基于布谷鸟算法的工业机器人轨迹跟踪控制

Trajectory Tracking Control for an Industrial Robot Based on Cuckoo Search Algorithm

研究SCARA工业机器人在关节空间内的轨迹跟踪控制问题。实际应用中,系统的未建模特性、关节摩擦间隙和未知负载等因素将引起机器人动力学性能的变化,从而影响其轨迹跟踪控制;并且外界扰动也会增加机器人轨迹跟踪控制的难度。针对上述问题,提出一种基于布谷鸟算法优化的快速连续非奇异终端滑模控制策略。该方法利用布谷鸟算法寻优机制规划机器人的参考轨迹;控制策略在李亚普诺夫稳定性理论的支撑下,采用连续非奇异终端滑模面来补偿与抑制系统的不确定性与外界扰动,引入快速终端滑模趋近律来加快系统的响应速度,并结合Anti-Windup技术来补偿系统中死区等其他非线性因素。通过李亚普诺夫稳定性理论,证明机器人系统的轨迹跟踪误差全局稳定。最后,通过轨迹跟踪试验验证了此方法的有效性。

The trajectory tracking control of a SCARA industrial robot in joint space was studied. In general, system unmodeled dynamics, joint friction and gap, and unknown load will lead to change of the robot dynamic performance, which will affect the robot trajectory tracking performance, and so does the external disturbances.Aiming at this issue, a fast nonsingular terminal sliding mode control strategy based on cuckoo search algorithm was proposed.In this method, the optimal mechanism of cuckoo search algorithm was used for trajectory planning.Under the framework of Lyapunov stability theory, the fast nonsingular terminal sliding mode surface was adopted to compensate and restrain the unmodeled dynamics and external disturbances, and the fast terminal sliding mode was introduced to improve the response speed. Meanwhile, an Anti-Windup technique was proposed to compensate the nonlinear factors of the deadzone in the system.According to Lyapunov stability theory, it is proved that the system trajectory tracking error is global stable. The effectiveness of the proposed approach is tested through a trajectory tracking experiment.