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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Vydáno v:IEEE transactions on systems, man, and cybernetics. Systems Ročník 53; číslo 6; s. 3461 - 3473
Hlavní autoři: Zhuang, Zhihe, Tao, Hongfeng, Chen, Yiyang, Stojanovic, Vladimir, Paszke, Wojciech
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
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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Shrnutí: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.
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2022.3225381