Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System

For the nonlinear discrete-time system, higher-order iterative learning control (HOILC) with optimal control gains based on evolutionary algorithm (EA) is developed in this paper. Since the updating actions are constituted by the tracking information from several previous iterations, the suitably de...

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Main Authors: Yun-Shan Wei, Xiaofen Yang, Wenli Shang, Ying-Yu Chen
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/4281006
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author Yun-Shan Wei
Xiaofen Yang
Wenli Shang
Ying-Yu Chen
author_facet Yun-Shan Wei
Xiaofen Yang
Wenli Shang
Ying-Yu Chen
author_sort Yun-Shan Wei
collection DOAJ
description For the nonlinear discrete-time system, higher-order iterative learning control (HOILC) with optimal control gains based on evolutionary algorithm (EA) is developed in this paper. Since the updating actions are constituted by the tracking information from several previous iterations, the suitably designed HOILC schemes with appropriate control gains usually achieve fast convergence speed. To optimize the control gains in HOILC approach, EA is introduced. The encoding strategy, population initialization, and fitness function in EA are designed according to the HOILC characteristics. With the global optimization of EA, the optimal control gains of HOILC are selected adaptively so that the number of convergence iteration is reduced in ILC process. It is shown in simulation that the sum absolute error, total square error, and maximum absolute error of tracking in the proposed HOILC based on EA are convergent faster than those in conventional HOILC.
format Article
id doaj-art-f1421db0a3dc45a2a247e21b53fe5a5c
institution Kabale University
issn 1099-0526
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-f1421db0a3dc45a2a247e21b53fe5a5c2025-02-03T01:04:16ZengWileyComplexity1099-05262021-01-01202110.1155/2021/4281006Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear SystemYun-Shan Wei0Xiaofen Yang1Wenli Shang2Ying-Yu Chen3School of Electronics and Communication EngineeringSchool of Mechanical and Electric EngineeringSchool of Electronics and Communication EngineeringSchool of Electronics and Communication EngineeringFor the nonlinear discrete-time system, higher-order iterative learning control (HOILC) with optimal control gains based on evolutionary algorithm (EA) is developed in this paper. Since the updating actions are constituted by the tracking information from several previous iterations, the suitably designed HOILC schemes with appropriate control gains usually achieve fast convergence speed. To optimize the control gains in HOILC approach, EA is introduced. The encoding strategy, population initialization, and fitness function in EA are designed according to the HOILC characteristics. With the global optimization of EA, the optimal control gains of HOILC are selected adaptively so that the number of convergence iteration is reduced in ILC process. It is shown in simulation that the sum absolute error, total square error, and maximum absolute error of tracking in the proposed HOILC based on EA are convergent faster than those in conventional HOILC.http://dx.doi.org/10.1155/2021/4281006
spellingShingle Yun-Shan Wei
Xiaofen Yang
Wenli Shang
Ying-Yu Chen
Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
Complexity
title Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
title_full Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
title_fullStr Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
title_full_unstemmed Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
title_short Higher-Order Iterative Learning Control with Optimal Control Gains Based on Evolutionary Algorithm for Nonlinear System
title_sort higher order iterative learning control with optimal control gains based on evolutionary algorithm for nonlinear system
url http://dx.doi.org/10.1155/2021/4281006
work_keys_str_mv AT yunshanwei higherorderiterativelearningcontrolwithoptimalcontrolgainsbasedonevolutionaryalgorithmfornonlinearsystem
AT xiaofenyang higherorderiterativelearningcontrolwithoptimalcontrolgainsbasedonevolutionaryalgorithmfornonlinearsystem
AT wenlishang higherorderiterativelearningcontrolwithoptimalcontrolgainsbasedonevolutionaryalgorithmfornonlinearsystem
AT yingyuchen higherorderiterativelearningcontrolwithoptimalcontrolgainsbasedonevolutionaryalgorithmfornonlinearsystem