Observer Based Event-triggered Fault Compensation Control for Nonlinear Systems via Adaptive Dynamic Programming

被引：0
作者：
Luo, Fangchao [1 ]
Zhao, Bo [2 ]
Liu, Derong [1 ]
机构：
[1] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
[2] Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China
来源：
2020 10TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (ICIST) | 2020年
基金：
中国国家自然科学基金;
关键词：
Adaptive dynamic programming; Event-triggered mechanism; Adaptive fault compensation; Optimal control; Neural network; TOLERANT CONTROL; ROBUST; STABILIZATION; PERFORMANCE; ALGORITHMS;
D O I：
10.1109/icist49303.2020.9202005
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper develops an observer based event-triggered fault compensation control method for a class of nonlinear continuous-time systems with actuator failures via adaptive dynamic programming (ADP). The proposed control method incorporates an event-triggered optimal control policy and an adaptive observer-based compensator. Due to the excellent estimation performance of neural networks, the actuator failure is precisely estimated by the online learning observer. By combining the event-triggered mechanism with ADP, the eventtriggered optimal control policy is obtained by adopting the critic neural network to solve Hamilton-Jacobi-Bellman equation. The triggering condition is provided along with the stability analysis of the close-loop system. Finally, the simulation of single link robot arm system is presented to confirm the efficiency of the proposed fault compensation control method.
引用
收藏
页码：139 / 144
页数：6
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