Sliding Mode Control for Electromagnetic Satellite Formation Based on RBF Neural Network

摘要：

　　In this paper,a radial basis function (RBF) neural network based sliding mode control is presented.Taking CW equation as dynamics model,the parameter perturbation and external disturbance has been considered.The controller consists of two parts,one is the feed-forward control,and the other is feedback sliding mode control using RBF neural network.Based on Lyapunov stability theory,the adaptive law of neural network has been obtained.Simulation results suggest that the control scheme can initialize the formation and maintain the relative motion according to the desired trajectory.The inherent chattering of sliding mode control has been weaken and the accuracy of trajectory tracking has greatly improved with the use of RBF neural network.

关键词： sliding mode control RBF neural network electromagnetic satellite formation flight

作者: Kefei Lian Yunfeng Dong

作者单位: School of Astronautics Beijing University of Aeronautics and Astronautics Beijing 100191, PR China

会议类型: 国际会议

会议名称: 2016 Sixth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2016)(第六届仪器测量、计算机通信与控制国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 532-535

在线出版日期: 2016-07-21（万方平台首次上网日期，不代表论文的发表时间）