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Adaptive fault tolerant control against actuator faults
Author(s) -
Shen Qikun,
Jiang Bin,
Shi Peng
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2689
Subject(s) - control theory (sociology) , actuator , fault tolerance , nonlinear system , controller (irrigation) , function (biology) , artificial neural network , fault (geology) , control engineering , computer science , property (philosophy) , control reconfiguration , class (philosophy) , control (management) , engineering , distributed computing , artificial intelligence , embedded system , biology , philosophy , physics , epistemology , quantum mechanics , evolutionary biology , seismology , agronomy , geology
Summary This paper investigates the problem of adaptive fault tolerant control for a class of dynamic systems with unknown un‐modeled actuator faults. The fault model is assumed to be an unknown nonlinear function of control input, not in the traditional form in which the faults can be described as gain and/or bias faults. Using the property of the basic function of neural networks and the implicit function theorem, a novel neural networks‐based fault tolerant controller is designed. Finally, the lateral dynamics of a front‐wheeled steered vehicle is used to demonstrate the efficiency of the proposed design techniques. Copyright © 2016 John Wiley & Sons, Ltd.