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Adaptive Control (adaptive + control)

Distribution by Scientific Domains
Engineering92%
4 Other Domains8%

Kinds of Adaptive Control

  • model reference adaptive control
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  • reference adaptive control
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  • robust adaptive control
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    Terms modified by Adaptive Control

  • adaptive control algorithm
  • adaptive control design
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  • adaptive control law
  • adaptive control scheme
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  • adaptive control system
  • adaptive control techniques
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    Selected Abstracts

    DIRECT ADAPTIVE CONTROL FOR NONLINEAR MATRIX SECOND-ORDER SYSTEMS WITH TIME-VARYING AND SIGN-INDEFINITE DAMPING AND STIFFNESS OPERATORS

    ASIAN JOURNAL OF CONTROL, Issue 1 2007
    Wassim M. Haddad
    ABSTRACT A direct adaptive control framework for a class of nonlinear matrix second-order systems with time-varying and sign-indefinite damping and stiffness operators is developed. The proposed framework guarantees global asymptotic stability of the closed-loop system states associated with the plant dynamics without requiring any knowledge of the system nonlinearities other than the assumption that they are continuous and bounded. The proposed adaptive control approach is used to design adaptive controllers for suppressing thermoacoustic oscillations in combustion chambers. [source]

    Adaptive Control For Robotic Manipulators Executing Multilateral Constrained Task

    ASIAN JOURNAL OF CONTROL, Issue 1 2003
    Haruhisa Kawasaki
    ABSTRACT This paper presents a model-based adaptive control in task coordinates for robotic manipulators executing multilateral constrained tasks The controller works based on the concept of orthogonality between force and motion in the subspaces derived from the constraints. The control gains are independently adjustable in each subspace. The friction force, depending on the contact force, is compensated adaptively. Asymptotic convergence for both force and motion tracking errors is guaranteed by the Lyapunov-Like Lemma. Experimental results obtained using a 3 D.O.F. robot are given. [source]

    PID-Augmented Adaptive Control of a Gyro Mirror Los System

    ASIAN JOURNAL OF CONTROL, Issue 2 2002
    K.K. Tan
    ABSTRACT In this paper, a composite control scheme using a synergy of PID and adaptive control is proposed. The adaptive control component provides an adaptive feedforward control signal, while the PID component provides feedback control for robustness against modeling errors in the feedforward control design. The PID control can be automatically tuned using a relay. The control scheme developed is relevant to a large class of nonlinear servo-mechanical systems, although in this paper, it is specifically implemented and demonstrated on a gyro mirror line-of-sight (LOS) system. [source]

    Human Symbol Manipulation Within an Integrated Cognitive Architecture

    COGNITIVE SCIENCE - A MULTIDISCIPLINARY JOURNAL, Issue 3 2005
    John R. Anderson
    Abstract This article describes the Adaptive Control of Thought,Rational (ACT,R) cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998) and its detailed application to the learning of algebraic symbol manipulation. The theory is applied to modeling the data from a study by Qin, Anderson, Silk, Stenger, & Carter (2004) in which children learn to solve linear equations and perfect their skills over a 6-day period. Functional MRI data show that: (a) a motor region tracks the output of equation solutions, (b) a prefrontal region tracks the retrieval of declarative information, (c) a parietal region tracks the transformation of mental representations of the equation, (d) an anterior cingulate region tracks the setting of goal information to control the information flow, and (e) a caudate region tracks the firing of productions in the ACT,R model. The article concludes with an architectural comparison of the competence children display in this task and the competence that monkeys have shown in tasks that require manipulations of sequences of elements. [source]

    An Activation-Based Model of Sentence Processing as Skilled Memory Retrieval

    COGNITIVE SCIENCE - A MULTIDISCIPLINARY JOURNAL, Issue 3 2005
    Richard L. Lewis
    Abstract We present a detailed process theory of the moment-by-moment working-memory retrievals and associated control structure that subserve sentence comprehension. The theory is derived from the application of independently motivated principles of memory and cognitive skill to the specialized task of sentence parsing. The resulting theory construes sentence processing as a series of skilled associative memory retrievals modulated by similarity-based interference and fluctuating activation. The cognitive principles are formalized in computational form in the Adaptive Control of Thought,Rational (ACT,R) architecture, and our process model is realized in ACT,R. We present the results of 6 sets of simulations: 5 simulation sets provide quantitative accounts of the effects of length and structural interference on both unambiguous and garden-path structures. A final simulation set provides a graded taxonomy of double center embeddings ranging from relatively easy to extremely difficult. The explanation of center-embedding difficulty is a novel one that derives from the model' complete reliance on discriminating retrieval cues in the absence of an explicit representation of serial order information. All fits were obtained with only 1 free scaling parameter fixed across the simulations; all other parameters were ACT,R defaults. The modeling results support the hypothesis that fluctuating activation and similarity-based interference are the key factors shaping working memory in sentence processing. We contrast the theory and empirical predictions with several related accounts of sentence-processing complexity. [source]

    Adaptive control of stochastic nonlinear systems with uncontrollable linearization

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 7 2009
    Wang Qiang-de
    Abstract For a class of high-order stochastic nonlinear systems with uncontrollable linearization, this paper investigates the problem of adaptive global stability in probability. By using the tool of adaptive adding a power integrator, a feedback domination design approach is presented and a smooth controller is constructed. The closed-loop stochastic system is proved to be globally stable in probability and the states can be regulated to the origin almost surely. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Adaptive control and signal processing literature survey (No. 12)

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2009
    Article first published online: 8 MAY 200
    First page of article [source]

    Adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 1 2009
    Alexander Leonessa
    Abstract A direct adaptive nonlinear tracking control framework for multivariable nonlinear uncertain systems with actuator amplitude and rate saturation constraints is developed. To guarantee asymptotic stability of the closed-loop tracking error dynamics in the face of amplitude and rate saturation constraints, the control signal to a given reference (governor or supervisor) system is modified to effectively robustify the error dynamics to the saturation constraints. Illustrative numerical examples are provided to demonstrate the efficacy of the proposed approach. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Adaptive control for a radio-controlled helicopter in a vertical flying stand

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2004
    Alejandro Dzul
    Abstract In this paper, we focus on the design and implementation of a controller for a two degree-of-freedom system. This system is composed of a small-scale helicopter which is mounted on a vertical platform. The model is based on Lagrangian formulation and the controller is obtained by classical pole-placement techniques for the yaw dynamics and adaptive pole-placement for the altitude dynamics. Experimental results show the performance of such a controller. Copyright © 2004 John Wiley & Sons, Ltd. [source]

    Adaptive control for non-negative and compartmental dynamical systems with applications to general anesthesia

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 3 2003
    Wassim M. Haddad
    Abstract Non-negative and compartmental dynamical system models are composed of homogeneous interconnected subsystems or compartments which exchange variable non-negative quantities of material with conservation laws describing transfer, accumulation, and elimination between the compartments and the environment. These models are widespread in biological and physiological sciences and play a key role in understanding these processes. In this paper, we develop a direct adaptive control framework for linear uncertain non-negative and compartmental systems. The proposed framework is Lyapunov-based and guarantees partial asymptotic set-point regulation; that is, asymptotic set-point stability with respect to part of the closed-loop system states associated with the plant. In addition, the adaptive controller guarantees that the physical system states remain in the non-negative orthant of the state space. Finally, a numerical example involving the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for non-cardiac surgery is provided to demonstrate the efficacy of the proposed approach. Copyright © 2003 John Wiley & Sons, Ltd. [source]

    Adaptive control using multiple models, switching and tuning

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 2 2003
    Kumpati S. Narendra
    Abstract The past decade has witnessed a great deal of interest in both the theory and practice of adaptive control using multiple models, switching, and tuning. The general approach was introduced in the early 1990s to cope with large and rapidly varying parameters in control systems. During the following years, detailed mathematical analyses of special classes of systems were carried out. Considerable empirical evidence was also collected to demonstrate the practical viability of the methods proposed. This paper attempts to review critically the stability questions that arise in the study of such systems, describes recent extensions of the approach to non-linear adaptive control, and discuss briefly promising new areas of research, particularly related to the location of models. Copyright © 2003 John Wiley & Sons, Ltd. [source]

    Adaptive control of continuous time stochastic systems

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2002
    T.E. Duncan
    Abstract Some problems and solutions of adaptive control problems for continuous time stochastic systems are described. A solution is given to the adaptive linear quadratic Gaussian control problem under the natural assumptions of controllability and observability. The effects of sampling and numerical differentiation on a least-squares estimation algorithm are described. Adaptive control problems for non-linear stochastic systems and linear stochastic distributed parameter systems are briefly described. Copyright © 2002 John Wiley & Sons, Ltd. [source]

    Adaptive control of Burgers' equation with unknown viscosity

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 7 2001
    Wei-Jiu Liu
    Abstract In this paper, we propose a fortified boundary control law and an adaptation law for Burgers' equation with unknown viscosity, where no a priori knowledge of a lower bound on viscosity is needed. This control law is decentralized, i.e., implementable without the need for central computer and wiring. Using the Lyapunov method, we prove that the closed-loop system, including the parameter estimator as a dynamic component, is globally H1 stable and well posed. Furthermore, we show that the state of the system is regulated to zero by developing an alternative to Barbalat's Lemma which cannot be used in the present situation. Copyright © 2001 John Wiley & Sons, Ltd. [source]

    Adaptive control of systems with actuator failures, Gang Tao, Shuhao Chen, Xidong Tang and Suresh M. Joshi, Springer: London, U.K., 2004, 299pp.

    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 11 2005
    8523, ISBN:
    No Abstracts [source]

    Adaptive power control for satellite to ground laser communication

    INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING, Issue 4 2007
    Michael Gubergrits
    Abstract We develop an adaptive power control algorithm to facilitate satellite to ground laser communication through turbulence fading channels. Adaptive control is a powerful tool that improves energetic gain of the satellite laser. We use discrete laser transmitter intensity levels in our control algorithm. A novel recursive technique defines optimal laser transmitting intensity levels so that the laser-transmitted power is adapted according to instant changes of the signal-to-noise ratio caused by channel fading. The algorithm's performance is first investigated in a general form suitable for any channel fading statistics. Then it is specified for a typical lognormal fading channel. The results indicate an improvement of up to 10dB in energetic gain. Copyright © 2007 John Wiley & Sons, Ltd. [source]

    Adaptive control for edge alignment in polyester film processing

    ADVANCES IN POLYMER TECHNOLOGY, Issue 3 2007
    Chang-Chiun Huang
    Abstract Edge alignment of polyester (PET) films is important for achieving product quality and processing speed in winding, coating, drying, and other processes. The edge alignment can be achieved by lateral deflection control, provided that the film tension and transport speed are even at desired values. This article aims to correct the lateral deflection of films by designing robust controllers to swivel the guiding rollers and to maintain even tension and speed at target levels. The self-tuning neuro-proportional integral derivative controller and adaptive high-gain output feedback controller are adopted to guide the lateral deflection so that the film aligns at the desired position. A control scheme, neuron controller by associative learning, is used for maintaining tension and speed control. These strategies are applied to a simplified PET film processing system. The experimental results demonstrate that in our setup, the control schemes can effectively alleviate not only the lateral deflection but also the tension and speed fluctuation at target levels. © 2008 Wiley Periodicals, Inc. Adv Polym Techn 26:153,162, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.20096 [source]

    PID adaptive control of incremental and arclength continuation in nonlinear applications

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2009
    A. M. P. Valli
    Abstract A proportional-integral-derivative (PID) control approach is developed, implemented and investigated numerically in conjunction with continuation techniques for nonlinear problems. The associated algorithm uses PID control to adapt parameter stepsize for branch,following strategies such as those applicable to turning point and bifurcation problems. As representative continuation strategies, incremental Newton, Euler,Newton and pseudo-arclength continuation techniques are considered. Supporting numerical experiments are conducted for finite element simulation of the ,driven cavity' Navier,Stokes benchmark over a range in Reynolds number, the classical Bratu turning point problem over a reaction parameter range, and for coupled fluid flow and heat transfer over a range in Rayleigh number. Computational performance using PID stepsize control in conjunction with inexact Newton,Krylov solution for coupled flow and heat transfer is also examined for a 3D test case. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    Output feedback stabilizability and passivity in nonstationary and nonlinear systems,

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 7 2010
    Itzhak Barkana
    Abstract Passivity properties and passivity conditions have been shown to be very important for the stability of various methodologies of control with uncertainty in linear-time-invariant (LTI) systems. Many publications have defined the conditions that allow LTI systems to become strictly passive (and their transfer function strictly positive real) via constant or dynamic output feedback. As beyond the usual uncertainty, real-world systems are not necessarily invariant, this paper expands the applicability of previous results to nonstationary and nonlinear systems. The paper first reviews a few pole,zero dynamics definitions in nonstationary systems and relates them to stability and passivity of the systems. The paper then finds the sufficient conditions that allow nonstationary systems to become stable and strictly passive via static or dynamic output feedback. Applications in robotics and adaptive control are also presented. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    Neural network-based adaptive attitude tracking control for flexible spacecraft with unknown high-frequency gain

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2010
    Qinglei Hu
    Abstract Adaptive control design using neural networks (a) is investigated for attitude tracking and vibration stabilization of a flexible spacecraft, which is operated at highly nonlinear dynamic regimes. The spacecraft considered consists of a rigid body and two flexible appendages, and it is assumed that the system parameters are unknown and the truncated model of the spacecraft has finite but arbitrary dimension as well, for the purpose of design. Based on this nonlinear model, the derivation of an adaptive control law using neural networks (NNs) is treated, when the dynamics of unstructured and state-dependent nonlinear function are completely unknown. A radial basis function network that is used here for synthesizing the controller and adaptive mechanisms is derived for adjusting the parameters of the network and estimating the unknown parameters. In this derivation, the Nussbaum gain technique is also employed to relax the sign assumption for the high-frequency gain for the neural adaptive control. Moreover, systematic design procedure is developed for the synthesis of adaptive NN tracking control with L2 -gain performance. The resulting closed-loop system is proven to be globally stable by Lyapunov's theory and the effect of the external disturbances and elastic vibrations on the tracking error can be attenuated to the prescribed level by appropriately choosing the design parameters. Numerical simulations are performed to show that attitude tracking control and vibration suppression are accomplished in spite of the presence of disturbance torque/parameter uncertainty. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    Indirect adaptive control of a class of marine vehicles

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 4 2010
    Yannick Morel
    Abstract A nonlinear adaptive framework for bounded-error tracking control of a class of non-minimum phase marine vehicles is presented. The control algorithm relies on a special set of tracking errors to achieve satisfactory tracking performance while guaranteeing stable internal dynamics. First, the design of a model-based nonlinear control law, guaranteeing asymptotic stability of the error dynamics, is presented. This control algorithm solves the tracking problem for the considered class of marine vehicles, assuming full knowledge of the system model. Then, the analysis of the zero-dynamics is carried out, which illustrates the efficacy of the chosen set of tracking errors in stabilizing the internal dynamics. Finally, an indirect adaptive technique, relying on a partial state predictor, is used to address parametric uncertainties in the model. The resulting adaptive control algorithm guarantees Lyapunov stability of the errors and parameter estimates, as well as asymptotic convergence of the errors to zero. Numerical simulations illustrate the performance of the adaptive algorithm. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    Improved adaptive control for the discrete-time parametric-strict-feedback form

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 12 2009
    Graciela Adriana González
    Abstract Adaptive control design for a class of single-input single-output nonlinear discrete-time systems in parametric-strict-feedback form is re-visited. No growth restrictions are assumed on the nonlinearities. The control objective is to achieve tracking of a reference signal. As usual, the algorithm derives from the combination of a control law and a parameter estimator (certainty equivalence principle). The parameter estimator strongly lies on the regressor subspace identification by means of an orthogonalization process. Certain drawbacks of previous schemes are analyzed. Several modifications on them are considered to improve the algorithm complexity, control performance and numerical stability. As a result, an alternative control scheme is proposed. When applied to the proposed class of systems, global boundedness and convergence remain as achieved objectives while improving the performance issues of previous schemes. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    State-feedback adaptive tracking of linear systems with input and state delays

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2009
    Boris Mirkin
    Abstract A state-feedback Lyapunov-based design of direct model reference adaptive control is developed for a class of linear systems with input and state delays based only on lumped delays without so-called distributed-delay blocks. The design procedure is based on the concept of reference trajectory prediction, and on the formulation of an augmented error. We propose a controller parametrization that attempts to anticipate the future states. An appropriate Lyapunov,Krasovskii type functional is found for the design and the stability analysis. A simulation example illustrates the new controller. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Neural network-based adaptive control of piezoelectric actuators with unknown hysteresis

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 1 2009
    Wen-Fang Xie
    Abstract This paper proposes a neural network (NN)-based adaptive control of piezoelectric actuators with unknown hysteresis. Based on the classical Duhem model described by a differential equation, the explicit solution to the equation is explored and a new hysteresis model is constructed as a linear model in series with a piecewise continuous nonlinear function. An NN-based dynamic pre-inversion compensator is designed to cancel out the effect of the hysteresis. With the incorporation of the pre-inversion compensator, an adaptive control scheme is proposed to have the position of the piezoelectric actuator track the desired trajectory. This paper has three distinct features. First, it applies the NN to online approximate complicated piecewise continuous unknown nonlinear functions in the explicit solution to Duhem model. Second, an observer is designed to estimate the output of hysteresis of piezoelectric actuator based on the system input and output. Third, the stability of the controlled piezoelectric actuator with the observer is guaranteed. Simulation results for a practical system validate the effectiveness of the proposed method in this paper. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Predictive adaptive control of plants with online structural changes based on multiple models

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2008
    J. M. Lourenço
    Abstract The objective of this paper is to present a new algorithm to improve the adaptation rate of a predictive adaptive controller. For that sake, the possible plant dynamic outcomes are covered by a bank of models. Each model is used to re-initialize the adaptive controller every time there is a large change in dynamics. The contribution of the paper consists in the development of a procedure that includes additional models in the bank when found suitable according to defined criteria. The algorithm is demonstrated in a benchmark problem consisting of the position control of two masses coupled by a spring of varying stiffness. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Passification-based adaptive control of linear systems: Robustness issues

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2008
    Dimitri Peaucelle
    Abstract Passivity is a widely used concept in control theory having led to many significant results. This paper concentrates on one characteristic of passivity, namely passification-based adaptive control. This concept applies to multi-input multi-output systems for which exists a combination of outputs that renders the open-loop system hyper-minimum phase. Under such assumptions, the system may be passified by both high-gain static output feedback and by a particular adaptive control algorithm. This last control law is modified here to guarantee its coefficients to be bounded. The contribution of this paper is to investigate its robustness with respect to parametric uncertainty. Time response characteristics are illustrated on examples including realistic situations with noisy output and saturated input. Theoretical results are formulated as linear matrix inequalities and can hence be readily solved with semi-definite programming solvers. Copyright © 2007 John Wiley & Sons, Ltd. [source]

    Finite-model adaptive control using an LS-like algorithm,

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2007
    Hongbin Ma
    Abstract Adaptive control problem of a class of discrete-time nonlinear uncertain systems, of which the internal uncertainty can be characterized by a finite set of functions, is formulated and studied by using an least squares (LS)-like algorithm to design the feedback control law. For the finite-model adaptive control problem, this algorithm is proposed as an extension of counterpart of traditional LS algorithm. Stability in sense of pth mean for the closed-loop system is proved under a so-called linear growth assumption, which is shown to be necessary in general by a counter-example constructed in this paper. The main results have been also applied to parametric cases, which demonstrate how to bridge the non-parametric case and parametric case. Copyright © 2006 John Wiley & Sons, Ltd. [source]

    Issues, progress and new results in robust adaptive control,

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2006
    Sajjad Fekri
    Abstract We overview recent progress in the field of robust adaptive control with special emphasis on methodologies that use multiple-model architectures. We argue that the selection of the number of models, estimators and compensators in such architectures must be based on a precise definition of the robust performance requirements. We illustrate some of the concepts and outstanding issues by presenting a new methodology that blends robust non-adaptive mixed µ-synthesis designs and stochastic hypothesis-testing concepts leading to the so-called robust multiple model adaptive control (RMMAC) architecture. A numerical example is used to illustrate the RMMAC design methodology, as well as its strengths and potential shortcomings. The later motivated us to develop a variant architecture, denoted as RMMAC/XI, that can be effectively used in highly uncertain exogenous plant disturbance environments. Copyright © 2006 John Wiley & Sons, Ltd. [source]

    Model reference adaptive iterative learning control for linear systems

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 9 2006
    A. Tayebi
    Abstract In this paper, we propose a model reference adaptive control (MRAC) strategy for continuous-time single-input single-output (SISO) linear time-invariant (LTI) systems with unknown parameters, performing repetitive tasks. This is achieved through the introduction of a discrete-type parametric adaptation law in the ,iteration domain', which is directly obtained from the continuous-time parametric adaptation law used in standard MRAC schemes. In fact, at the first iteration, we apply a standard MRAC to the system under consideration, while for the subsequent iterations, the parameters are appropriately updated along the iteration-axis, in order to enhance the tracking performance from iteration to iteration. This approach is referred to as the model reference adaptive iterative learning control (MRAILC). In the case of systems with relative degree one, we obtain a pointwise convergence of the tracking error to zero, over the whole finite time interval, when the number of iterations tends to infinity. In the general case, i.e. systems with arbitrary relative degree, we show that the tracking error converges to a prescribed small domain around zero, over the whole finite time interval, when the number of iterations tends to infinity. It is worth noting that this approach allows: (1) to extend existing MRAC schemes, in a straightforward manner, to repetitive systems; (2) to avoid the use of the output time derivatives, which are generally required in traditional iterative learning control (ILC) strategies dealing with systems with high relative degree; (3) to handle systems with multiple tracking objectives (i.e. the desired trajectory can be iteration-varying). Finally, simulation results are carried out to support the theoretical development. Copyright © 2006 John Wiley & Sons, Ltd. [source]

    Output-feedback co-ordinated decentralized adaptive tracking: The case of MIMO subsystems with delayed interconnections

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2005
    Boris M. Mirkin
    Abstract Exact decentralized output-feedback Lyapunov-based designs of direct model reference adaptive control (MRAC) for linear interconnected delay systems with MIMO subsystems are introduced. The design process uses a co-ordinated decentralized structure of adaptive control with reference model co-ordination which requires an exchange of signals between the different reference models. It is shown that in the framework of the reference model co-ordination zero residual tracking error is possible, exactly as in the case with SISO subsystems. We develop decentralized MRAC on the base of a priori information about only the local subsystems gain frequency matrices without additional a priori knowledge about the full system gain frequency matrix. To achieve a better adaptation performance we propose proportional, integral time-delayed adaptation laws. The appropriate Lyapunov,Krasovskii type functional is suggested to design the update mechanism for the controller parameters, and in order to prove stability. Two different adaptive DMRAC schemes are proposed, being the first asymptotic exact zero tracking results for linear interconnected delay systems with MIMO subsystems. Copyright © 2005 John Wiley & Sons, Ltd. [source]

    Hybrid adaptive control for non-linear uncertain impulsive dynamical systems

    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2005
    Wassim M. Haddad
    Abstract A direct hybrid adaptive control framework for non-linear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. Furthermore, hybrid adaptive controllers guaranteeing attraction of the closed-loop system plant states are also developed. Finally, two numerical examples are provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach. Copyright © 2004 John Wiley & Sons, Ltd. [source]