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基于仿生群智能优化RBF神经网络的机械手滑模控制方法研究 被引量:4
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作者 杨雨佳 张福泉 王怡鸥 《机床与液压》 北大核心 2020年第18期189-195,共7页
为了提高机械手滑模控制的准确度,采用RBF神经网络来完成机械手滑模控制,并借助群体智能算法中的混合蛙跳算法来实现模型参数的优化。在机械手滑模控制及机械手运动轨迹跟踪过程中,将RBF神经网络权重和阈值作为蛙跳算法的青蛙个体,随机... 为了提高机械手滑模控制的准确度,采用RBF神经网络来完成机械手滑模控制,并借助群体智能算法中的混合蛙跳算法来实现模型参数的优化。在机械手滑模控制及机械手运动轨迹跟踪过程中,将RBF神经网络权重和阈值作为蛙跳算法的青蛙个体,随机产生的多个权重和阈值组合个体构成蛙群,并对蛙群进行分组,通过不断重新分组和组内迭代的方法来获取全局最优个体,得到最优权重和阈值,确定最优机械手滑模控制模型。经过实验证明,采用基于仿生群智能优化RBF神经网络的机械手滑模控制,跟踪准确度高。 展开更多
关键词 仿生群智能优化 机械手滑模控制 RBF神经网络 蛙跳算法 跟踪误差
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Dynamic analysis, simulation, and control of a 6-DOF IRB-120 robot manipulator using sliding mode control and boundary layer method 被引量:3
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作者 Mojtaba HADI BARHAGHTALAB Vahid MEIGOLI +2 位作者 Mohammad Reza GOLBAHAR HAGHIGHI Seyyed Ahmad NAYERI Arash EBRAHIMI 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第9期2219-2244,共26页
Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,... Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,nonlinear controllers with robust performance which can cope with these are recommended.The sliding mode control(SMC)is a robust state feedback control method for nonlinear systems that,in addition having a simple design,efficiently overcomes uncertainties and disturbances in the system.It also has a very fast transient response that is desirable when controlling robotic manipulators.The most critical drawback to SMC is chattering in the control input signal.To solve this problem,in this study,SMC is used with a boundary layer(SMCBL)to eliminate the chattering and improve the performance of the system.The proposed SMCBL was compared with inverse dynamic control(IDC),a conventional nonlinear control method.The kinematic and dynamic equations of the IRB-120 robot manipulator were initially extracted completely and accurately,and then the control of the robot manipulator using SMC was evaluated.For validation,the proposed control method was implemented on a 6-DOF IRB-120 robot manipulator in the presence of uncertainties.The results were simulated,tested,and compared in the MATLAB/Simulink environment.To further validate our work,the results were tested and confirmed experimentally on an actual IRB-120 robot manipulator. 展开更多
关键词 robot manipulator control IRB-120 robot sliding mode control sliding mode control with boundary layer inverse dynamic control
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