Robust Inversion Based Fault Estimation for Discrete-Time LPV Systems

Kulcsár, Balázs; Verhaegen, Michel

doi:10.1109/tac.2011.2176160

Cited by 42 publications

(31 citation statements)

References 22 publications

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“…Up to date, considerable research attention has been devoted to the theoretical research on the fault estimation problem, and a great number of fault estimation approaches have been proposed in existing literature, see e.g. [6,[11][12][13]15,17,19,27,30] and the references therein. For example, in [11,12,19,29], the problems of fault estimation have been investigated by applying adaptive fault diagnosis observers that can improve the rapidity of fault estimation.…”

Section: Introductionmentioning

confidence: 99%

Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems

et al. 2014

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This paper is concerned with the finite-horizon estimation problem of randomly occurring faults for a class of nonlinear systems whose parameters are all time-varying. The faults are assumed to occur in a random way governed by two sets of Bernoulli distributed white sequences. The stochastic nonlinearities entering the system are described by statistical means that can cover several classes of well-studied nonlinearities. The aim of the problem is to estimate the random faults, over a finite horizon, such that the influence from the exogenous disturbances onto the estimation errors is attenuated at the given level quantified by a H∞-norm in the mean square sense. By using the completing squares method and stochastic analysis techniques, necessary and sufficient conditions are established for the existence of the desired finite-horizon H∞ fault estimator whose parameters are then obtained by solving coupled backward recursive Riccati difference equations (RDEs). A simulation example is utilized to illustrate the effectiveness of the proposed fault estimation method.

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Section: Introductionmentioning

confidence: 99%

Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems

et al. 2014

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“…Generally, the uncertainty is employed to represent the inaccurate parameters and described via a time-varying function. In the literatures [1][2][3][4][5][6][7][8][9], the robust control methods have been proposed to design the controller such that stability of uncertain systems is guaranteed. Among of the literatures [1][2][3], the uncertainty is constructed via specific function to simulate the parameters varying.…”

Section: Introductionmentioning

confidence: 99%

“…And, the uncertainty is bounded with determined norm. Otherwise, the LPV systems [4][5][6][7][8][9][10] have been proposed to describe the uncertain system via combining several linear subsystems and weighting functions. The LPV system is one of oncoming paradigm used to strictly capture the behavior of uncertain time-variation of parameters of systems.…”

Section: Introductionmentioning

confidence: 99%

Gain-scheduled controller design for discrete-time Linear Parameter Varying systems with multiplicative noises

Chen

2015

Int. J. Control Autom. Syst.

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In this paper, two technologies to design gain-scheduled controller are proposed for discretetime Linear Parameter Varying (LPV) systems with multiplicative noises. In the considered systems, the time-varying parameters are proposed to describe the uncertainties. And, the added multiplicative noise term is applied to describe the stochastic behaviors of the system. Furthermore, the gainscheduled design scheme is applied to deal with the stabilization problem of the LPV systems with multiplicative noises. Through the parameter-independent and parameter-dependent Lyapunov functions, the corresponding sufficient conditions are derived to discuss the stability and stabilization problems of the system. In order to apply the convex optimization algorithm, the derived sufficient conditions are converted into Linear Matrix Inequality (LMI) problems. Based on the proposed design technologies, gain-scheduled controllers are designed such that the considered system is asymptotically stable in the mean square. Finally, two numerical examples are applied to demonstrate the application and effectiveness of the proposed design technologies of this paper.

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“…For LPV discrete-time systems, fault reconstruction via a robust dynamic inversion is proposed in Ref. [13] where a Luenberger observer is synthesized. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Fault Reconstruction and Accommodation in Linear Parameter-Varying Systems via Learning Unknown-Input Observers

Jia

Chen²,

Zhang

et al. 2015

Journal of Dynamic Systems, Measurement, and Control

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This paper addresses the problem of observer-based fault reconstruction and accommodation for polytopic linear parameter-varying (LPV) systems. A polytopic representation of an LPV system subject to actuator faults and external disturbances is first established; then, a novel polytopic learning unknown-input observer (LUIO) is constructed for simultaneous state estimation and robust fault reconstruction. The stability of the presented LUIO is proved using Lyapunov stability theory together with H 1 techniques. Further, using reconstructed fault information, a reconfigurable fault-tolerant controller is designed to compensate for the influence of actuator faults by stabilizing the closed-loop system. At last, an aircraft example is employed to illustrate the effectiveness and practicability of the proposed techniques.

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Robust Inversion Based Fault Estimation for Discrete-Time LPV Systems

Cited by 42 publications

References 22 publications

Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems

Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems

Gain-scheduled controller design for discrete-time Linear Parameter Varying systems with multiplicative noises

Fault Reconstruction and Accommodation in Linear Parameter-Varying Systems via Learning Unknown-Input Observers

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