An Optimal Iterative Learning Control Approach for Linear Systems With Nonuniform Trial Lengths Under Input Constraints

In practical applications of iterative learning control (ILC), the repetitive process may end up early by accident during the performance improvement along the trial axis, which yields the nonuniform trial length problem. For such practical systems, input signals are usually constrained because of s...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems Jg. 53; H. 6; S. 3461 - 3473
Hauptverfasser:	Zhuang, Zhihe, Tao, Hongfeng, Chen, Yiyang, Stojanovic, Vladimir, Paszke, Wojciech
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Constraint handling Constraints Convergence Design methodology Input constraint iterative learning control (ILC) Iterative methods Learning Linear systems nonuniform trial length primal–dual interior point method Process control Trajectory Uncertainty
ISSN:	2168-2216, 2168-2232
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Abstract	In practical applications of iterative learning control (ILC), the repetitive process may end up early by accident during the performance improvement along the trial axis, which yields the nonuniform trial length problem. For such practical systems, input signals are usually constrained because of some certain physical limitations. This article proposes an optimal ILC algorithm for linear time-invariant multiple-input-multiple-output (MIMO) systems with nonuniform trial lengths under input constraints. The optimal ILC framework is specifically modified for the nonuniform trial length problem, where the primal-dual interior point method is introduced to deal with the input constraints. Hence, the constraint handling capability are improved compared with the conventional counterparts for nonuniform trial lengths. Also, the monotonic convergence property of the proposed optimal ILC algorithm is obtained in the sense of mathematical expectation. Finally, the effectiveness of the proposed algorithm is verified on the numerical simulation of a mobile robot.
AbstractList	In practical applications of iterative learning control (ILC), the repetitive process may end up early by accident during the performance improvement along the trial axis, which yields the nonuniform trial length problem. For such practical systems, input signals are usually constrained because of some certain physical limitations. This article proposes an optimal ILC algorithm for linear time-invariant multiple-input-multiple-output (MIMO) systems with nonuniform trial lengths under input constraints. The optimal ILC framework is specifically modified for the nonuniform trial length problem, where the primal-dual interior point method is introduced to deal with the input constraints. Hence, the constraint handling capability are improved compared with the conventional counterparts for nonuniform trial lengths. Also, the monotonic convergence property of the proposed optimal ILC algorithm is obtained in the sense of mathematical expectation. Finally, the effectiveness of the proposed algorithm is verified on the numerical simulation of a mobile robot.
Author	Chen, Yiyang Zhuang, Zhihe Tao, Hongfeng Paszke, Wojciech Stojanovic, Vladimir
Author_xml	– sequence: 1 givenname: Zhihe orcidid: 0000-0003-0811-9519 surname: Zhuang fullname: Zhuang, Zhihe email: 6191905054@stu.jiangnan.edu.cn organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China – sequence: 2 givenname: Hongfeng surname: Tao fullname: Tao, Hongfeng email: taohongfeng@jiangnan.edu.cn organization: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China – sequence: 3 givenname: Yiyang orcidid: 0000-0001-9960-9040 surname: Chen fullname: Chen, Yiyang email: yychen90@suda.edu.cn organization: School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China – sequence: 4 givenname: Vladimir orcidid: 0000-0002-6005-2086 surname: Stojanovic fullname: Stojanovic, Vladimir email: vladostojanovic@mts.rs organization: Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering, University of Kragujevac, Kraljevo, Serbia – sequence: 5 givenname: Wojciech surname: Paszke fullname: Paszke, Wojciech email: w.paszke@iee.uz.zgora.pl organization: Institute of Automation, Electronic and Electrical Engineering, University of Zielona Góra, Zielona Góra, Poland
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Snippet	In practical applications of iterative learning control (ILC), the repetitive process may end up early by accident during the performance improvement along the...
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SubjectTerms	Algorithms Constraint handling Constraints Convergence Design methodology Input constraint iterative learning control (ILC) Iterative methods Learning Linear systems nonuniform trial length primal–dual interior point method Process control Trajectory Uncertainty
Title	An Optimal Iterative Learning Control Approach for Linear Systems With Nonuniform Trial Lengths Under Input Constraints
URI	https://ieeexplore.ieee.org/document/9979725 https://www.proquest.com/docview/2814543175
Volume	53
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