Sigmoid Fuzzy Neural Network

摘要：

Aiming at high maneuverability and ability to avoid obstacles in motion control of mini underwater robots, a novel method of control based on sigmoid fuzzy neural network was presented. The structure of fuzzy neural network was constructed according to the moving characters, and the learning algorithm which calculated dynamic learning ratio based on least disturbance was deduced in detail. Finally, simulation and lake experiments were carried out on WEILONG mini underwater robot. The results show that dynamic learning ratio keeps the learning of neural network stable and fast, and the operating speed was picked up greatly on the basis that there is no loss for integral control quality. The response ability is improved, which meets the requirement of real-time control.

关键词： mini underwater robot fuzzy neural network control sigmoid function least disturbance dynamic learning ratio

作者: Liang Xiao Guo Bingjie Wan Lei

作者单位: College of Shipbuilding Engineering Harbin Engineering University Harbin, China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）