期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 27, 期 11, 页码 2242-2254出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2019.2896843
关键词
Actuators; Nonlinear systems; Adaptive systems; Stochastic processes; Observers; Stochastic systems; Fuzzy control; Actuator faults; adaptive fuzzy control; event-triggered control; full state constraints; fuzzy logic systems (FLSs)
资金
- National Natural Science Foundation of China [61622302, 61573070]
- Department of Education of Guangdong Province [2017KZDXM027]
- Science and Technology Planning Project of Guangdong Province [2017B010116006]
- Innovative Research Team Program of Guangdong Province Science Foundation [2018B030312006]
In this paper, an adaptive fuzzy output feedback control problem is investigated for a class of stochastic nonlinear systems in which the fuzzy logic systems are adopted to approximate the unknown nonlinear functions. A reduced-order observer and a general fault model are designed to observe the unavailable state variables and describe the actuator faults, respectively. An event-triggered control law is developed to reduce the communication burden from the controller to the actuator. Meanwhile, the barrier Lyapunov functions are constructed to guarantee that all the states of the stochastic nonlinear system are not to violate their constraints. Furthermore, an observer-based adaptive fuzzy event-triggered control strategy is proposed for the full-state-constrained nonlinear system with actuator faults based on backstepping technique, which can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin in a finite time. Finally, simulation results are given to illustrate the effectiveness of the proposed control scheme.
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