A kind of new dynamic modeling method based on improved genetic wavelet neural networks for the robot wrist force sensor

摘要：

This paper presents a method used to the robot wrist force sensor modeling based on improved genetic wavelet neural networks (IGWNN) and the principle of algorithm is introduced. In this method, the dynamic model of the wrist force sensor is set up according to data of the dynamic calibration, where the structure and parameters of wavelet neural networks of the dynamic model are optimized by genetic algorithm. The results show that the proposed method can overcome the shortcomings of easy convergence to the local minimum points of BP algorithm, and the network complexity, the convergence and the generalization ability are well compromised and the training speed and precision of model are increased.

关键词： wrist force sensor dynamic modeling wavelet neural networks genetic algorithm

作者: Yu A-long

作者单位: School of Physics and Electronic Electrical Engineering, Huaiyin Normal University Huaian, Jiangsu, 223300.PR China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 641-644

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）