Study on application of system identification of a 6R serial manipulator using artificial neural network
The lack of transparency of the nonlinear systems has forced improvement to be made to its control system to enhance the control efficiency and accuracy. In this article, system identification using artificial neural network (ANN) is embedded in an adaptive control to model a nonlinear system due to its ability of approximating any kind of nonlinear mapping. The presented application is applied to a 6R serial manipulator, and the experiments about the joint tracking control show that it can greatly improve the control accuracy and reduce the control cycle and the computation of the adaptive control algorithm.
Serial manipulator Artificial neural network (ANN) Adaptive control Nonlinear system System identification
Xuanyin Wang Yuanming Ding
The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China
国际会议
杭州
英文
490-493
2009-04-08（万方平台首次上网日期，不代表论文的发表时间）