Segment-wise learning control for trajectory tracking of robot manipulators under iteration-dependent periods  

作　　者：Fan ZHANG Deyuan MENG Kaiquan CAI 

机构地区：[1]The Seventh Research Division,Beihang University,Beijing 100191,China [2]School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China [3]School of Electronics and Information Engineering,Beihang University,Beijing 100191,China

出　　处：《Science China(Information Sciences)》2024年第3期151-162,共12页中国科学（信息科学）（英文版）

基　　金：supported in part by National Natural Science Foundation of China (Grant Nos.U2333215,62273018);National Key Research and Development Program of China (Grant No.2021YFB2601703);Science and Technology on Space Intelligent Control Laboratory (Grant No.HTKJ2022KL502006)。

摘　　要：This paper is concerned with the amplitude boundedness problem of adaptive iterative learning control(AILC)for robot manipulators operating with iteration-dependent periods.By introducing virtual memory slots for storing historical data,a practical AILC method is proposed to achieve the segmentwise learning.This method requires less memory storage for historical information of previous iterations,especially in comparison with that of the conventional AILC methods using point-wise learning strategies.It is shown that not only the energy boundedness but also the amplitude boundedness of estimates and inputs of practical AILC can be guaranteed.Moreover,the practical AILC method can achieve the perfect tracking objective regardless of iteration-dependent periods when the robot manipulators have a persistent full learning property.In addition,a solution to the visual manipulator platform is provided and deployed based on Coppeliasim and Matlab,which helps to show the amplitude boundedness of learning results and the perfect tracking performances of the proposed practical AILC method for robot manipulators.

关 键 词：amplitude boundedness iteration-dependent period iterative learning control robot manipulator segment-wise virtual memory slot 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP273[自动化与计算机技术—控制科学与工程]