Fu-Kai Chang

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Based on the electromagnetism-like algorithm, an evolutionary algorithm, improved EM algorithm with genetic algorithm technique (IEMGA), for optimization of fractional-order PID (FOPID) controller is proposed in this article. IEMGA is a population-based meta-heuristic algorithm originated from the electromagnetism theory. It does not require gradient(More)
This paper introduces an improved electromagnetism-like algorithm (IEM) for recurrent fuzzy neural controller design. The hybrid IEM algorithm combines the advantages of the electromagnetism-like (EM) algorithm and the genetic algorithm (GA). The proposed IEM is composed of initialization, local search, total force calculation, movement, and evaluation. For(More)
In this paper, we propose a design method of fractional order PID controller via hybrid of electromagnetism-like (EM) algorithm and genetic algorithm (GA). The hybrid algorithm improves the performance of EM algorithm by using GA, called IEMGA. The main modification is that the randomly neighborhood local search is changed by genetic algorithm for designing(More)
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