Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (14): 231-239.DOI: 10.3778/j.issn.1002-8331.1904-0406

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Finite-Time Adaptive Iterative Learning Control for Robotic Systems

GUAN Haiwa   

  1. 1.College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
    2.Wenzhou Vocational College of Science and Technology, Wenzhou, Zhejiang 325006, China
  • Online:2020-07-15 Published:2020-07-14



  1. 1.浙江工业大学 信息工程学院,杭州 310023
    2.温州科技职业学院,浙江 温州 325006


This paper presents a finite-time adaptive iterative learning control for robotic systems under arbitrary initial state error. With the concept of initial rectified attractor being introduced, an error variable with an initial rectify term is constructed. The constant robotic system and time-varying robotic system are respectively considered. Based on Lyapunov-like function, accordingly, iterative learning controllers are designed for handling the uncertainties. By applying the unsaturated/ saturated learning mechanisms, the error variable would uniformly converge to zero over the entire time  interval as iteration increase, thereby the  tracking error would achieve practical complete tracking  over a pre-specified interval, while the uniform boundness of all variable in the closed-loop system can be guaranteed. Effectiveness of the proposed control method is demonstrated by numerical simulation.

Key words: iterative learning control, finite-time control, robotic systems, time-varying systems



关键词: 迭代学习控制, 有限时间控制, 机器人系统, 时变系统