Fault-tolerant Control Algorithm of Neural Network Based on Particle Swarm Optimization

被引：0
|
作者：
Zhou Li-qun [1 ]
Li Shu-chen [1 ]
Su Cheng-li [1 ]
Zhai Chun-yan [1 ]
机构：
[1] Liaoning Shihua Univ, Sch Informat & Control Engn, Fushun 113001, Liaoning, Peoples R China
来源：
2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6 | 2011年
关键词：
Fault Diagnosis; Fault-tolerant Control; BP Neural-Network; PSO; CSTR; PERFORMANCE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A fault-tolerant control method combining fault diagnosis and fault-tolerant control is proposed for sensor faults. A BP neural network based on Particle Swarm Optimization algorithm is used to estimate system states and fault parameters of the constructed model for sensor faults. The estimated fault parameters are processed by the modified Bayes classification algorithm to achieve sensor faults diagnosis, separation and estimation on-line, and sensor faults are described as "equivalent bias" vectors to realize fault-tolerant control by compensation algorithm. Simulation results for, continuous stirred tank reactor. (CSTR) show good convergence of the approach and strong fault-tolerant ability for sensor faults.
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页码：700 / 704
页数：5
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