Fractional-order PID controller optimization via improved electromagnetism-like algorithm

Ching Hung Lee*, Fu Kai Chang

*Corresponding author for this work

研究成果: Article同行評審

125 引文 斯高帕斯(Scopus)


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 calculations and can automatically converge at a good solution. For FOPID control optimization, IEMGA simulates the "attraction" and "repulsion" of charged particles by considering each controller parameters as an electrical charge. The neighborhood randomly local search of EM algorithm is improved by using GA and the competitive concept. IEMGA has the advantages of EM and GA in reducing the computation complexity of EM. Finally, several illustration examples are presented to show the performance and effectiveness.

頁(從 - 到)8871-8878
期刊Expert Systems with Applications
出版狀態Published - 十二月 2010

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