智能系统学报2012，Vol.7Issue(5)：457-461,5.DOI:10.3969/j.issn.1673-4785.201008005
模糊CMAC的柔性空间机器人轨迹跟踪自学习控制
Trajectory tracking self-study control for flexible space manipulators with fuzzy CMAC
摘要
Abstract
Considering the uncertainty of free floating adaptable space robot systems (FSRS) , cerebellar model articulation controller (CMAC) neutral network self-learning control strategies are used to solve the trajectory tracking control problems of the inverse model control algorithm. Firstly, a non-linearity dynamics equation of flexible space manipulator is established. The controller based on fuzzy CMAC neutral network is used for effectively learning how to compensate inverse-model, and fuzzy CMAC network parameters that could be adaptively adjusted online by improved supervisory Hebb learning rules. Error function is provided via proportional integration differential (PID) controller. The controller improved control accuracy and asymptotic convergence of tracking error. The simulation results illustrate the presented controller system has engineering value.关键词
模糊CMAC/逆模控制/柔性空间机器人/PID控制/轨迹跟踪/Hebb学习规则Key words
fuzzy CMAC/ inverse-model control/ flexible space robot/ PID control/ trajectory tracking/ Hebb learning rules分类
信息技术与安全科学引用本文复制引用
张文辉,周启航,齐乃明..模糊CMAC的柔性空间机器人轨迹跟踪自学习控制[J].智能系统学报,2012,7(5):457-461,5.基金项目
国家自然科学基金资助项目(61171189). （61171189）
