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Adaptive decentralized fault‐tolerant tracking control for large‐scale nonlinear systems with input quantization
Author(s) -
Wang CaiCheng,
Yang GuangHong
Publication year - 2018
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4086
Subject(s) - backstepping , control theory (sociology) , actuator , nonlinear system , quantization (signal processing) , computer science , fault tolerance , bounded function , adaptive control , decentralised system , uniform boundedness , control engineering , mathematics , control (management) , engineering , algorithm , artificial intelligence , mathematical analysis , distributed computing , physics , quantum mechanics
Summary In this paper, an adaptive decentralized tracking control scheme is designed for large‐scale nonlinear systems with input quantization, actuator faults, and external disturbance. The nonlinearities, time‐varying actuator faults, and disturbance are assumed to exist unknown upper and lower bounds. Then, an adaptive decentralized fault‐tolerant tracking control method is designed without using backstepping technique and neural networks. In the proposed control scheme, adaptive mechanisms are used to compensate the effects of unknown nonlinearities, input quantization, actuator faults, and disturbance. The designed adaptive control strategy can guarantee that all the signals of each subsystem are bounded and the tracking errors of all subsystems converge asymptotically to zero. Finally, simulation results are provided to illustrate the effectiveness of the designed approach.