Fault-tolerant control strategies based on fuzzy neural networks for safe coal-mining
Due to its great potential value in theory and application, fault-tolerant control strategies of nonlinear coal-mining systems, especially combining with intelligent control methods, have been a focus in the academe. A fault-tolerant control method based on fuzzy neural networks presents nonlinear systems in this paper. The fault parameters was designed to detect the fault, and adaptive updating method was intro duced to estimate and tracking fault, fuzzy neural networks was used to adjust the fault parameters and construct automated fault diagnosis, and the fault compensation control force, which given by fault estima tion, was used to realize adaptive fault-tolerant control. This framework leaded to a simple structure, an accurate detection and a high robustness. The simulation results in induction motor showed that it was still able to work well with high dynamic performance and control precision under the condition of motor parameters variation fault and load torque disturbance.
fuzzy neural network coal-mining system fault-tolerant control adaptive
Dongsheng Zuo Jianguo Jiang Minghan Yuan Hua Jiang
School of Electronics and Electric Engineering, Shanghai Jiao Tong University,Shanghai 200030, China School of Electronics and Electric Engineering, Shanghai Jiao Tong University, Shanghai 200030, Chin Shanghai University of Electric Power,Shanghai 200090, China
国际会议
重庆
英文
263-270
2009-05-20（万方平台首次上网日期，不代表论文的发表时间）