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

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.

关键词： Fault Diagnosis Fault-tolerant Control BP Neural Network PSO CSTR

作者: Zhou Li-qun Li Shu-chen Su Cheng-li Zhai Chun-yan

作者单位: School of Information and Control Engineering,Liaoning Shihua University, Fushun Liaoning 113001

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 700-704

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）