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基于RBF神经网络的空间机械臂关节空间轨迹跟踪补偿控制 被引量:1

Trajectory tracking compensating control for the joint space of space manipulator based on RBF neural network
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摘要 在PD策略的计算力矩法基础上,讨论了系统参数不确定的空间机械臂系统的控制问题.针对空间机械臂载体的位置不受控制,姿态受控制的情况下,对系统动量守恒关系进行了分析,得到了空间机械臂的系统动力学方程.采用PD策略的计算力矩法,考虑协调参数的不确定性,得到了系统的闭环动态误差方程.在此基础上提出了一种基于RBF神经网络的补偿学习控制方法,设计了具有不确定性的自由漂浮空间机械臂关节空间的补偿控制方案.将基于神经网络的补偿学习控制与计算力矩法相结合,利用进化学习来消除系统参数不确定性而造成的轨迹跟踪不准确的问题,实现了对空间机械臂关节空间内的轨迹跟踪控制.数值仿真的结果验证了该方法的有效性. In this paper,based on the PD type computed torque method,the control of space manipulator with uncertain system parameter is discussed.The closed-loop dynamic error equations considering uncertainties of the space manipulator is derived.A compensating learning control method using RBF Neural Network is proposed.Aided of RBF neural Network's evolutionary learning,system uncertainties can be approached,then the computed torque method and the RBF network learning control can combine to use evolutionary learning eliminate the problem of trajectory tracking error caused by the uncertainty of system parameter,and it realizes the spece trajectory tracking control in the space of space manipulators joint.Simulation results confirm the efficiency of the control method.
出处 《闽江学院学报》 2011年第2期34-37,共4页 Journal of Minjiang University
基金 福建省科技厅2010年A类项目(JA10227) 闽江学院2009年科技启动项目(YKQ09002)
关键词 空间机器人 RBF神经网络 学习控制 关节空间 space manipulator RBF neural network learning control joint space
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参考文献11

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二级参考文献12

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