Fuzzy Quantized Control of Nonstrict Feedback Nonlinear Systems with Actuator Faults
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Fuzzy Quantized Control of Nonstrict Feedback Nonlinear Systems with Actuator Faults Hang Su1 • Weihai Zhang1
Received: 26 September 2019 / Revised: 4 February 2020 / Accepted: 12 May 2020 Ó Taiwan Fuzzy Systems Association 2020
Abstract This paper studies the adaptive tracking control problem for a class of nonstrict feedback nonlinear systems with quantized inputs and actuator faults. Compared with existing works on quantized control problem, the asymmetric hysteresis quantizer is considered in the actuator failure problem in this paper. To resolve the control challenge caused by the quantization effect, a nonlinear decomposition of the quantizer is proposed and applied to the controller design in the last step of the backsteppingbased control approach. Combining with fuzzy logic systems, the unknown nonlinear functions contained in the researched nonlinear system is disposed without knowing some restrictive conditions of uncertainties. The developed controller guarantees that the system output converges to a small neighborhood of the desired reference signal and all the signals of the closed-loop system are bounded. Finally, simulation results are depicted to illustrate the efficiency of the proposed control algorithm. Keywords Adaptive tracking control Nonstrict feedback nonlinear systems Quantized inputs Actuator faults
1 Introduction In practical engineering systems, the plants pass the control signals through actuator components, if the actuators are under sudden faults or lose some of effectiveness and they
& Hang Su [email protected] 1
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China
are vulnerable to these failures, the normal operation, reliability and stability of the system will be affected. Moreover, kinds of failures occur due to wear, aging, external disturbances and other instability-influencing factors. Therefore, the issues of dealing with actuator failures have been developed by substantial research fault-tolerant control (FTC) methods such as [1–6]. In [1–3], the fixed controller was designed in passive approach to achieve the acceptable level of performance in the preprogrammed failure situations. On the other hand, many active FTC methods were considered in fault-diagnosis-based approach [4], sliding mode control scheme [5], and multiple-model control design [6]. Particularly, adaptive-based FTC strategy has become a promising active approach to cope with actuator failures. The problem of event-triggered control for uncertain nonlinear systems with actuator failures was studied in [7]. In [8], a computationally inexpensive and low-complexity state feedback control FTC scheme was proposed to guarantee prescribed tracking performance for nonlinear systems with unknown control directions. Due to the fact that fuzzy logic systems and neural networks can be used to approximate the unknown nonlinear functions on arbitrary compact set, adaptive fuzzy and neural FTC have received growing attraction in the past decades.
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