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Robust adaptive fault‐tolerant quantized control of nonlinear systems with constraints on system behaviors and states.

Authors :
Zhao, Kai
Lei, Ting
Lin, Ting
Chen, Long
Source :
International Journal of Robust & Nonlinear Control. 5/25/2020, Vol. 30 Issue 8, p3215-3233. 19p.
Publication Year :
2020

Abstract

Summary: In this work, we develop a robust adaptive fault‐tolerant tracking control scheme for a class of input‐quantized strict‐feedback nonlinear systems in the presence of error/state constraints and actuation faults. The problem is rather complicated yet challenging if nonparametric uncertainties and unknown quantization parameters as well as time‐varying yet completely undetectable actuation faults are involved in the considered systems. Compared with the most existing approaches in the literature, the proposed control exhibits several attractive advantages: (1) upon using a nonlinear decomposition for quantized input and employing the robust technique for actuation fault, not only the exact knowledge of quantization parameters are not required, but also the actuation fault can be easily compensated since neither fault detection and diagnosis/fault detection and identification nor controller reconfiguration is needed; (2) based on the error/state‐dependent unified nonlinear function, the constraints on tracking error and system states are directly handled and the cases with or without constraints can also be addressed in a unified manner without changing the control structure; and (3) the utilization of unified nonlinear function‐based dynamic surface control not only avoids the problem of the explosion of complexity in traditional backstepping design, but also bypasses the demanding feasibility conditions of virtual controllers. Furthermore, by using the Lyapunov analysis, it is ensured that all signals in the closed‐loop systems are uniformly ultimately bounded. The effectiveness of the developed control algorithm is confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10498923
Volume :
30
Issue :
8
Database :
Academic Search Index
Journal :
International Journal of Robust & Nonlinear Control
Publication Type :
Academic Journal
Accession number :
142770707
Full Text :
https://doi.org/10.1002/rnc.4926