Disturbance-Observer-Based Fault Tolerant Control of High-Speed Trains: A Markovian Jump System Model Approach

被引:0
|
作者
Yao, Xiuming [1 ]
Wu, Ligang [2 ]
Guo, Lei [3 ,4 ]
机构
[1] School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
[2] Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China
[3] School of Electrical Engineering and Automation, Beihang University, Beijing, China
[4] Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing,100191, China
基金
中国国家自然科学基金;
关键词
Lyapunov functions - Fault detection - Markov processes - Fault tolerance - Convex optimization - Railroads - Railroad cars - Railroad transportation - Stochastic models;
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学科分类号
摘要
This paper addresses the fault tolerant control problem for high-speed trains in case of multiple possible failures. A new multiple point-mass model with system faults is built based on a stochastic jump system model approach. A novel active fault tolerant composite hierarchical anti-disturbance control strategy based on the disturbance observer is proposed such that the resulting composite system is stochastically stable with position and velocity tracking performance. According to whether the transition probabilities (TPs) of the failure and fault detection and isolation process can be accessed completely, three different cases (TPs are completely known, partially known, and completely unknown) are analyzed. For each case, based on the Lyapunov functional approach, a composite hierarchical controller is synthesized via a convex optimization problem. Finally, the simulations are given to illustrate the performance of the proposed methodologies. © 2020 IEEE.
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页码:1476 / 1485
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