Fault-Tolerant Control of Stochastic Strict-Feedback Nonlinear Systems With Multiple Faults

被引：5
作者：
Wang, Tong [1 ]
Zhao, Zhihong [1 ]
Wang, Nan [2 ]
机构：
[1] Harbin Inst Technol, Res Inst Intelligent Control & Syst, Harbin 150080, Peoples R China
[2] Henan Univ Sci & Technol, Sch Informat Engn, Luoyang 471600, Peoples R China
来源：
IEEE TRANSACTIONS ON RELIABILITY | 2024年 / 73卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Artificial neural networks; Stochastic processes; Actuators; Stability analysis; Observers; Nonlinear systems; Process control; Actuator fault; fault-tolerant control (FTC); neural network (NN); sensor fault; DYNAMIC SURFACE CONTROL; NEURAL-NETWORK CONTROL; TRACKING CONTROL; DESIGN;
D O I：
10.1109/TR.2024.3354979
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this article, we study the fault-tolerant control (FTC) issue of stochastic nonlinear controlled plants. The considered plant is of strict-feedback form, which subjects to multiple faults, i.e., sensor and actuator faults. For the purpose of estimating the unmeasured system state vectors, a neural-network-based observer is presented. With the help of a combined quadratic, cubic, and quartic Lyapunov functional candidate, a new type of adaptive FTC strategy is formulated to ensure the overall tracking performance with multiple faults. Besides, the corresponding stability analysis is carried out as well. Comparing with the simulation results without fault compensation strategy, the validity of the designed FTC mechanism is verified.
引用
收藏
页码：1684 / 1692
页数：9
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