improve safe driving with ACC.
National Research Council Canada - National Science Library
Deshpande, Sunil; Rivera, Daniel E; Younger, Jarred W; Nandola, Naresh N
2014-01-01
.... Control systems engineering offers an attractive means for designing and implementing adaptive behavioral interventions that feature intensive measurement and frequent decision-making over time...
Randomised controlled trial adapting US school obesity prevention to England.
Kipping, R R; Payne, C; Lawlor, D A
2008-06-01
To determine whether a school obesity prevention project developed in the United States can be adapted for use in England. A pilot cluster randomised controlled trial and interviews with teachers were carried out in 19 primary schools in South West England. Participants included 679 children in year 5 (age 9-10). Baseline and follow-up assessments were completed for 323 children (screen viewing) and 472 children (body mass index). Sixteen lessons on healthy eating, physical activity and reducing TV viewing were taught over 5 months by teachers. Main outcome measures were hours of screen activities, body mass index, mode of transport to school and teachers' views of the intervention. Children from intervention schools spent less time on screen-viewing activities after the intervention but these differences were imprecisely estimated: mean difference in minutes spent on screen viewing at the end of the intervention (intervention schools minus control schools) adjusted for baseline levels and clustering within schools was -11.6 (95% CI -42.7 to 19.4) for a week day and was -15.4 (95% CI -57.5 to 26.8) for a Saturday. There was no difference in mean body mass index or the odds of obesity. It is feasible to transfer this US school-based intervention to UK schools, and it may be effective in reducing the time children spend on screen-based activities. The study has provided information for a full-scale trial, which would require 50 schools ( approximately 1250 pupils) to detect effects on screen viewing and body mass index over 2 years of follow-up.
The ADAPT design model : towards instructional control of transfer
Jelsma, Otto; van Merrienboer, Jeroen J.G.; van Merrienboer, J.J.G.; Bijlstra, Jim P.; Bijlstra, J.P.
1990-01-01
This paper presents a detailed description of the ADAPT (Apply Delayed Automatization for Positive Transfer) design model. ADAPT is based upon production system models of learning and provides guidelines for developing instructional systems that offer transfer of leamed skills. The model suggests
Adaptive observer for speed sensorless PM motor control
DEFF Research Database (Denmark)
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
2003-01-01
This paper presents an adaptive observer for extimating the rotor position and speed of a permanent magnet synchronous motors (PMSM). The observer compensates for voltage offsets and permanent magnet strength variations. The adaptation structure for estimating the strength of the permanent magnet...
Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang
2015-03-25
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes--the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC--were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Directory of Open Access Journals (Sweden)
Shun-Yuan Wang
2015-03-01
Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Wen, John T.; Kreutz, Kenneth; Bayard, David S.
1988-01-01
A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.
Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control
Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten
2011-01-01
When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526
Thibbotuwawa, Namal; Oloyede, Adekunle; Li, Tong; Singh, Sanjleena; Senadeera, Wijitha; Gu, YuanTong
2015-09-01
Due to anatomical and biomechanical similarities to human shoulder, kangaroo was chosen as a model to study shoulder cartilage. Comprehensive enzymatic degradation and indentation tests were applied on kangaroo shoulder cartilage to study mechanisms underlying its strain-rate-dependent mechanical behavior. We report that superficial collagen plays a more significant role than proteoglycans in facilitating strain-rate-dependent behavior of the kangaroo shoulder cartilage. By comparing the mechanical properties of degraded and normal cartilages, it was noted that proteoglycan and collagen degradation significantly compromised strain-rate-dependent mechanical behavior of the cartilage. Superficial collagen contributed equally to the tissue behavior at all strain-rates. This is different to the studies reported on knee cartilage and confirms the importance of superficial collagen on shoulder cartilage mechanical behavior. A porohyperelastic numerical model also indicated that collagen disruption would lead to faster damage of the shoulder cartilage than when proteoglycans are depleted.
CHARADE: A characteristic code for calculating rate-dependent shock-wave response
Energy Technology Data Exchange (ETDEWEB)
Johnson, J.N.; Tonks, D.L.
1991-01-01
In this report we apply spatially one-dimensional methods and simple shock-tracking techniques to the solution of rate-dependent material response under flat-plate-impact conditions. This method of solution eliminates potential confusion of material dissipation with artificial dissipative effects inherent in finite-difference codes, and thus lends itself to accurate calculation of elastic-plastic deformation, shock-to-detonation transition in solid explosives, and shock-induced structural phase transformation. Equations are presented for rate-dependent thermoelastic-plastic deformation for (100) planar shock-wave propagation in materials of cubic symmetry (or higher). Specific numerical calculations are presented for polycrystalline copper using the mechanical threshold stress model of Follansbee and Kocks with transition to dislocation drag. A listing of the CHARADE (for characteristic rate dependence) code and sample input deck are given. 26 refs., 11 figs.
Optimal control based on adaptive model reduction approach to control transfer phenomena
Oulghelou, Mourad; Allery, Cyrille
2017-01-01
The purpose of optimal control is to act on a set of parameters characterizing a dynamical system to achieve a target dynamics. In order to reduce CPU time and memory storage needed to perform control on evolution systems, it is possible to use reduced order models (ROMs). The mostly used one is the Proper Orthogonal Decomposition (POD). However the bases constructed in this way are sensitive to the configuration of the dynamical system. Consequently, the need of full simulations to build a basis for each configuration is time consuming and makes that approach still relatively expensive. In this paper, to overcome this difficulty we suggest to use an adequate bases interpolation method. It consists in computing the associated bases to a distribution of control parameters. These bases are afterwards called in the control algorithm to build a reduced basis adapted to a given control parameter. This interpolation method involves results of the calculus of Geodesics on Grassmann manifold.
Adaptive Control for Nonlinear Systems with Time-Varying Control Gain
Directory of Open Access Journals (Sweden)
Alejandro Rincon
2012-01-01
Full Text Available We propose a scheme for nonlinear plants with time-varying control gain and time-varying plant coefficients, on the basis of a plant model consisting of a Brunovsky-type model with polynomials as approximators. We develop an adaptive robust control scheme for this plant, under the following assumptions: (i the plant terms involve time-varying but bounded coefficients, being its upper bound unknown; (ii the control gain is unknown, not necessarily bounded, and only its signum is known. To achieve robustness, we use a combination of robustifying control inputs and dead zone-type update laws. We apply this methodology to the speed control of a permanent magnet synchronous motor (PMSM, and we achieve proper tracking results.
Weyrauch, T; Vorontsov, M A; Bifano, T G; Hammer, J A; Cohen, M; Cauwenberghs, G
2001-08-20
The performance of adaptive systems that consist of microscale on-chip elements [microelectromechanical mirror (mu-mirror) arrays and a VLSI stochastic gradient descent microelectronic control system] is analyzed. The mu-mirror arrays with 5 x 5 and 6 x 6 actuators were driven with a control system composed of two mixed-mode VLSI chips implementing model-free beam-quality metric optimization by the stochastic parallel perturbative gradient descent technique. The adaptation rate achieved was near 6000 iterations/s. A secondary (learning) feedback loop was used to control system parameters during the adaptation process, further increasing the adaptation rate.
Strain-rate-dependent non-linear tensile properties of the superficial zone of articular cartilage.
Ahsanizadeh, Sahand; Li, LePing
2015-11-01
The tensile properties of articular cartilage play an important role in the compressive behavior and integrity of the tissue. The stress-strain relationship of cartilage in compression was observed previously to depend on the strain-rate. This strain-rate dependence has been thought to originate mainly from fluid pressurization. However, it was not clear to what extent the tensile properties of cartilage contribute to the strain-rate dependence in compressive behavior of cartilage. The aim of the present study was to quantify the strain-rate dependent stress-strain relationship and hysteresis of articular cartilage in tension. Uniaxial tensile tests were performed to examine the strain-rate dependent non-linear tensile properties of the superficial zone of bovine knee cartilage. Tensile specimens were oriented in the fiber direction indicated by the India ink method. Seven strain-rates were used in the measurement ranging from 0.1 to 80%/s, which corresponded to nearly static to impact joint loadings. The experimental data showed substantial strain-rate and strain-magnitude dependent load response: for a given strain-magnitude, the tensile stress could vary by a factor of 1.95 while the modulus by a factor of 1.58 with strain-rate; for a given strain-rate, the modulus at 15% strain could be over four times the initial modulus at no strain. The energy loss in cartilage tension upon unloading exhibited a complex variation with the strain-rate. The strain-rate dependence of cartilage in tension observed from the present study is relatively weaker than that in compression observed previously, but is considerable to contribute to the strain-rate dependent load response in compression.
Induction machine Direct Torque Control system based on fuzzy adaptive control
Li, Shi-ping; Yu, Yan; Jiao, Zhen-gang; Gu, Shu-sheng
2009-07-01
Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.
Rate dependency of depth in nanoindentation of polycrystalline NiTi
Directory of Open Access Journals (Sweden)
Sun Q.P.
2010-06-01
Full Text Available The recent increased use of shape memory alloys (SMAs for engineering applications manifests the need of checking the aspect of rate in NiTi. The ability of models and experiments to accurately predict the rate dependency of function–rate relationship is important. This paper concentrates on the rate dependency of depth in nanoindentation of NiTi where different tips have been used. To explain the phenomena, hysteresis damping areas are investigated. The results show decreasing depth at higher rates is due to the amount of latent heat generated from phase transition and relaxation time for heat release.
Adaptive Backstepping Control of Nonlinear Hydraulic-Mechanical System Including Valve Dynamics
Directory of Open Access Journals (Sweden)
M. Choux
2010-01-01
Full Text Available The main contribution of the paper is the development of an adaptive backstepping controller for a nonlinear hydraulic-mechanical system considering valve dynamics. The paper also compares the performance of two variants of an adaptive backstepping tracking controller with a simple PI controller. The results show that the backstepping controller considering valve dynamics achieves significantly better tracking performance than the PI controller, while handling uncertain parameters related to internal leakage, friction, the orifice equation and oil characteristics.
Integrated Backstepping Design of Missile Guidance andControl with Time delay Adaptive Scheme
2016-03-30
Guidance and Control with Time-delay Adaptive Scheme Seong-Min Hong 1 , Min-Guk Seo 1 , Chang-Hun Lee 2 and Min-Jea Tahk 1 1 Department...engagement kinematics are merged. Control input for the overall system is derived by backstepping approach. The stability of control logic is proved...estimated by using a time-delay adaptive control law. The performance of designed controller is investigated by numerical simulation. Keywords
Active Control of Nonlinear Suspension System Using Modified Adaptive Supertwisting Controller
Directory of Open Access Journals (Sweden)
Jagat J. Rath
2015-01-01
Full Text Available The suspension system is faced with nonlinearities from the spring, damper, and external excitations from the road surface. The objective of any control action provided to the suspension is to improve ride comfort while ensuring road holding for the vehicle. In this work, a robust higher order sliding mode algorithm combining the merits of the modified supertwisting algorithm and the adaptive supertwisting algorithm has been proposed for the nonlinear active suspension system. The proposed controller is robust to linearly growing perturbations and bounded uncertainties. Simulations have been performed for different classes of road excitations and the results are presented.
Directory of Open Access Journals (Sweden)
Poramate eManoonpong
2013-02-01
Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.
Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin
2013-01-01
Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.
In the mood for adaptation: how affect regulates conflict-driven control.
van Steenbergen, Henk; Band, Guido P H; Hommel, Bernhard
2010-11-01
Cognitive conflict plays an important role in tuning cognitive control to the situation at hand. On the basis of earlier findings demonstrating emotional modulations of conflict processing, we predicted that affective states may adaptively regulate goal-directed behavior that is driven by conflict. We tested this hypothesis by measuring conflict-driven control adaptations following experimental induction of four different mood states that could be differentiated along the dimensions of arousal and pleasure. After mood states were induced, 91 subjects performed a flanker task, which provided a measure of conflict adaptation. As predicted, pleasure level affected conflict adaptation: Less pleasure was associated with more conflict-driven control. Arousal level did not influence conflict adaptation. This study suggests that affect adaptively regulates cognitive control. Implications for future research and psychopathology are discussed.
Experimental study of shear rate dependence in perpetually sheared granular matter
Directory of Open Access Journals (Sweden)
Liu Sophie Yang
2017-01-01
Full Text Available We study the shear behaviour of various granular materials by conducting novel perpetual simple shear experiments over four orders of magnitude of relatively low shear rates. The newly developed experimental apparatus employed is called “3D Stadium Shear Device” which is an extended version of the 2D Stadium Shear Device [1]. This device is able to provide a non-radial dependent perpetual shear flow and a nearly linear velocity profile between two oppositely moving shear walls. Using this device, we are able to test a large variety of granular materials. Here, we demonstrate the applicability of the device on glass beads (diameter 1 mm, 3 mm, and 14 mm and rice. We particularly focus on studying these materials at very low inertial number I ranging from 10−6 to 10−2. We find that, within this range of I, the friction coefficient μ of glass beads has no shear rate dependence. A particularly appealing observation comes from testing rice, where the attainment of critical state develops under much longer duration than in other materials. Initially during shear we find a value of μ similar to that found for glass beads, but with time this value decreases gradually towards the asymptotic critical state value. The reason, we believe, lies in the fact that rice grains are strongly elongated; hence the time to achieve the stable μ is primarily controlled by the time for particles to align themselves with respect to the shear walls. Furthermore, the initial packing conditions of samples also plays a role in the evolution of μ when the shear strain is small, but that impact will eventually be erased after sufficient shear strain.
Design and Modeling of an Adaptively Controlled Rainwater Harvesting System
Directory of Open Access Journals (Sweden)
David Roman
2017-12-01
Full Text Available Management of urban stormwater to mitigate Combined Sewer Overflows (CSOs is a priority for many cities; yet, few truly innovative approaches have been proposed to address the problem. Recent advances in information technology are now, however, providing cost-effective opportunities to achieve better performance of conventional stormwater infrastructure through a Continuous Monitoring and Adaptive Control (CMAC approach. The primary objective of this study was to demonstrate that a CMAC approach can be applied to a conventional rainwater harvesting system in New York City to improve performance by minimizing discharge to the combined sewer during rainfall events, reducing water use for irrigation of local vegetation, and optimizing vegetation health. To achieve this objective, a hydrologic and hydraulic model was developed for a planned and designed rainwater harvesting system to explore multiple potential scenarios prior to the system’s actual construction. Model results indicate that the CMAC rainwater harvesting system is expected to provide significant performance improvements over conventional rainwater harvesting systems. The CMAC system is expected to capture and retain 76.6% of roof runoff per year on average, as compared to just 14.8% and 41.3% for conventional moisture and timer based systems, respectively. Similarly, the CMAC system is expected to use 81.4% and 18.0% less harvested rainwater than conventional moisture and timer based irrigation approaches, respectively. The flexibility of the CMAC approach to meet competing objectives is promising for widespread implementation in New York City and other heavily urbanized areas challenged by stormwater management issues.
Directory of Open Access Journals (Sweden)
Li Jing
2016-01-01
Full Text Available For the control of the liquid level of liquid ammonia in thermal power plant’s ammonia vaporization room, traditional PID controller parameter tuning is difficult to adapt to complex control systems, the setting of the traditional PID controller parameters is difficult to adapt to the complex control system. For the disadvantage of bad parameter setting, poor performance and so on the fuzzy adaptive PID control is proposed. Fuzzy adaptive PID control combines the advantages of traditional PID technology and fuzzy control. By using the fuzzy controller to intelligent control the object, the performance of the PID controller is further improved, and the control precision of the system is improved[1]. The simulation results show that the fuzzy adaptive PID controller not only has the advantages of high accuracy of PID controller, but also has the characteristics of fast and strong adaptability of fuzzy controller. It realizes the optimization of PID parameters which are in the optimal state, and the maximum increase production efficiency, so that are more suitable for nonlinear dynamic system.
Preliminary Test of Adaptive Neuro-Fuzzy Inference System Controller for Spacecraft Attitude Control
Directory of Open Access Journals (Sweden)
Sung-Woo Kim
2012-12-01
Full Text Available The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS. An ANFIS produces a control signal for one of the three axes of a spacecraft’s body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.
Adaptive Backstepping Self-balancing Control of a Two-wheel Electric Scooter
Directory of Open Access Journals (Sweden)
Nguyen Ngoc Son
2014-10-01
Full Text Available This paper introduces an adaptive backstepping control law for a two-wheel electric scooter (eScooter with a nonlinear uncertain model. Adaptive backstepping control is integrated with feedback control that satisfies Lyapunov stability. By using the recursive structure to find the controlled function and estimate uncertain parameters, an adaptive backstepping method allows us to build a feedback control law that efficiently controls a self-balancing controller of the eScooter. Additionally, a controller area network (CAN bus with high reliability is applied for communicating between the modules of the eScooter. Simulation and experimental results demonstrate the robustness and good performance of the proposed adaptive backstepping control.
Indirect Adaptive Attitude Control for a Ducted Fan Vertical Takeoff and Landing Microaerial Vehicle
Directory of Open Access Journals (Sweden)
Shouzhao Sheng
2015-01-01
Full Text Available The present paper addresses an attitude tracking control problem of a ducted fan microaerial vehicle. The proposed indirect adaptive controller can greatly reduce tracking error in the initial stage of the adaptive learning process by using an error compensation strategy and can achieve good capability to eliminate the adverse effect of measurement noises on the convergence of adjustable parameters. Moreover, the learning rate adaptation strategy is proposed to further minimize the adverse effect of large learning rates on the convergence of adjustable parameters. The experimental tests have illustrated the effectiveness of the proposed adaptive controller.
Human-centered headway control for adaptive cruise-controlled vehicles
Directory of Open Access Journals (Sweden)
Zhenhai Gao
2015-11-01
Full Text Available Driving characteristics of human drivers, such as driving safety, comfort, handiness, and efficiency, which are interrelated and contradictory, are synthetically considered to maintain a safe inter-vehicle distance in this article. For the multi-objective coordination control problem, the safety, handiness, comfort, and efficiency indicators are established via driving states and manipulated variable. Furthermore, a multi-performance indicator coordination mechanism is proposed via the invariant set and quadratic boundedness theory. A headway control algorithm for adaptive cruise control is established under the dynamic output feedback control framework. Finally, feasibility and effectiveness of the proposed algorithm are verified via closed-loop simulations under the following, cut-out, and cut-in typical operating conditions.
Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle
Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.
2010-01-01
This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.
Adaptive control of call acceptance in WCDMA network
Directory of Open Access Journals (Sweden)
Milan Manojle Šunjevarić
2013-10-01
Full Text Available In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probability of blocking.. Introduction We are witnessing a steady increase in the number of demands placed upon modern wireless networks. New applications and an increasing number of users as well as user activities growth in recent years reinforce the need for an efficient use of the spectrum and its proper distribution among different applications and classes of services. Besides humans, the last few years saw different computers, machines, applications, and, in the future, many other devices, RFID applications, and finally networked objects, as a new kind of wireless networks "users". Because of the exceptional rise in the number of users, the demands placed upon modern wireless networks are becoming larger, and spectrum management plays an important role. For these reasons, choosing an appropriate call admission control algorithm is of great importance. Multiple access and resource management in wireless networks Radio resource management of mobile networks is a set of algorithms to manage the use of radio resources with the aim is to maximize the total capacity of wireless systems with equal distribution of resources to users. Management of radio resources in cellular networks is usually located in the base station controller, the base station and the mobile terminal, and is based on decisions made on appropriate measurement and feedback. It is often defined as the maximum volume of traffic load that the system can provide for some of the requirements for the
Local Adaptive Control of Solar Photovoltaics and Electric Water Heaters for Real-time Grid Support
DEFF Research Database (Denmark)
Bhattarai, Bishnu Prasad; Mendaza, Iker Diaz de Cerio; Bak-Jensen, Birgitte
2016-01-01
, such as electric vehicles, electric water heaters (EWHs) etc. An adaptive control using only local measurements for the EWHs and PVs is proposed in this study to alleviate OV as well as UV issues. The adaptive control is designed such that it monitors the voltage at the point of connection and adjusts active...
Berkhoff, Arthur P.
Model errors in adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous work has shown that the addition of a low-authority controller that increases damping in the system may lead to improved performance of an adaptive,
A Comparative Study of Item Exposure Control Methods in Computerized Adaptive Testing.
Chang, Shun-Wen; Twu, Bor-Yaun
This study investigated and compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each of the exposure control algorithms was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design…
Berkhoff, A.P.
2011-01-01
Model errors in adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous work has shown that the addition of a low-authority controller that increases damping in the system may lead to improved performance of an adaptive,
Boussalis, Dhemetrios; Wang, Shyh J.
1992-01-01
This paper presents a method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems.
A Dung Beetle-like Leg and its Adaptive Neural Control
DEFF Research Database (Denmark)
Di Canio, Giuliano; Stoyanov, Stoyan; Larsen, Jørgen Christian
2016-01-01
also apply adaptive neural control, based on a central pattern generator (CPG) circuit with synaptic plasticity, to autonomously generate a proper stepping frequency of the leg. The controller can also adapt the leg movement to deal with external perturbations within a few steps....
Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure
Directory of Open Access Journals (Sweden)
Ashraf Ahmed Fahmy
2014-03-01
Full Text Available This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation. Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.
Simulation of dynamic behavior of quasi-brittle materials with new rate dependent damage model
Magalhaes Pereira, L.F.; Weerheijm, J.; Sluijs, Lambertus J.; Saouma, V.; Bolander, J.; Landis, E.
2016-01-01
Stress-based nonlocal model, Damage, Rate dependency, Dynamic crack-branching Abstract. In concrete often complex fracture and fragmentation patterns develop when subjected to high straining loads. The proper simulation of the dynamic cracking process in concrete is crucial for good predictions of
Aero-Effected Distributed Adaptive Control of Flexible Aircraft Using Active Bleed Project
National Aeronautics and Space Administration — The proposed research focuses on the development of a new adaptive control methodology for active control of wing aerodynamic shape to effect distributed aerodynamic...
A novel 3-D jerk chaotic system with three quadratic nonlinearities and its adaptive control
National Research Council Canada - National Science Library
Sundarapandian Vaidyanathan
2016-01-01
.... The Kaplan-Yorke dimension of the novel jerk chaotic system is derived as D = 2.17026. Next, an adaptive controller is designed via backstepping control method to globally stabilize the novel jerk chaotic system with unknown parameters...
Directory of Open Access Journals (Sweden)
Ming-Chang Pai
2012-01-01
Full Text Available Input shaping technique is widely used in reducing or eliminating residual vibration of flexible structures. The exact elimination of the residual vibration via input shaping technique depends on the amplitudes and instants of impulse application. However, systems always have parameter uncertainties which can lead to performance degradation. In this paper, a closed-loop input shaping control scheme is developed for uncertain flexible structures. The algorithm is based on input shaping control and adaptive sliding mode control. The proposed scheme does not need a priori knowledge of upper bounds on the norm of the uncertainties, but estimates them by using the adaptation technique. This scheme guarantees closed-loop system stability, and yields good performance and robustness in the presence of parameter uncertainties and external disturbances as well. Furthermore, it is shown that increasing the robustness to parameter uncertainties does not lengthen the duration of the impulse sequence. Simulation results demonstrate the efficacy of the proposed closed-loop input shaping control scheme.
Rivera, Daniel E; Pew, Michael D; Collins, Linda M
2007-05-01
The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.
Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review.
Aoi, Shinya; Manoonpong, Poramate; Ambe, Yuichi; Matsuno, Fumitoshi; Wörgötter, Florentin
2017-01-01
Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots.
Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review
Directory of Open Access Journals (Sweden)
Shinya Aoi
2017-08-01
Full Text Available Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task. In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots.
Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review
Aoi, Shinya; Manoonpong, Poramate; Ambe, Yuichi; Matsuno, Fumitoshi; Wörgötter, Florentin
2017-01-01
Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots. PMID:28878645
Energy Technology Data Exchange (ETDEWEB)
Hwang, Eun-Ju; Hyun, Chang-Ho; Kim, Euntai [ICS Laboratory (B723), Department of Electrical and Electronic Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749 (Korea, Republic of); Park, Mignon [ICS Laboratory (B723), Department of Electrical and Electronic Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749 (Korea, Republic of)], E-mail: mignpark@yonsei.ac.kr
2009-05-11
This Letter presents fuzzy model-based robust tracking control for the adaptive synchronization of uncertain chaotic systems. Fuzzy model and adaptive algorithm are employed to present the unknown chaotic systems. H{sup {infinity}} and sliding mode control are combined to construct a robust tracking controller. The incorporated H{sup {infinity}} controller can attenuate the external disturbance and approximation error to any prescribed level. The proposed scheme guarantees that all the variables are bounded and the tracking error is compensated.
Fast spacecraft adaptive attitude tracking control through immersion and invariance design
Wen, Haowei; Yue, Xiaokui; Li, Peng; Yuan, Jianping
2017-10-01
This paper presents a novel non-certainty-equivalence adaptive control method for the attitude tracking control problem of spacecraft with inertia uncertainties. The proposed immersion and invariance (I&I) based adaptation law provides a more direct and flexible approach to circumvent the limitations of the basic I&I method without employing any filter signal. By virtue of the adaptation high-gain equivalence property derived from the proposed adaptive method, the closed-loop adaptive system with a low adaptation gain could recover the high adaptation gain performance of the filter-based I&I method, and the resulting control torque demands during the initial transient has been significantly reduced. A special feature of this method is that the convergence of the parameter estimation error has been observably improved by utilizing an adaptation gain matrix instead of a single adaptation gain value. Numerical simulations are presented to highlight the various benefits of the proposed method compared with the certainty-equivalence-based control method and filter-based I&I control schemes.
The beauty of simple adaptive control and new developments in nonlinear systems stability analysis
Barkana, Itzhak
2014-12-01
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.
REVIEW: Internal models in sensorimotor integration: perspectives from adaptive control theory
Tin, Chung; Poon, Chi-Sang
2005-09-01
Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems—such as sensorimotor prediction or the resolution of vestibular sensory ambiguity—is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.
Energy Technology Data Exchange (ETDEWEB)
Ben Youssef, C.; Dahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1995-12-31
Controlling the process of a fixed bed bioreactor imply solving filtering and adaptative control problems. Estimation processes have been developed for unmeasurable parameters. An adaptative non linear control has been built, instead of conventional approaches trying to linearize the system and apply a linear control system. (D.L.) 10 refs.
Directory of Open Access Journals (Sweden)
Mingyue Cui
2016-09-01
Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.
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 ...
Final report on development of adaptive control algorithm for active control of total power input
DEFF Research Database (Denmark)
Laugesen, Søren; Henriksen, Eigil; Ohlrich, Mogens
1996-01-01
An adaptive realtime algorithm for minimisation of total power input to a receiving structure has been derived, implemented and tested, and this control algorithm has proved to be robust and reliable. Simulation studies ahve clearly demonstrated that the algorithm behaves exactly as should...... be expected from frequency domain predictions. Experimental trials in the laboratory have supported these observations. Again, the reductions of the measured total power input to the receiving structure were in perfect agreement with the results obtained by analytically minimising the controller cost function....... Apart from the good results obtained with this control strategy under ideal circumstances, observations have also been made of the detrimental effects of 'flanking paths' and measurement errors that may be experienced in a practical implementation....
Temporal adaptation enhances efficient contrast gain control on natural images.
Directory of Open Access Journals (Sweden)
Fabian Sinz
Full Text Available Divisive normalization in primary visual cortex has been linked to adaptation to natural image statistics in accordance to Barlow's redundancy reduction hypothesis. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization is rather inefficient in reducing local contrast correlations, but that a simple temporal contrast adaptation mechanism of the half-saturation constant can substantially increase its efficiency. Our findings reveal the experimentally observed temporal dynamics of divisive normalization to be critical for redundancy reduction.
Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.
Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min
2014-01-01
An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.
Energy Technology Data Exchange (ETDEWEB)
Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Yi, Sun [North Carolina A and T State Univ., Raleigh (United States)
2016-08-15
In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.
Energy Technology Data Exchange (ETDEWEB)
Lin, Tsung-Chih, E-mail: tclin@fcu.edu.tw [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Lee, Tun-Yuan [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Balas, Valentina E. [Aurel Vlaicu University of Arad, B-dul Revolutiei 77, 310130 Arad (Romania)
2011-10-15
Highlights: > We study uncertain fractional order chaotic systems synchronization. > Lyapunov synthesis is used to derive control law and adaptive laws. > Based on sliding mode control, chattering phenomena in the control effort can be reduced. - Abstract: This paper deals with chaos synchronization between two different uncertain fractional order chaotic systems based on adaptive fuzzy sliding mode control (AFSMC). With the definition of fractional derivatives and integrals, a fuzzy Lyapunov synthesis approach is proposed to tune free parameters of the adaptive fuzzy controller on line by output feedback control law and adaptive law. Moreover, chattering phenomena in the control efforts can be reduced. The sliding mode design procedure not only guarantees the stability and robustness of the proposed AFSMC, but also the external disturbance on the synchronization error can be attenuated. The simulation example is included to confirm validity and synchronization performance of the advocated design methodology.
Long, Lijun; Zhao, Jun
2017-07-01
In this paper, the problem of adaptive neural output-feedback control is addressed for a class of multi-input multioutput (MIMO) switched uncertain nonlinear systems with unknown control gains. Neural networks (NNs) are used to approximate unknown nonlinear functions. In order to avoid the conservativeness caused by adoption of a common observer for all subsystems, an MIMO NN switched observer is designed to estimate unmeasurable states. A new switched observer-based adaptive neural control technique for the problem studied is then provided by exploiting the classical average dwell time (ADT) method and the backstepping method and the Nussbaum gain technique. It effectively handles the obstacle about the coexistence of multiple Nussbaum-type function terms, and improves the classical ADT method, since the exponential decline property of Lyapunov functions for individual subsystems is no longer satisfied. It is shown that the technique proposed is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop system under a class of switching signals with ADT, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the approach proposed is illustrated by its application to a two inverted pendulum system.
Innate Control of Adaptive Immunity: Beyond the Three-Signal Paradigm.
Jain, Aakanksha; Pasare, Chandrashekhar
2017-05-15
Activation of cells in the adaptive immune system is a highly orchestrated process dictated by multiples cues from the innate immune system. Although the fundamental principles of innate control of adaptive immunity are well established, it is not fully understood how innate cells integrate qualitative pathogenic information to generate tailored protective adaptive immune responses. In this review, we discuss complexities involved in the innate control of adaptive immunity that extend beyond TCR engagement, costimulation, and priming cytokine production but are critical for the generation of protective T cell immunity. Copyright © 2017 by The American Association of Immunologists, Inc.
DEFF Research Database (Denmark)
Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin
2013-01-01
Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate......, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize...... on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models...
Controlling the local false discovery rate in the adaptive Lasso
Sampson, J. N.
2013-04-09
The Lasso shrinkage procedure achieved its popularity, in part, by its tendency to shrink estimated coefficients to zero, and its ability to serve as a variable selection procedure. Using data-adaptive weights, the adaptive Lasso modified the original procedure to increase the penalty terms for those variables estimated to be less important by ordinary least squares. Although this modified procedure attained the oracle properties, the resulting models tend to include a large number of "false positives" in practice. Here, we adapt the concept of local false discovery rates (lFDRs) so that it applies to the sequence, λn, of smoothing parameters for the adaptive Lasso. We define the lFDR for a given λn to be the probability that the variable added to the model by decreasing λn to λn-δ is not associated with the outcome, where δ is a small value. We derive the relationship between the lFDR and λn, show lFDR =1 for traditional smoothing parameters, and show how to select λn so as to achieve a desired lFDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate specific antigen.
Towards Adaptive Virtual Camera Control In Computer Games
DEFF Research Database (Denmark)
Burelli, Paolo; Yannakakis, Georgios N.
2011-01-01
machine learning to build predictive models of the virtual camera behaviour. The perfor- mance of the models on unseen data reveals accuracies above 70% for all the player behaviour types identified. The characteristics of the gener- ated models, their limits and their use for creating adaptive automatic...
Online adaptive neural control of a robotic lower limb prosthesis
Spanias, J. A.; Simon, A. M.; Finucane, S. B.; Perreault, E. J.; Hargrove, L. J.
2018-02-01
Objective. The purpose of this study was to develop and evaluate an adaptive intent recognition algorithm that continuously learns to incorporate a lower limb amputee’s neural information (acquired via electromyography (EMG)) as they ambulate with a robotic leg prosthesis. Approach. We present a powered lower limb prosthesis that was configured to acquire the user’s neural information and kinetic/kinematic information from embedded mechanical sensors, and identify and respond to the user’s intent. We conducted an experiment with eight transfemoral amputees over multiple days. EMG and mechanical sensor data were collected while subjects using a powered knee/ankle prosthesis completed various ambulation activities such as walking on level ground, stairs, and ramps. Our adaptive intent recognition algorithm automatically transitioned the prosthesis into the different locomotion modes and continuously updated the user’s model of neural data during ambulation. Main results. Our proposed algorithm accurately and consistently identified the user’s intent over multiple days, despite changing neural signals. The algorithm incorporated 96.31% [0.91%] (mean, [standard error]) of neural information across multiple experimental sessions, and outperformed non-adaptive versions of our algorithm—with a 6.66% [3.16%] relative decrease in error rate. Significance. This study demonstrates that our adaptive intent recognition algorithm enables incorporation of neural information over long periods of use, allowing assistive robotic devices to accurately respond to the user’s intent with low error rates.
Model-free adaptive sliding mode controller design for generalized ...
Indian Academy of Sciences (India)
L M WANG
2017-08-16
Aug 16, 2017 ... Abstract. A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master–slave system ...
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.
CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots.
Liu, Chengju; Chen, Qijun; Wang, Danwei
2011-06-01
This paper deals with the locomotion control of quadruped robots inspired by the biological concept of central pattern generator (CPG). A control architecture is proposed with a 3-D workspace trajectory generator and a motion engine. The workspace trajectory generator generates adaptive workspace trajectories based on CPGs, and the motion engine realizes joint motion imputes. The proposed architecture is able to generate adaptive workspace trajectories online by tuning the parameters of the CPG network to adapt to various terrains. With feedback information, a quadruped robot can walk through various terrains with adaptive joint control signals. A quadruped platform AIBO is used to validate the proposed locomotion control system. The experimental results confirm the effectiveness of the proposed control architecture. A comparison by experiments shows the superiority of the proposed method against the traditional CPG-joint-space control method.
Adaptive fuzzy sliding control of single-phase PV grid-connected inverter.
Directory of Open Access Journals (Sweden)
Juntao Fei
Full Text Available In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance.
Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3
Frost, Susan A.; Balas, Mark J.; Wright, Alan D.
2009-01-01
Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.
Adaptive Global Sliding Mode Control for MEMS Gyroscope Using RBF Neural Network
Directory of Open Access Journals (Sweden)
Yundi Chu
2015-01-01
Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.
Directory of Open Access Journals (Sweden)
Xuxi Zhang
2014-01-01
Full Text Available The attitude tracking problem of spacecraft in the presence of unknown disturbance is investigated. By using the adaptive control technique and the Lyapunov stability theory, a chattering-free adaptive sliding mode control law is proposed for the attitude tracking problem of spacecraft with unknown disturbance. Simulation results are employed to demonstrate the effectiveness of the proposed control design technique in this paper.
Directory of Open Access Journals (Sweden)
Leng Fei
2008-09-01
Full Text Available This paper discusses the seismic analysis of concrete dams with consideration of material nonlinearity. Based on a consistent rate-dependent model and two thermodynamics-based models, two thermodynamics-based rate-dependent constitutive models were developed with consideration of the influence of the strain rate. They can describe the dynamic behavior of concrete and be applied to nonlinear seismic analysis of concrete dams taking into account the rate sensitivity of concrete. With the two models, a nonlinear analysis of the seismic response of the Koyna Gravity Dam and the Dagangshan Arch Dam was conducted. The results were compared with those of a linear elastic model and two rate-independent thermodynamics-based constitutive models, and the influences of constitutive models and strain rate on the seismic response of concrete dams were discussed. It can be concluded from the analysis that, during seismic response, the tensile stress is the control stress in the design and seismic safety evaluation of concrete dams. In different models, the plastic strain and plastic strain rate of concrete dams show a similar distribution. When the influence of the strain rate is considered, the maximum plastic strain and plastic strain rate decrease.
Rate dependence of grain boundary sliding via time-scaling atomistic simulations
Hammami, Farah; Kulkarni, Yashashree
2017-02-01
Approaching experimentally relevant strain rates has been a long-standing challenge for molecular dynamics method which captures phenomena typically on the scale of nanoseconds or at strain rates of 107 s-1 and higher. Here, we use grain boundary sliding in nanostructures as a paradigmatic problem to investigate rate dependence using atomistic simulations. We employ a combination of time-scaling computational approaches, including the autonomous basin climbing method, the nudged elastic band method, and kinetic Monte Carlo, to access strain rates ranging from 0.5 s-1 to 107 s-1. Combined with a standard linear solid model for viscoelastic behavior, our simulations reveal that grain boundary sliding exhibits noticeable rate dependence only below strain rates on the order of 10 s-1 but is rate independent and consistent with molecular dynamics at higher strain rates.
Control of plankton seasonal succession by adaptive grazing
DEFF Research Database (Denmark)
Mariani, Patrizio; Andersen, Ken Haste; Visser, Andre
2013-01-01
The ecological succession of phytoplankton communities in temperate seas is characterized by the dominance of nonmotile diatoms during spring and motile flagellates during summer, a pattern often linked to the seasonal variation in the physical environment and nutrient availability. We focus...... on the effects of adaptive zooplankton grazing behavior on the seasonal succession of temperate plankton communities in an idealized community model consisting of a zooplankton grazer and two phytoplankton species, one motile and the other nonmotile. The grazer can switch between ambush feeding on motile cells...... behavior that optimizes its fitness. The adaptive grazing model predicts essential features of the seasonal plankton succession reported from temperate seas, including the vertical distribution and seasonal variation in the relative abundance of motile and nonmotile phytoplankton and the seasonal variation...
Rate-Dependent Left Bundle-Branch Block in a Child With Propionic Aciduria
Ardoin, Kipp B.; Moodie, Douglas S.; Snyder, Christopher S.
2009-01-01
In most cases, a left bundle-branch block pattern on an electrocardiogram is a postoperative phenomenon. Under rare circumstances, it can be found in patients after myocardial infarction or in patients with hypertrophic cardiomyopathy, or it can be exercised induced. We describe a pediatric patient with propionic aciduria, dilated cardiomyopathy, and rate-dependent left bundle-branch block on her electrocardiogram. PMID:21603417
Parallel evolution controlled by adaptation and covariation in ammonoid cephalopods
Klug Christian; De Baets Kenneth; Monnet Claude
2011-01-01
Abstract Background A major goal in evolutionary biology is to understand the processes that shape the evolutionary trajectory of clades. The repeated and similar large-scale morphological evolutionary trends of distinct lineages suggest that adaptation by means of natural selection (functional constraints) is the major cause of parallel evolution, a very common phenomenon in extinct and extant lineages. However, parallel evolution can result from other processes, which are usually ignored or...
Electrically controllable ionic polymeric gels as adaptive optical lenses
Salehpoor, Karim; Shahinpoor, Mohsen; Mojarrad, Mehran
1996-02-01
Reversible change in optical properties of ionic polymeric gels, 2-acrylamido-2-methylpropane sulfonic acid (PAMPS) and polyacrylic acid plus sodium acrylate cross-linked with bisacrylamide (PAAM), under the effect of an electric field is reported. The shape of a cylindrical piece of the gel, with flat top and bottom surfaces, changed when affected by an electric field. The top surface became curved and the sense of the curvature (whether concave or convex) depended on the polarity of the applied electric field. The curvature of the surface changed from concave to convex and vice versa by changing the polarity of the electric field. By the use of an optical apparatus, focusing capability of the curved surface was verified and the focal length of the deformed gel was measured. The effect of the intensity of the applied electric field on the surface curvature and thus, on the focal length of the gel are tested. Different mechanisms are discussed; either of them or their combination may explain the surface deformation and curvature. Practical difficulties in the test procedure and the future potential of the electrically adaptive and active optical lenses are also discussed. These adaptive lenses may be considered as smart adaptive lenses for contact lens or other optical applications requiring focal point undulation.
interval type-2 fuzzy gain-adaptive controller of a doubly fed
African Journals Online (AJOL)
Loukal K and Benalia L
2016-05-01
May 1, 2016 ... ABSTRACT. This paper presents a comparison between an Interval Type-2 Fuzzy Gain-Adaptive IP. (IT2FGAIP) controller and a conventional IP controller used for speed control with a direct stator flux orientation control of a doubly fed induction motor. In particular, the introduction part of the paper presents ...
Directory of Open Access Journals (Sweden)
Ali Unluturk
2017-03-01
Full Text Available In this article, a novel real-time artificial neural network–based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platform for experimental setup is made for balance problem on different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error and mean absolute controller output data are employed for surface estimation by using artificial neural network. In a designed two-wheeled mobile balance robot system, robot tilt angle is estimated via Kalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.
Directory of Open Access Journals (Sweden)
James Lua
2004-01-01
Full Text Available Marine composite materials typically exhibit significant rate dependent response characteristics when subjected to extreme dynamic loading conditions. In this work, a strain-rate dependent continuum damage model is incorporated with multicontinuum technology (MCT to predict damage and failure progression for composite material structures. MCT treats the constituents of a woven fabric composite as separate but linked continua, thereby allowing a designer to extract constituent stress/strain information in a structural analysis. The MCT algorithm and material damage model are numerically implemented with the explicit finite element code LS-DYNA3D via a user-defined material model (umat. The effects of the strain-rate hardening model are demonstrated through both simple single element analyses for woven fabric composites and also structural level impact simulations of a composite panel subjected to various impact conditions. Progressive damage at the constituent level is monitored throughout the loading. The results qualitatively illustrate the value of rate dependent material models for marine composite materials under extreme dynamic loading conditions.
Zhai, Ding; An, Liwei; Ye, Dan; Zhang, Qingling
2018-03-01
This paper investigates the adaptive static output feedback (SOF) control problem for continuous-time linear systems with stochastic sensor failures. A multi-Markovian variable is introduced to denote the failure scaling factors for each sensor. Different from the existing results, the failure parameters are stochastically jumping and their bounds of are unknown. An adaptive reliable SOF control method is proposed, where the controller parameters are updated automatically to compensate for the failure effects on systems. A novel cubic absolute Lyapunov function is proposed to design adaptive laws only using measured output with sensor failures, and the convergence of jumping adaptive parameters is ensured by a trajectory initialization approach. The resultant designs can guarantee the asymptotic stability with an adaptive performance of closed-loop systems regardless of sensor failures. Finally, the simulation results on the "Raptor-90" helicopter are given to show the effectiveness of the proposed approaches.
Anti-Synchronization of Tigan and Li Systems with Unknown Parameters via Adaptive Control
Directory of Open Access Journals (Sweden)
Sundarapandian VAIDYANATHAN
2012-01-01
Full Text Available In this paper, the adaptive nonlinear control method has been deployed to derive new resultsfor the anti-synchronization of identical Tigan systems (2008, identical Li systems (2009 and nonidenticalTigan and Li systems. In adaptive anti-synchronization of identical chaotic systems, theparameters of the master and slave systems are unknown and the feedback control law has been derivedusing the estimates of the system parameters. In adaptive anti-synchronization of non-identical chaoticsystems, the parameters of the master system are known, but the parameters of the slave system areunknown and accordingly, the feedback control law has been derived using the estimates of theparameters of the slave system. Our adaptive synchronization results derived in this paper for theuncertain Tigan and Li systems are established using Lyapunov stability theory. Numerical simulationsare shown to demonstrate the effectiveness of the adaptive anti-synchronization schemes for theuncertain chaotic systems addressed in this paper.
Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di
2017-04-01
This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.
Li, Yongming; Tong, Shaocheng
2016-10-01
In this paper, a fuzzy adaptive switched control approach is proposed for a class of uncertain nonholonomic chained systems with input nonsmooth constraint. In the control design, an auxiliary dynamic system is designed to address the input nonsmooth constraint, and an adaptive switched control strategy is constructed to overcome the uncontrollability problem associated with x0(t0) = 0. By using fuzzy logic systems to tackle unknown nonlinear functions, a fuzzy adaptive control approach is explored based on the adaptive backstepping technique. By constructing the combination approximation technique and using Young's inequality scaling technique, the number of the online learning parameters is reduced to n and the 'explosion of complexity' problem is avoid. It is proved that the proposed method can guarantee that all variables of the closed-loop system converge to a small neighbourhood of zero. Two simulation examples are provided to illustrate the effectiveness of the proposed control approach.
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2017-10-01
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.
Frequency Adaptive Repetitive Control of Grid-Tied Single-Phase PV Inverters
DEFF Research Database (Denmark)
Zhou, Keliang; Yang, Yongheng; Blaabjerg, Frede
2015-01-01
. This paper thus explores a frequency adaptive repetitive control strategy for grid converters, which employs fractional delay filters in order to adapt to the change of the grid frequency. Case studies with experimental results of a single-phase grid-connected PV inverter system are provided to verify...
Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System
Chen, Ching-Huei; Chang, Shu-Wei
2015-01-01
The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…
Biohybrid control of general linear systems using the adaptive filter model of cerebellum
Directory of Open Access Journals (Sweden)
Emma D. Wilson
2015-07-01
Full Text Available The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems such as the vestibulo-ocular reflex (VOR and to sensory processing problems such as the adaptive cancellation of reafferent noise. It has also been successfully applied to problems in robotics such as adaptive camera stabilisation and sensor noise cancellation. In previous applications to inverse control problems the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity control of this plant results in unstable learning and control. To be more generally useful in engineering problems it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC scheme, which stabilises the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
Adaptive and learning control of large space structures
Montgomery, R. C.; Thau, F. J.
1980-01-01
The paper describes the adaptive learning system for space operations which assumes that structural testing can be conducted during deployment and assembly. Simulation results using the solar electric propulsion array and a novel remote sensor are presented; they involve faster scan television coverage of the motions of the array from four cameras on the corners of the Space Shuttle payload bay. The description of the simulation, the filtering algorithm for processing the TV data, the parameter extraction algorithm, and the simulation results are presented.
The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller
Energy Technology Data Exchange (ETDEWEB)
Calvino, F.; Gennusa, M. La; Rizzo, G.; Scaccianoce, G. [Universita di Palermo (Italy). Dept. of Energy and Environmental Researches
2004-02-01
The control and the monitoring of indoor thermal conditions represents a pre-eminent task with the aim of ensuring suitable working and living spaces to people. Especially in industrialised countries, in fact, several rules and standards have been recently released in order of providing technicians with suitable design tools and effective indexes and parameters for the checking of the indoor microclimate. Among them, predicted mean vote (PMV) index is often adopted for assessing the thermal comfort conditions of thermal moderate environments. Unfortunately, the PMV index is characterised by non-linear features, which could determine some difficulties when monitoring and controlling HVAC equipment. In order of overcoming these problems, a fuzzy control for HVAC system is here described. It represents a new simple approach, focused on the application of an adaptive fuzzy controller that avoids the modelling of indoor and outdoor environments. After a brief description of the method, some simulation results are presented. A simplified application, referring to a room belonging to a university building, is finally reported. (author)
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...
Directory of Open Access Journals (Sweden)
Yu Oliver
2006-01-01
Full Text Available To minimize QoS degradations during nonstationary packet loadings, predictive rate schedulers adapt the operation according to anticipated packet arrival rates deduced via specified estimation algorithm. Existing predictive rate schedulers are developed under the assumption of perfect estimation, which may not be possible in future CDMA-based cellular networks characterized with highly nonstationary and bursty traffic. Additional shortcoming of existing rate schedulers is the coupling of delay and bandwidth, that is, close interdependence of delay and bandwidth (rate, whereby controlling one is accomplished solely by changing the other. In order to mitigate for the arrival rate estimation errors and delay-bandwidth coupling, this paper presents the feedback-enhanced target-tracking weighted fair queuing (FT-WFQ rate scheduler. It is an adaptive rate scheduler over multiclass CDMA systems with predictive adaptation control to adapt to nonstationary loadings; and feedback-enhanced reactive adaptation control to counteract arrival rate estimation errors. When the predictive adaptation control is not able to maintain long-term delay targets, feedback information will trigger reactive adaptation control. The objective of FT-WFQ scheduler is to minimize deviations from delay targets subject to maximum throughput utilization. Analytical and simulation results indicate that FT-WFQ is able to substantially reduce degradations caused by arrival rate estimation errors and to minimize delay degradations during nonstationary loading conditions.
Adaptive neuro-fuzzy inference system based automatic generation control
Energy Technology Data Exchange (ETDEWEB)
Hosseini, S.H.; Etemadi, A.H. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran)
2008-07-15
Fixed gain controllers for automatic generation control are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute control gains. A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by the results of off-line studies obtained using particle swarm optimization, is proposed in this paper to optimize and update control gains in real-time according to load variations. Also, frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is demonstrated via simulations. Compliance of the proposed method with NERC control performance standard is verified. (author)
Method study on fuzzy-PID adaptive control of electric-hydraulic hitch system
Li, Mingsheng; Wang, Liubu; Liu, Jian; Ye, Jin
2017-03-01
In this paper, fuzzy-PID adaptive control method is applied to the control of tractor electric-hydraulic hitch system. According to the characteristics of the system, a fuzzy-PID adaptive controller is designed and the electric-hydraulic hitch system model is established. Traction control and position control performance simulation are carried out with the common PID control method. A field test rig was set up to test the electric-hydraulic hitch system. The test results showed that, after the fuzzy-PID adaptive control is adopted, when the tillage depth steps from 0.1m to 0.3m, the system transition process time is 4s, without overshoot, and when the tractive force steps from 3000N to 7000N, the system transition process time is 5s, the system overshoot is 25%.
Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network
Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui
2012-01-01
This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587
Simple adaptive control system design for a quadrotor with an internal PFC
Energy Technology Data Exchange (ETDEWEB)
Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto; Takagi, Taro [Dept. of Mechanical Systems Engineering, Kumamoto University 2-39-1 Kurokami, Kumamoto, 860-8555 (Japan)
2014-12-10
The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loop of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations.
Nonlinear adaptive PID control for greenhouse environment based on RBF network.
Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui
2012-01-01
This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production.
Directory of Open Access Journals (Sweden)
Wang Chao
2016-03-01
Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.
Performance Optimizing Adaptive Control with Time-Varying Reference Model Modification
Nguyen, Nhan T.; Hashemi, Kelley E.
2017-01-01
This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the performance optimization requirement obtained from an optimal control problem. The time-varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance metric. The effectiveness of the proposed method is demonstrated by an application of maneuver load alleviation control for a flexible aircraft.
Non-identifier based adaptive control in mechatronics theory and application
Hackl, Christoph M
2017-01-01
This book introduces non-identifier-based adaptive control (with and without internal model) and its application to the current, speed and position control of mechatronic systems such as electrical synchronous machines, wind turbine systems, industrial servo systems, and rigid-link, revolute-joint robots. In mechatronics, there is often only rough knowledge of the system. Due to parameter uncertainties, nonlinearities and unknown disturbances, model-based control strategies can reach their performance or stability limits without iterative controller design and performance evaluation, or system identification and parameter estimation. The non-identifier-based adaptive control presented is an alternative that neither identifies the system nor estimates its parameters but ensures stability. The adaptive controllers are easy to implement, compensate for disturbances and are inherently robust to parameter uncertainties and nonlinearities. For controller implementation only structural system knowledge (like relativ...
Active random noise control using adaptive learning rate neural networks with an immune feedback law
Sasaki, Minoru; Kuribayashi, Takumi; Ito, Satoshi
2005-12-01
In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. In the proposed method, because of the immune feedback law change a learning rate of the neural networks individually and adaptively, it is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks with the immune feedback law. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.
Online adaptive assistance control in robot-based neurorehabilitation therapy.
Stroppa, Fabio; Marcheschi, Simone; Mastronicola, Nicola; Loconsole, Claudio; Frisoli, Antonio
2017-07-01
Repetitive and task specific robot-based rehabilitation has been proved to be effective for motor recovery over time. During a therapy, the task should improve subject's impaired movements, but also enhance their efforts for a more effective recovery. This requires an accurate tuning of the task difficulty, which should be tailored directly to the patient. In this work, we propose a system for real-time assistance adaptation based on online performance evaluation for post-stroke subjects. In particular, the aim of the system is to implement the "assist-as-needed" paradigm based on actual patients' motor skills during a therapy session with an active upper-limb robotic exoskeleton. The strength of the work is to propose a real-time algorithm for the assistance tuning based on an "assistance-performance" relationship. Such a relationship is based on experimental measurements, and allows the algorithm to compute a straightforward calculation of the assistance required. Finally, an assessment phase will show how the system provides assistance based on the difficulties experienced from the subjects, also facilitating their adaptation during the task.
Mind wandering and the adaptive control of attentional resources.
Kam, Julia W Y; Dao, Elizabeth; Stanciulescu, Maria; Tildesley, Hamish; Handy, Todd C
2013-06-01
Mind wandering is a natural, transient state wherein our neurocognitive systems become temporarily decoupled from the external sensory environment as our thoughts drift away from the current task at hand. Yet despite the ubiquity of mind wandering in everyday human life, we rarely seem impaired in our ability to adaptively respond to the external environment when mind wandering. This suggests that despite widespread neurocognitive decoupling during mind wandering states, we may nevertheless retain some capacity to attentionally monitor external events. But what specific capacities? In Experiment 1, using traditional performance measures, we found that both volitional and automatic forms of visual-spatial attentional orienting were significantly attenuated when mind wandering. In Experiment 2, however, ERPs revealed that, during mind wandering states, there was a relative preservation of sensitivity to deviant or unexpected sensory events, as measured via the auditory N1 component. Taken together, our findings suggest that, although some selective attentional processes may be subject to down-regulation during mind wandering, we may adaptively compensate for these neurocognitively decoupled states by maintaining automatic deviance-detection functions.
Salden, Ron; Paas, Fred; Van Merriënboer, Jeroen
2008-01-01
Salden, R.J.C.M., Paas, F., & Van Merriënboer, J.J.G. (2006). Personalised adaptive task selection in air traffic control: Effects on training efficiency and transfer. Learning and Instruction, 16, 350-362
Pilot Induced Oscillation Suppression Under Off-Nominal Conditions Using L1 Adaptive Control Project
National Aeronautics and Space Administration — ZONA Technology, Inc. proposes an R&D effort to develop an adaptive flight control system which can provide near-nominal performance for the aircraft under...
Adaptive RBF Neural Network Control for Three-Phase Active Power Filter
Directory of Open Access Journals (Sweden)
Juntao Fei
2013-05-01
Full Text Available Abstract An adaptive radial basis function (RBF neural network control system for three-phase active power filter (APF is proposed to eliminate harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non-linear load and improve the quality of the power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of the neural network can be adaptively updated to achieve the desired tracking task. The simulation results demonstrate good performance, for example showing small current tracking error, reduced total harmonic distortion (THD, improved accuracy and strong robustness in the presence of parameters variation and nonlinear load. It is shown that the adaptive RBF neural network control system for three-phase APF gives better control than hysteresis control.
Automated Clutch of AMT Vehicle Based on Adaptive Generalized Minimum Variance Controller
National Research Council Canada - National Science Library
Ze Li; Xinhao Yang
2014-01-01
... of the automated clutch of automatic mechanical transmission vehicle. In this paper, an adaptive generalized minimum variance controller is applied to the automated clutch, which is driven by a brushless DC motor...
Detection of new in-path targets by drivers using Stop & Go Adaptive Cruise Control.
Stanton, Neville A; Dunoyer, Alain; Leatherland, Adam
2011-05-01
This paper reports on the design and evaluation of in-car displays used to support Stop & Go Adaptive Cruise Control. Stop & Go Adaptive Cruise Control is an extension of Adaptive Cruise Control, as it is able to bring the vehicle to a complete stop. Previous versions of Adaptive Cruise Control have only operated above 26 kph. The greatest concern for these technologies is the appropriateness of the driver's response in any given scenario. Three different driver interfaces were proposed to support the detection of modal, spatial and temporal changes of the system: an iconic display, a flashing iconic display, and a representation of the radar. The results show that drivers correctly identified more changes detected by the system with the radar display than with the other displays, but higher levels of workload accompanied this increased detection. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.
DEFF Research Database (Denmark)
Yao, Wei; Fang, Jiakun; Zhao, Ping
2013-01-01
In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have...... system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency...
New fuzzy approximate model for indirect adaptive control of distributed solar collectors
Elmetennani, Shahrazed
2014-06-01
This paper studies the problem of controlling a parabolic solar collectors, which consists of forcing the outlet oil temperature to track a set reference despite possible environmental disturbances. An approximate model is proposed to simplify the controller design. The presented controller is an indirect adaptive law designed on the fuzzy model with soft-sensing of the solar irradiance intensity. The proposed approximate model allows the achievement of a simple low dimensional set of nonlinear ordinary differential equations that reproduces the dynamical behavior of the system taking into account its infinite dimension. Stability of the closed loop system is ensured by resorting to Lyapunov Control functions for an indirect adaptive controller.
Campbell, Stefan F.; Kaneshige, John T.
2010-01-01
Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).
New class of control laws for robotic manipulators. I - Nonadaptive case. II - Adaptive case
Wen, John T.; Bayard, David S.
1988-01-01
A new class of exponentially stabilizing control laws for joint level control of robot arms is discussed. Closed-loop exponential stability has been demonstrated for both the set point and tracking control problems by a slight modification of the energy Lyapunov function and the use of a lemma which handles third-order terms in the Lyapunov function derivatives. In the second part, these control laws are adapted in a simple fashion to achieve asymptotically stable adaptive control. The analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and uses a parameterization based on physical (time-invariant) quantities.
Adapting Wireless Technology to Lighting Control and Environmental Sensing
Energy Technology Data Exchange (ETDEWEB)
Dana Teasdale; Francis Rubinstein; Dave Watson; Steve Purdy
2005-10-01
The high cost of retrofitting buildings with advanced lighting control systems is a barrier to adoption of this energy-saving technology. Wireless technology, however, offers a solution to mounting installation costs since it requires no additional wiring to implement. To demonstrate the feasibility of such a system, a prototype wirelessly-controlled advanced lighting system was designed and built. The system includes the following components: a wirelessly-controllable analog circuit module (ACM), a wirelessly-controllable electronic dimmable ballast, a T8 3-lamp fixture, an environmental multi-sensor, a current transducer, and control software. The ACM, dimmable ballast, multi-sensor, and current transducer were all integrated with SmartMesh{trademark} wireless mesh networking nodes, called motes, enabling wireless communication, sensor monitoring, and actuator control. Each mote-enabled device has a reliable communication path to the SmartMesh Manager, a single board computer that controls network functions and connects the wireless network to a PC running lighting control software. The ACM is capable of locally driving one or more standard 0-10 Volt electronic dimmable ballasts through relay control and a 0-10 Volt controllable output. The mote-integrated electronic dimmable ballast is designed to drive a standard 3-lamp T8 light fixture. The environmental multi-sensor measures occupancy, light level and temperature. The current transducer is used to measure the power consumed by the fixture. Control software was developed to implement advanced lighting algorithms, including daylight ramping, occupancy control, and demand response. Engineering prototypes of each component were fabricated and tested in a bench-scale system. Based on standard industry practices, a cost analysis was conducted. It is estimated that the installation cost of a wireless advanced lighting control system for a retrofit application is at least 30% lower than a comparable wired system for
An adaptive compound control system for the ESC of electric-wheel vehicle
Directory of Open Access Journals (Sweden)
Wang Cheng
2015-01-01
Full Text Available The aim of this study is to achieve the adaptive control for the Electronic Stability Control (ESC of electric-wheel vehicle. An adaptive compound control system is designed. The system main includes a yaw velocity controller and a side slip angle controller. The yaw velocity controller is robust PID. The side slip angle controller is neural network PID. The PID parameters are adjusted adaptively through robust and neural network. The two controllers constitute the compound controller. Lateral acceleration is used as a limit value and added to the yaw velocity control. A full vehicle model is built to simulate the real electric-wheel vehicle. The ideal values of control parameters are introduced through the ideal vehicle model. Simulation experiments were dong, which included a steering wheel step input experiment and a sine input experiment. The experimental results show that the steady state and the transient performance of the control system are good. The adaptive compound control system is fit for the ESC.
Adaptive Fuzzy Containment Control for Uncertain Nonlinear Multiagent Systems
Directory of Open Access Journals (Sweden)
Yang Yu
2014-01-01
Full Text Available This paper considers the containment control problem for uncertain nonlinear multiagent systems under directed graphs. The followers are governed by nonlinear systems with unknown dynamics while the multiple leaders are neighbors of a subset of the followers. Fuzzy logic systems (FLSs are used to identify the unknown dynamics and a distributed state feedback containment control protocol is proposed. This result is extended to the output feedback case, where observers are designed to estimate the unmeasurable states. Then, an output feedback containment control scheme is presented. The developed state feedback and output feedback containment controllers guarantee that the states of all followers converge to the convex hull spanned by the dynamic leaders. Based on Lyapunov stability theory, it is proved that the containment control errors are uniformly ultimately bounded (UUB. An example is provided to show the effectiveness of the proposed control method.
Expert systems for adaptive control of large space structures
Gartrell, Charles F.
1988-01-01
It is expected that space systems for the future will evolve to structures of unprecedented size with associated extreme control requirements. A method is necessary that is sufficiently general to initiate stable control of a vehicle and subsequently learn the true nature of the structure. It is suggested that a suitable constructed expert system (ES) would be capable of learning by appending observations to a knowledge base. To verify that an ES can control a large space structure, numerical simulations of a simple structure subjected to periodic vibrations and the performance of a classical controllers were performed. The ES was then exercised to show its ability to truthfully mimic nominal control and to demonstrate its superiority to the classical controller, given sensor failures. An ES generating software package, The Intelligent Machine Model, was employed. It uses the pattern matching technique. Results of this program are discussed.
Parallel evolution controlled by adaptation and covariation in ammonoid cephalopods
Directory of Open Access Journals (Sweden)
Klug Christian
2011-04-01
Full Text Available Abstract Background A major goal in evolutionary biology is to understand the processes that shape the evolutionary trajectory of clades. The repeated and similar large-scale morphological evolutionary trends of distinct lineages suggest that adaptation by means of natural selection (functional constraints is the major cause of parallel evolution, a very common phenomenon in extinct and extant lineages. However, parallel evolution can result from other processes, which are usually ignored or difficult to identify, such as developmental constraints. Hence, understanding the underlying processes of parallel evolution still requires further research. Results Herein, we present a possible case of parallel evolution between two ammonoid lineages (Auguritidae and Pinacitidae of Early-Middle Devonian age (405-395 Ma, which are extinct cephalopods with an external, chambered shell. In time and through phylogenetic order of appearance, both lineages display a morphological shift toward more involute coiling (i.e. more tightly coiled whorls, larger adult body size, more complex suture line (the folded walls separating the gas-filled buoyancy-chambers, and the development of an umbilical lid (a very peculiar extension of the lateral shell wall covering the umbilicus in the most derived taxa. Increased involution toward shells with closed umbilicus has been demonstrated to reflect improved hydrodynamic properties of the shell and thus likely results from similar natural selection pressures. The peculiar umbilical lid might have also added to the improvement of the hydrodynamic properties of the shell. Finally, increasing complexity of suture lines likely results from covariation induced by trends of increasing adult size and whorl overlap given the morphogenetic properties of the suture. Conclusions The morphological evolution of these two Devonian ammonoid lineages follows a near parallel evolutionary path for some important shell characters during several
Parallel evolution controlled by adaptation and covariation in ammonoid cephalopods.
Monnet, Claude; De Baets, Kenneth; Klug, Christian
2011-04-29
A major goal in evolutionary biology is to understand the processes that shape the evolutionary trajectory of clades. The repeated and similar large-scale morphological evolutionary trends of distinct lineages suggest that adaptation by means of natural selection (functional constraints) is the major cause of parallel evolution, a very common phenomenon in extinct and extant lineages. However, parallel evolution can result from other processes, which are usually ignored or difficult to identify, such as developmental constraints. Hence, understanding the underlying processes of parallel evolution still requires further research. Herein, we present a possible case of parallel evolution between two ammonoid lineages (Auguritidae and Pinacitidae) of Early-Middle Devonian age (405-395 Ma), which are extinct cephalopods with an external, chambered shell. In time and through phylogenetic order of appearance, both lineages display a morphological shift toward more involute coiling (i.e. more tightly coiled whorls), larger adult body size, more complex suture line (the folded walls separating the gas-filled buoyancy-chambers), and the development of an umbilical lid (a very peculiar extension of the lateral shell wall covering the umbilicus) in the most derived taxa. Increased involution toward shells with closed umbilicus has been demonstrated to reflect improved hydrodynamic properties of the shell and thus likely results from similar natural selection pressures. The peculiar umbilical lid might have also added to the improvement of the hydrodynamic properties of the shell. Finally, increasing complexity of suture lines likely results from covariation induced by trends of increasing adult size and whorl overlap given the morphogenetic properties of the suture. The morphological evolution of these two Devonian ammonoid lineages follows a near parallel evolutionary path for some important shell characters during several million years and through their phylogeny. Evolution
The Adaptive Neural Network Control of Quadrotor Helicopter
Directory of Open Access Journals (Sweden)
A. S. Yushenko
2017-01-01
Full Text Available The current steady-rising interest in using the unmanned multi-rotor aerial vehicles (UMAV designed to solve a wide range of tasks is, mainly, due to their simple design and high weight-carrying capacity as compared to classical helicopter options. Unfortunately, to solve a problem of multi-copter control is complicated because of essential nonlinearity and environmental perturbations. The most widely spread PID controllers and linear-quadratic regulators do not quite well cope with this task. The need arises for the prompt adjustment of PID controller coefficients in the course of operation or their complete re-tuning in cases of changing parameters of the control object.One of the control methods under changing conditions is the use of the sliding mode. This technology enables us to reach the stabilization and proper operation of the controlled system even under accidental external exposures and when there is a lack of the reasonably accurate mathematical model of the control object. The sliding principle is to ensure the system motion in the immediate vicinity of the sliding surface in the phase space. On the other hand, the sliding mode has some essential disadvantages. The most significant one is the high-frequency jitter of the system near the sliding surface. The sliding mode also implies the complete knowledge of the system dynamics. Various methods have been proposed to eliminate these drawbacks. For example, A.G. Aissaoui’s, H. Abid’s and M. Abid’s paper describes the application of fuzzy logic to control a drive and in Lon-Chen Hung’s and Hung-Yuan Chung’s paper an artificial neural network is used for the manipulator control.This paper presents a method of the quad-copter control with the aid of a neural network controller. This method enables us to control the system without a priori information on parameters of the dynamic model of the controlled object. The main neural network is a MIMO (“Multiple Input Multiple
Modeling and adaptive pinning synchronization control for a chaotic-motion motor in complex network
Zhu, Darui; Liu, Chongxin; Yan, Bingnan
2014-01-01
We introduce a chaos model for a permanent-magnet synchronous motor and construct a coupled chaotic motor in a complex dynamic network using the Newman-Watts small-world network algorithm. We apply adaptive pinning control theory for complex networks to obtain suitable adaptive feedback gain and the number of nodes to be pinned. Nodes of low degree are pinned to realize global asymptotic synchronization in the complex network. The proposed adaptive pinning controller is added to the complex motor network for simulation and verification.
A Static Control Algorithm for Adaptive Beam String Structures Based on Minimal Displacement
Directory of Open Access Journals (Sweden)
Yanbin Shen
2013-01-01
Full Text Available The beam string structure (BSS is a type of prestressed structure and has been widely used in large span structures nowadays. The adaptive BSS is a typical smart structure that can optimize the working status itself by controlling the length of active struts via certain control device. The control device commonly consists of actuators in all struts and sensors on the beam. The key point of the control process is to determine the length adjustment values of actuators according to the data obtained by preinstalled sensors. In this paper, a static control algorithm for adaptive BSS has been presented for the adjustment solution. To begin with, an optimization model of adaptive BSS with multiple active struts is established, which uses a sensitivity analysis method. Next, a linear displacement control process is presented, and the adjustment values of struts are calculated by a simulated annealing algorithm. A nonlinear iteration procedure is used afterwards to calibrate the results of linear calculation. Finally, an example of adaptive BSS under different external loads is carried out to verify the feasibility and accuracy of the algorithm. And the results also show that the adaptive BSS has much better adaptivity and capability than the noncontrolled BSS.
Adaptive Finite-Time Controller Design for T-S Fuzzy Systems.
Li, Yue; Liu, Lu; Feng, Gang
2017-09-01
This paper studies the adaptive finite-time stabilization problem for a class of nonlinear systems described by Takagi-Sugeno (T-S) fuzzy dynamic models with parametric uncertainties. A novel adaptive state feedback control scheme for the T-S fuzzy systems is proposed, and the scheme is developed based on finite-time Lyapunov theorem and adaptive backstepping-like method. Augmented dynamics are introduced in the design of finite-time stabilization controllers to construct suitable finite-time Lyapunov functions. It is shown that finite-time convergence of the closed-loop adaptive control system can be achieved, and the potential controller singularity problem caused by the augmented dynamics can be avoided. In addition, constructive procedures to obtain such an adaptive finite-time controller are given. Convergence time as a transient performance specification is also taken into account, and a finite upper bound on the convergence time is estimated. Finally, two numerical examples are provided to illustrate the effectiveness and practicality of the proposed adaptive control approach.
Wheeled vehicle deceleration as estimation parameter of adaptive brake control system state
Directory of Open Access Journals (Sweden)
Turenko A.
2012-06-01
Full Text Available The method of stability estimation of adaptive control system with signal adjustment based on Lyapunov’s direct method that allows to take into account the nonstationarity of the basic system and non-linearity in the form of limitation on control action restriction as well as error control is stated.
DEFF Research Database (Denmark)
El Fadil, H.; Giri, F.; Guerrero, Josep M.
2013-01-01
This paper deals with the problem of controlling energy generation systems including fuel cells (FCs) and interleaved boost power converters. The proposed nonlinear adaptive controller is designed using sliding mode control (SMC) technique based on the system nonlinear model. The latter accounts...
A Dynamic Geocast Solution to Support Cooperative Adaptive Cruise Control (CACC) Merging
Klein Wolterink, W.; Karagiannis, Georgios; Heijenk, Geert
2010-01-01
Cooperative Adaptive Cruise Control (CACC) is a type of cruise control in which the speed of a vehicle is controlled based on wireless communication between vehicles. In this paper we tackle the communication needed in case of fully automatic CACC merging at a junction. The first contribution of our
DEFF Research Database (Denmark)
Sun, Bo; Trintis, Ionut; Munk-Nielsen, Stig
2016-01-01
This paper presents an adaptive dc-link voltage controller for the purpose of decreasing the operating dc-link voltage in a back-to-back converter system. An outer loop to control the maximum modulation (Mmax) index is added to the conventional dc-link voltage controller, and hence the system can...