收稿日期: 2010-08-17
修回日期: 2010-09-28
网络出版日期: 2011-07-15
基金资助
中国航天科技集团创新基金(CAST09C01)资助
Adaptive compensation control of free-floating space robot based on fuzzy neural network
Received date: 2010-08-17
Revised date: 2010-09-28
Online published: 2011-07-15
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]. 中国科学院大学学报, 2011 , 28(4) : 514 -521 . DOI: 10.7523/j.issn.2095-6134.2011.4.013
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.
Key words： fuzzy neural network; GL matrix; space robot; adaptive control
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