中国科学院研究生院学报2011，Vol.28Issue(4)：514-521,8.
漂浮基空间机器人的基于模糊神经网络的自适应补偿控制
Adaptive compensation control of free-floating space robot based on fuzzy neural network
摘要
Abstract
Considering trajectory tracking of free-floating space robot with uncertainties and friction blind section non-linearity, we propose an adaptive fuzzy CMAC compensation control algorithm. The control scheme uses fuzzy neural network to establish modeling online, and imports GL matrix and multiplication operator ". " into neural network to distinguish parameters of system and friction blind section non-linearity. The control scheme can guarantee the stability of closed loop system and the asymptotic convergence of tracking errors. Neural network approach errors and outside disturbance can be eliminated by sliding model controller. Based on a standard Lyapunov theorem, we prove that all signals in the closed-loop are bounded. The simulation results show that the controller can achieve high control precision and meet the requirement of real time.关键词
模糊神经网络/GL矩阵/空间机器人/自适应控制Key words
fuzzy neural network/GL matrix/space robot/adaptive control分类
计算机与自动化引用本文复制引用
张文辉,齐乃明,马静,肖阿阳..漂浮基空间机器人的基于模糊神经网络的自适应补偿控制[J].中国科学院研究生院学报,2011,28(4):514-521,8.基金项目
中国航天科技集团创新基金(CAST09C01)资助 （CAST09C01）
