Event Triggered Fault Tolerant Control for Nonlinear Systems Based on Adaptive Fault Estimation

被引：0
|
作者：
Fan, Quan-Yong [1 ]
Xu, Shuoheng [1 ]
Deng, Chao [2 ]
Wang, Cai-Cheng [3 ]
机构：
[1] Northwestern Polytech Univ, Sch Automat, Xian, Peoples R China
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
[3] North Automat Control Technol Inst, Taiyuan, Peoples R China
来源：
16TH IEEE INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2020) | 2020年
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Nonlinear systems; fault tolerant control; event triggered control; neural network learning; TIME CONTROL; DESIGN;
D O I：
10.1109/icarcv50220.2020.9305501
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the problem of event triggered fault-tolerant control for nonlinear systems based on neural network learning technique is investigated. To achieve the main objective, a novel dynamic fault estimation method is proposed so that the fault mode of the system considered can be determined quickly. Then, one appropriate reference dynamics is selected. Based on the model reference control mechanism, the neural network is employed to learn the desired control policy when the event triggering condition is met. The stability of the closed-loop system is proved based on Lyapunov stability theory. Moreover, there does not exist the Zeno phenomenon using the proposed event triggered control method. Finally, the the effectiveness of the proposed method is verified on a single-joint manipulator system.
引用
收藏
页码：1236 / 1241
页数：6
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