漂浮基空间机械臂基于双向映射神经元网络的逆运动学控制

Inverse Kinematic Control of Free-floating Space Manipulator System Based on a Mutual Mapping Neural Network

基于双向映射神经元网络,讨论了载体位置、姿态均不受控制情况下,漂浮基空间机械臂的运动学控制问题。为此,根据系统几何关系,结合系统动量守恒、动量矩守恒关系,分析、建立了空间机械臂的广义运动雅可比关系。以此为基础,利用双向映射神经元网络及李雅普诺夫直接方法,设计了一种收敛的空间机械臂逆运动学控制方法,以控制空间机械臂的末端位姿朝着惯性空间的期望位姿点运动。提出的控制方法的突出优点在于:既不需要确切知道空间机械臂运动雅可比矩阵的具体结构,也不需要了解系统动力学参数的相关信息。一个作平面运动的自由漂浮两杆空间机械臂系统的数值仿真,证实了方法的有效性。

Based on a mutual mapping neural network,the inverse kinematic control problem of the free-floating space manipulator system without base control is discussed.With the geometrical relation and the linear,angular momentum conservation of the free-floating space manipulator system,the kinematic equation of the system is deduced and the generalized Jacobian matrix is obtained.Following the above result,a mutual mapping neural network inverse kinematic control scheme employing Lyapunov functions is designed to control the end-effector of the free-floating space manipulator system to track the desired trajectory in workspace.The control scheme needs neither the structure of generalized Jacobian matrix nor the relevant information of dynamic parameters.A planar two-link free-floating space manipulator system is simulated to verify the designed control scheme.