机器人系统有限时间自适应迭代学习控制  

Finite-Time Adaptive Iterative Learning Control for Robotic Systems

作　　者：管海娃[1,2] GUAN Haiwa(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China;Wenzhou Vocational College of Science and Technology,Wenzhou,Zhejiang 325006,China)

机构地区：[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

出　　处：《计算机工程与应用》2020年第14期231-239,共9页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61174034,No.61573320)。

摘　　要：研究任意初态下,机器人系统的有限时间自适应迭代学习控制方法。引入初始修正吸引子的概念,构造一个含有初始修正项的误差变量。针对定常机器人系统和时变机器人系统,采用Lyapunov-like方法,分别设计迭代学习控制器处理系统中不确定性。并且,采用未含/含限幅学习机制,保证闭环系统各变量的一致有界性和误差变量在整个作业区间一致收敛性。藉以实现跟踪误差在预先指定区间的完全跟踪。仿真结果验证所设计控制方法的有效性。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 Lyapunovlike 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.

关 键 词：迭代学习控制 有限时间控制 机器人系统 时变系统 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]