基于时延估计的机械臂改进趋近律滑模控制

Improved reaching law sliding mode control of manipulatorbased on time delay estimation

针对机械臂动力学模型存在不确定性以及外部扰动情况下的轨迹跟踪控制问题,提出一种基于时延估计的改进趋近律滑模控制策略。采用时延估计方法把机械臂动力学模型转化为局部模型,并针对局部模型设计滑模控制器,实现机械臂系统的轨迹跟踪控制;考虑到传统滑模控制收敛速度慢且存在抖振的问题,设计一种改进型趋近律,有效提高系统动态响应速度,抑制系统抖振,并从理论上证明了改进型趋近律的存在性和可达性。对比仿真结果显示,传统滑模算法和基于模型补偿的PD算法误差收敛时间为1.4 s和2.8 s,而所提改进算法在1.3 s达到期望收敛效果,且控制精度最高,力矩平滑,具有更强的鲁棒性。

An improved reaching law sliding mode control strategy based on time delay estimation is proposed to solve the trajectory tracking control problem of a manipulator with uncertainties in its dynamic model and external disturbances. The dynamic model of the manipulator is transformed into a local model by time-delay estimation, and a sliding mode controller is designed for the local model to compensate for the time-delay estimation error;Considering the slow convergence speed and chattering of traditional sliding mode control, an improved reaching law is designed to effectively improve the dynamic response speed of the system and suppress the inherent chattering of sliding mode control. The existence and accessibility of the improved reaching law are proved theoretically. The comparative simulation results show that the error convergence time of the traditional sliding mode algorithm and the PD algorithm based on model compensation is 1.4 s and 2.8 s, while the proposed improved method achieves the desired convergence effect in 1.3 s, with the highest control accuracy, smooth torque and no chattering, and stronger robustness.