Application of fuzzy neural PID controller based on PSO for high precision servo system
Friction is a key factor that influences the low velocity performance of high precision servo systems. It usually causes the steady-state error of servo systems and results in the creeping phenomenon in low velocity motions. Friction is complicated nonlinear process with time-varying uncertainties. The traditional PID controller of servo systems with fricition was not satisfactory in control precision and response timcln this paper,the fuzzy neural PID controller based on fuzzy neural network(FNN),which combines the advantages of robustness and nonlinear characteristic of fuzzy control and adaptive selflearning capability of neural network,was used to eliminate nonlinear disturbance caused by friction. To solve the problems of stagnation,poor convergence and local optima in traditional NN Learning Algorithms,the modified PSO algorithm is adopted to train FNN on line. The experiment result demonstrates that FNN PID controller can remove friction disturbance efficiently and reduce steady-state error to only one fifth of the one using the PID algorithm.
friction nonlinear high precision FNN PSO
Li Xinghua Chen Wenlei Zhang Yajuan
State Key Laborary of Precision Measuring Technology and Instruments Tianjin University Tianjin,China
国际会议
杭州
英文
671-674
2011-10-28（万方平台首次上网日期，不代表论文的发表时间）