摘要
讨论了载体位置无控、姿态受控情况下,双臂空间机器人姿态、关节协调运动的控制问题.由Lagrange第二类方法及系统动量守恒关系,建立了漂浮基双臂空间机器人的系统动力学方程.以此为基础,借助于RBF神经网络技术、GL矩阵及其乘积算子定义,对双臂空间机器人系统进行了神经网络系统建模;之后针对双臂空间机器人所有惯性参数均未知的情况,设计了双臂空间机器人载体姿态与机械臂各关节协调运动基于RBF神经网络的自适应控制算法.提出的控制算法不要求系统动力学方程具有惯常的关于惯性参数的线性性质,且无需预知系统惯性参数的任何信息,也无需对神经网络进行离线训练、学习,因此更适于实时应用.一个平面漂浮基双臂空间机器人系统的数值仿真,证实了该控制算法的有效性.
The control problem of coordinated motion between the base＇ s attitude and the arms＇ joints of a free-floating dual-arm space robot with uncertain parameters was discussed, Combining the relationship of the system linear momentum conversation and the Lagrangian approach, the dynamic equation of a free-floating dual-arm space robot was established, Based on the above results, the free-floating dual-arm space robot system was modeled by the RBF neural network technique, the GL matrix and its product operator. With all uncertain inertial parameters of system, the adaptive RBF neural network control scheme was developed for coordinated motion between the base＇s attitude and the arms＇ joints of the free-floating dual-arm space robot. This proposed control scheme need neither linearly parameterize the dynamic equation of system and foreknow any actual inertial parameters accurately, nor train the neural network offiine so that it could be prone to real-time and online application. A planar free-floating dual-arm space robot is simulated to verify the feasibility of the proposed control scheme,
出处
《应用数学和力学》
CSCD
北大核心
2008年第9期1028-1036,共9页
Applied Mathematics and Mechanics
基金
国家自然科学基金资助项目(1037202210672040)
福建省自然科学基金资助项目(E0410008)
