A DYNAMIC FUZZY NEURAL NETWORKS CONTROLLER FOR DYNAMIC LOAD SIMULATOR
This paper presents the design, development of dynamic load simulator based on dynamic fuzzy neural networks (D-FNNs) controller. Dynamic load simulator (DLS) can reproduce desired load torque acting on loaded object to test its performance and stability. In DLS, the redundancy torque caused by the motion of loaded object has a very poor effect on the loading accuracy. So a simplified dynamic model is derived to clarify the causation of redundancy torque, and a inverse model controller based on D-FNNs is implemented to compensate redundancy torque and improve the accuracy of load torque despite the nonlinearity and uncertainties in the DLS system. The effectiveness of D-FNNs controller for DLS is verified by numerical simulation and experiment.
Dynamic load simulator Fuzzy system neural networks Inverse model control
BEN GUO MING-YAN WANG JIAN ZHANG
Dept.of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
375-379
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）