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基于模糊CMAC的三连杆机械臂的最优控制器
Optimal Controller of Three-link Manipulator Based on Fuzzy CMAC Neural Network
【摘要】 研究了将模糊CMAC神经网络和最优控制方法Hkamilton-Jacobi-Bellman(H-J-B)相结合来实现三连杆机械臂的最优控制策略。介绍了模糊CMAC神经网络的基本结构,基于二次最优控制信号的模糊CMAC控制器设计,推导了基于Lyapunov稳定性分析理论的神经网络自适应学习算法,并通过一个鲁棒化向量来克服系统模型中不确定项的影响,保证系统的稳定性。
【Abstract】 In this paper,fuzzy CMAC neural network is compound with the optimal control method (H-J-B) to realize the the optimal control strategy of three-link manipulator.It introduces the basic structure of fuzzy CMAC neural network and the design of fuzzy CMAC neural network controller based on quadratic optimal control signals,deduces a neural network adaptive algorithm in terms of Lyapunov theory,designs an optimal control method of three-link manipulator,and hurdle the effect of uncertainty in the system model through a robust vector,to guarantee the system′s stability.
【Key words】 fuzzy CMAC neural network; H-J-B optimal control; neural network adaptive algorithm; robust;
- 【文献出处】 现代电子技术 ,Modern Electronics Technique , 编辑部邮箱 ,2007年11期
- 【分类号】TP241
- 【被引频次】1
- 【下载频次】130