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Optimized PID Controller Using Adaptive Differential Evolution with Meanof-pbest Mutation Strategy

Ti-Hung Chen1, Ming-Feng Yeh2,*

1 Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taoyuan, Taiwan, ROC
2 Department of Electrical Engineering, Lunghwa University of Science and Technology, Taoyuan, Taiwan, ROC.

* Corresponding Author: Ming-Feng Yeh, email

Intelligent Automation & Soft Computing 2020, 26(3), 407-420. https://doi.org/10.32604/iasc.2020.013917

Abstract

On the basis of JADE (adaptive differential evolution with optional external archive) and the modified differential evolution with p-best crossover (MDE_pBX), this study attempts to propose a modified mutation strategy termed "DE/(pbest)/1" for the differential evolution (DE) algorithm, where “(pbest)” represents the mean of p top-best vectors. Two modified parameter adaptation mechanisms are also proposed to update the crossover rate and the scale factor, respectively, in an adaptive manner. The DE variant with the proposed mutation strategy and two modified adaptation mechanisms is termed adaptive differential evolution with mean-of-pbest mutation strategy, denoted by ADE_pBM is comparable to or better than the four state-of-the-art adaptive DE variants in terms of accuracy, reliability and efficiency.

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APA Style
Chen, T., Yeh, M. (2020). Optimized PID controller using adaptive differential evolution with meanof-<i>p</i>best mutation strategy. Intelligent Automation & Soft Computing, 26(3), 407-420. https://doi.org/10.32604/iasc.2020.013917
Vancouver Style
Chen T, Yeh M. Optimized PID controller using adaptive differential evolution with meanof-<i>p</i>best mutation strategy. Intell Automat Soft Comput . 2020;26(3):407-420 https://doi.org/10.32604/iasc.2020.013917
IEEE Style
T. Chen and M. Yeh, "Optimized PID Controller Using Adaptive Differential Evolution with Meanof-<i>p</i>best Mutation Strategy," Intell. Automat. Soft Comput. , vol. 26, no. 3, pp. 407-420. 2020. https://doi.org/10.32604/iasc.2020.013917

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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