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2R1T并联机器人滑模自适应迭代学习控制OA北大核心CSTPCD

Adaptive Sliding-mode Iterative Learning Control for 2R1T Parallel Robots

中文摘要英文摘要

针对具有两转一移自由度的并联机器人的重复性加工轨迹跟踪精度问题,提出了一种滑模—自适应—迭代学习控制方案.具体而言,采用迭代学习控制来提高轨迹控制的精度,引入滑模控制来增强控制系统的鲁棒性,并采用自适应控制来处理系统内在的不确定性,降低了滑模控制中切换项引起的振荡问题.进一步,通过Bellman-Gronwall定理与λ范数证明了控制系统的收敛性.通过设计类李雅普诺夫函数证明了控制系统的稳定性.最后,进行控制方案的数值仿真以及真机实验,验证了所提出的控制方案能够有效提升两转一移类并联机构的控制精度以及系统鲁棒性.在该控制算法下,并联机器人关节空间的平均误差、最大误差及标准差相比于PD控制方法降低了 59.5%、55.1%和 60.1%.

To solve the tracking accuracy problem in repetitive machining of parallel robots with 2 rotational and 1 transla-tional(2R1T)degrees of freedom(DOFs),an adaptive sliding-mode iterative learning control scheme is proposed.Specifical-ly,an iterative learning control method is adopted to improve the trajectory control accuracy,a sliding-mode control algorithm is introduced to enhance the robustness of the control system,and the adaptive control method is employed to deal with the intrinsic uncertainty of the control,therefore,overcoming the oscillation problem caused by switching terms in sliding-mode control.Furthermore,the convergence of the proposed control system is proved by Bellman-Gronwall theorem and λ-norm.The stability of the proposed control system is validated through designing a Lyapunov-like function.Finally,numerical sim-ulations and prototype experiments are carried out to verify the proposed control scheme.The experimental results show that the proposed control scheme can significantly improve the control accuracy and the system robustness of the 2R1T parallel robots.Under this control algorithm,the mean error,maximum error and standard deviation of the joint space of the parallel robot are reduced by 59.5%,55.1%and 60.1%compared with the PD(proportional-derivative)control method.

周博文;张海峰;李秦川

浙江理工大学机械工程学院,浙江杭州 310018

迭代学习控制2R1T并联机器人滑模控制自适应控制

iterative learning control2R1T parallel robotsliding-mode controladaptive control

《机器人》 2024 (003)

大型航空结构件高效加工并联机器人设计理论与方法

317-329 / 13

国家自然科学基金(51935010).

10.13973/j.cnki.robot.230283

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