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