Fixed‐time fault‐tolerant control of uncertain MIMO switched interconnected systems subject to state delay, unknown control directions, and quantized nonlinear inputs

Abstract

Summary This paper investigates design of an adaptive fixed‐time fault‐tolerant decentralized controller for a class of uncertain multi‐input multi‐output (MIMO) switched large‐scale non‐strict interconnected systems under arbitrary switching subject to unknown control directions, quantized nonlinear inputs, actuator failures unknown external disturbances, and unmodeled dynamics. In addition to interconnected terms, time‐varying delayed interconnected terms have been considered in the system model which makes it more general than previous works in the literature. The proposed controller can handle switched systems with unknown switching signal and different types of input nonlinearities including, saturation, backlash, and dead‐zone. The singularity problem in designing the fixed time controller has been solved. The quantizer and actuators fault parameters are assumed to be unknown. The Razumikhin lemma has been used to deal with the delayed interconnected terms. To cope with the system unknown dynamics, neural networks (NNs) have been applied and by updating the maximum norms of the networks weight vectors the computational load has been reduced. The explosion of complexity occurring in the traditional back‐stepping technique has been avoided by applying dynamic surface control (DSC). Finally, by defining an appropriate common Lyapunov function (CLF), fixed‐time convergence of system outputs and the closed‐loop system stability have been established. The effectiveness of the proposed controller has been shown via simulation study.

Robust and quantized repetitive tracking control for fractional‐order fuzzy large‐scale systems

“…Remark Note that some existing controller design methods (state‐feedback, adaptivity, finite‐time, $$$ {H}_{\infty } $$$, sampled‐data, guaranteed cost) were developed for LSSs in References 3,8,10,12,13,16,17, LSSs with fuzzy model in References 24–29, Fuzzy LSSs with input‐quantization in References 47–51, Fuzzy LSFOSs with estimation based controller in References 4,30–39, the disturbance rejection tracking control (RC,MRC) for nonlinear systems in References 40,41,43,44 and Fuzzy LSFOSs for disturbance rejection/tracking controller in References 41,54. In addition, this article discussed the disturbance rejection‐based MRC for Fuzzy LSFOSs with input‐quantizer and $$$ {H}_{\infty } $$$ performance index.…”

“…Remark 2. It is noted that, the significant number of research studies have been studied in existing literatures on the modified repetitive controller and input-quantization for nonlinear systems in References 38,39,47,48. Nonetheless, the stability of fractional-order LSSs with fuzzy technique is not fully fetched recently. It should be noted that the interconnection between the subsystems has been assumed to be unknown and nonlinear in practice.…”

“…Quantization robust nonlinear characteristics, which can degrade the system performance or may lead instability of the systems. In Reference 47, a new set of sufficient condition is derived to obtain decentralized control with a prescribed $$$ {H}_{\infty } $$$ performance level for a class of large‐scale systems with the power constraint. Ghoreishee et al 48 derived a finite‐time adaptive decentralized control law with input quantization, actuator faults and external disturbances which can ensure that the signals of every subsystem converge to zero and reduced complexity via dynamic surface control technique.…”