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柔性关节空间机器人基于柔性补偿的模糊鲁棒滑模控制及柔性振动主动抑制
引用本文:谢立敏,陈力.柔性关节空间机器人基于柔性补偿的模糊鲁棒滑模控制及柔性振动主动抑制[J].空间科学学报,2013,33(6):683-689.
作者姓名:谢立敏  陈力
作者单位:1.福建农林大学机电工程学院 福州 350002
基金项目:国家自然科学基金项目(11372073, 11072061, 10672040)和福建省自然科学基金(2010J01003)共同资助
摘    要:针对参数不确定的漂浮基柔性关节空间机器人系统,研究了其动力学建模过程、运动控制律设计及柔性振动的主动抑制.利用系统动量、动量矩守恒关系和拉格朗日方程建立了系统的动力学方程.为克服传统奇异摄动法仅适用于关节弱柔性系统这一局限性,设计了柔性补偿项来等效提高空间机器人系统中柔性关节的刚度.在此基础上,利用奇异摄动法将系统分解为相互独立的慢变子系统和快变子系统,并分别进行控制律设计.所设计的慢变子系统模糊鲁棒滑模控制律可补偿系统中的不确定参数,减小柔性关节引起的转角传动误差,实现系统期望运动轨迹的渐近跟踪;快变子系统控制律可主动抑制柔性关节引起的系统柔性振动.仿真实验结果证明了该混合控制律的有效性. 

关 键 词:空间机器人    柔性关节    奇异摄动    柔性补偿    模糊    鲁棒    滑模
收稿时间:2012-10-24

Fuzzy Robust Sliding Mode Control and Flexible Vibration Active Suppression of Flexible-joint Space Robot Based on Flexibility Compensation
Affiliation:1.School of Mechanical and Electronic Engineering, Fujian Agriculture and Forestry University, Fuzhou 3500022.School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108
Abstract:For free-floating flexible-joint space robot system with uncertain parameters, the dynamics modeling, motion controller design and flexible vibration active suppression are developed. Dynamic equations of the system are established by the system's linear and angular momentum conservation and Lagrange equation. In order to overcome the limitations of that the traditional singular perturbation method only applies to the system with weak joint flexibility, a joint flexibility compensator is designed to improve the flexible-joint's stiffness of space robot system equivalently. On the above basis, the system is decomposed into a slow subsystem and a fast subsystem by singular perturbation method, and the controllers of the subsystems are designed. The slow subsystem's fuzzy robust sliding mode controller can compensate the uncertain parameters, decrease the rotation angle transmission errors caused by the flexible-joint, and realize the asymptotic tracking of the system desired trajectory. The fast subsystem controller can suppress the flexible vibration caused by flexible-joint actively. The simulation experimental results prove the efficiency of the hybrid controller. 
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