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基于RBF神经网络补偿的一种绳牵引并联机器人支撑系统的力/位混合控制 被引量:3

Force/position hybrid control for a wire-driven parallel robot support system based on RBF neural network compensation
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摘要 为了保证用于风洞试验的绳牵引并联机器人支撑系统(wire-driven parallel robot support system,WDPRSS)的末端执行精度,设计一种采用Hamilton-Jacobi Inequality(HJI)定理并基于RBF神经网络补偿的力/位混合控制.通过对WDPRSS的动力学建模分析,选择以位姿作为变量建立WDPRSS的整体动力学方程,将所设计的力/位混合控制代入到整体动力学方程中得到误差闭环系统,对闭环系统进行稳定性分析,结果表明WDPRSS是趋于渐近稳定特性的.对八绳牵引的并联机器人支撑系统进行Matlab/Simulink仿真实验,仿真结果表明所设计的力/位混合控制是正确有效的,满足控制精度要求,并将所设计的力/位混合控制与PD控制进行对比分析.最后,通过样机实验验证所提出控制方案的有效性. In order to guarantee the precision of the end effector of a wire-driven parallel robot support system(WDPRSS)used in a wind tunnel test,a force/position hybrid control is proposed based on the Hamilton-Jacobi Inequality(HJI)theorem and RBF neural network compensation.Through dynamic modeling analysis of the WDPRSS,the whole dynamic equation of the WDPRSS is established using the pose as the variable.The proposed force/position hybrid control is substituted into the dynamic equation to obtain the error closed-loop system.The stability analysis of the closed-loop system shows that the WDPRSS tends to be asymptotic stable.A MATLAB/SIMULINK simulation experiment of the WDPRSS is conducted.The simulation results show that the proposed force/position hybrid control strategy is correct and valid,and satisfies control accuracy requirement.And the designed force/position hybrid control and PD control are compared and analyzed.Finally,the effectiveness of the proposed control scheme is verified by prototype experiments.
作者 王宇奇 林麒 王晓光 周凡桂 刘骏 WANG Yu-qi;LIN Qi;WANG Xiao-guang;ZHOU Fan-gui;LIU Jun(School of Aerospace Engineering,Xiamen University,Xiamen 361005,China)
出处 《控制与决策》 EI CSCD 北大核心 2020年第3期536-546,共11页 Control and Decision
基金 国家自然科学基金项目(11472234,11072207,11702232).
关键词 WDPRSS 动力学 HJI定理 RBF神经网络补偿 力/位混合控制 WDPRSS dynamics HJI theorem RBFNN compensation force/position hybrid control
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