Adaptive iterative learning PID control based on Markov parameter tuning

被引：0
|
作者：
Yin J.-H. [1 ]
Bo C.-M. [1 ]
Liu Y.-P. [1 ]
Yang L. [1 ]
机构：
[1] College of Electrical Engineering and Control Science, Nanjing University of Technology, Nanjing
来源：
Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities | 2019年 / 33卷 / 06期
关键词：
Iterative learning control; Markov tuning; PID control; Single neuron adaptive mechanism;
D O I：
10.3969/j.issn.1003-9015.2019.06.026
中图分类号：
学科分类号：
摘要：
Parameters of semi-batch processes often varies with time. A single neuron adaptive PID iterative learning control strategy based on Markov parameter tuning was investigated in this study. A two-dimensional iterative learning PID controller (2D-ILC-PID) was first established, and the initial values of the parameters were tuned offline by the Markov parameter method. The controller parameters were adaptively adjusted online by single neuron adaptive adjustment mechanism. The algorithm can make full use of the repeating information between batches and improve the iterative learning rate, and achieve effective improvement of the control performance. The control method was verified by a simulated reaction process, and the results show that the single neuron adaptive iterative learning control method based on Markov parameter tuning can effectively achieve accurate tracking of reaction temperature. © 2019, Editorial Board of "Journal of Chemical Engineering of Chinese Universities". All right reserved.
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页码：1490 / 1498
页数：8
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