基于干扰观测器的机器人自适应滑模控制

Adaptive Sliding Mode Control Based on Disturbance Observer for Manipulator Systems

  • 摘要: 研究了一种基于干扰观测器的自适应滑模控制算法,并应用到机械臂运动控制当中,实现了机械臂关节运动的精确控制.考虑到机械臂系统存在外界干扰,设计了一种基于非奇异终端滑模的干扰观测器,对外界干扰进行估计并对系统输入进行补偿.结合提出的干扰观测器,设计了一种基于干扰观测器的连续自适应滑模控制方法,克服了系统“抖振”,提高了控制精度.通过李亚普诺夫方法证明了该算法的闭环系统稳定性.最后,将提出的连续滑模控制算法应用到机械臂运动控制当中,通过Matlab仿真表明其在外界干扰存在条件下,具有较高的控制精度和良好的鲁棒性.

     

    Abstract: We propose a novel adaptive sliding mode control algorithm for manipulator systems based on a disturbance observer. This mode control algorithm is successfully used in the motion control of manipulator systems to improve control precision and robustness. Considering external disturbance, we develop a new disturbance observer based on non-singular terminal sliding mode to compensate for control input to enhance precision. Then, we propose a continuous adaptive sliding mode control algorithm with a disturbance observer which can overcome chattering and improve control precision. Closed-loop stability is proved by Lyapunov theory. Matlab simulation results verify that the proposed approach has high precision and strong robustness in the presence of external disturbance and system uncertainty.

     

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