4.6 Article

Decentralized adaptive fuzzy fault-tolerant tracking control of large-scale nonlinear systems with actuator failures

Journal

NEUROCOMPUTING
Volume 179, Issue -, Pages 307-317

Publisher

ELSEVIER
DOI: 10.1016/j.neucom.2015.11.086

Keywords

Decentralized adaptive control; Fault-tolerant control; Fuzzy logic systems (FLSs); Non-affine and nonlinear system; Asymptotic

Funding

  1. National Natural Science of China [61273148, 61420106016, 61273155, 61322312]
  2. Foundation for the Author of National Excellent Doctoral Dissertation of PR China [201157]
  3. Fok Ying Tung Education Foundation [141060]
  4. State Key Laboratory of Synthetical Automation for Process Industries [2013ZCX01-01, 2013ZCX01-02]

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This study is concerned with the problem of decentralized adaptive fault-tolerant control for a class of large-scale non-affine and nonlinear systems with external disturbances and actuator failures including loss of effectiveness and bias. Based on fuzzy logic systems (FLSs) to approximate the appropriate nonlinear functions, a novel decentralized adaptive fuzzy fault-tolerant control scheme is developed via direct adaptive control technique. To tackle the non-affine term with actuator failures, with the help of a non-affine compensation term, the corresponding adaptive mechanism that depends on the unknown upper bound of a defined compounded disturbance is introduced. Meanwhile, by utilizing the on-line estimating information of the unknown upper bound and the unknown parameters of necessary FLSs, a new adaptive fuzzy fault-tolerant controller with the adjustable parameter updated laws is designed to achieve robust tracking performance. Furthermore, it is shown that all the closed-loop signals of the interconnected subsystems are uniformly bounded and the tracking errors asymptotically converge to zero via Lyapunov stability analysis. Finally, numerical simulation results are provided to demonstrate the efficiency of the presented decentralized adaptive fuzzy fault-tolerant tracking design scheme. (C) 2015 Elsevier B.V. All rights reserved.

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