【作者】 陈卫东； 陈丽； 王海涛； 王洪瑞；

【Author】 CHEN Wei-Dong, CHEN Li ,Wang Hai-Tao, WANG Hong-Rui (Department of Electronic Engineering, Yanshan University, Qinhuangdao 066004,China)

【机构】 燕山大学电气工程学院；

【摘要】 针对模型未知和动力学非线性机器人轨迹跟踪,提出了一种基于模糊回归神经网络(FRNN)的间接自适应控制方法。该方法在PD动态反馈控制的基础上,引入模糊回归神经网络辨识器(FRNNI)和控制器(FRNNC)在线动态逼近对象的非线性动力学,减少了动力学非线性造成的误差。仿真结果表明该控制方案使系统具有良好的跟踪性能和较强的鲁棒性。更多还原

【Abstract】 This paper presents an indirect adaptive control scheme for nonlinear robot manipulators trajectory tracking based on fuzzy recurrent neural-network. This method combines PD dynamic feedback controller with fuzzy neural identifier and neural controller, in order to approach the nonlinear dynamics and reduce the tracking error caused by the robotic nonlinear uncertainties. The control scheme can guarantee better trajectory tracking performance and robustness. Simulation results prove the validity of theoretic analysis results.更多还原