An improved spotted hyena optimizer for PID parameters in an AVR system

An improved spotted hyena optimizer for PID parameters in an AVR system

In this paper, an improved spotted hyena optimizer (ISHO) with a nonlinear convergence factor is proposed for proportional integral derivative (PID) parameter optimization in an automatic voltage regulator (AVR). In the proposed ISHO, an opposition-based learning strategy is used to initialize the s...

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Bibliographic Details
Main Authors: Guo Zhou, Jie Li, Zhonghua Tang, Qifang Luo, Yongquan Zhou
Format: Article
Language:English
Published: AIMS Press 2020-05-01
Series:Mathematical Biosciences and Engineering
Subjects:
spotted hyena optimizer
opposition-based learning
nonlinear convergence factor
pid parameter optimization
metaheuristic
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2020211?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2020211?viewType=HTML

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