Force Control of Electrical Load System Based on Single Neuron PID Adaptive and Repetitive Control

摘要：

　　In view of the surplus torque and complexity of controlled plant in passive electrical load system,a novel approach based on single neuron PID adaptive control and repetitive control for repetitive periodic load control system is proposed.Radial basis function (RBF) neural network is used to identify the system on-line for the single neuron PID controller to adjust its weights and PID parameters by self-learning and self-adapting based on the desired output.The dynamic state performance can be improved by the single neuron adaptive PID control and the steady state performance is also improved by modified repetitive control.Computer simulation results show that the force/position hybrid control system can effectively reduce the surplus torque and improve the loading precision,and also it has fine dynamic and steady state performance and good robustness.The reliability of whole system is further improved.

关键词： surplus torque electrical load system single neuron PID control repetitive control

作者: Zhiqiang Wei Guanghua Zong Hongchong Wu

作者单位: Robotics Institute Beihang University Beijing,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 1206-1210

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）