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Published on 24 January 2024
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Ma,Y. (2024). Optimization of basic PID control algorithm based on genetic algorithm and Matlab. Theoretical and Natural Science,30,178-186.
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Optimization of basic PID control algorithm based on genetic algorithm and Matlab

Yingjie Ma *,1,
  • 1 Shanghai University of Science and Technology

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2753-8818/30/20241103

Abstract

This paper investigates how to optimize the basic PID algorithm by using population genetic forms. "In traditional PID control, the tuning of PID parameters mostly relies on the experience of the tuner. The main purpose of this paper is to use an algorithm that can automatically tune its parameters to self-tune a PID controller for an actual model." Based on the principle of genetic algorithm, this paper compares the traditional PID controller tuning methods to study the trend of the PID parameters during the iteration process as well as the trend of the PID controller adaptability. Through the principle of the algorithm and the iterative output, as well as in the code set the weights occupied by different performance indicators, it can not only flexibly adjust the degree of adaptation and make the algorithm more flexible, but also prove that the use of genetic algorithms for the rectification of the PID is more adaptable and convenient, with promising research prospects

Keywords

PID algorithm, genetic algorithm, Matlab simulation

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Cite this article

Ma,Y. (2024). Optimization of basic PID control algorithm based on genetic algorithm and Matlab. Theoretical and Natural Science,30,178-186.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics

Conference website: https://www.confciap.org/
ISBN:978-1-83558-283-1(Print) / 978-1-83558-284-8(Online)
Conference date: 27 January 2024
Editor:Yazeed Ghadi
Series: Theoretical and Natural Science
Volume number: Vol.30
ISSN:2753-8818(Print) / 2753-8826(Online)

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