A modified biogeography‐based optimization algorithm based on cloud theory for optimizing a fuzzy PID controller. (12th January 2022)

• Record Type: Journal Article
• Authors: Li, Xiang; Chen, Jianjun; Zhou, Dingshan; Gu, Qingdong
• Other Names: Wang Hong guestEditor.; Yang Fuwen guestEditor.
• Is Part Of: Optimal control applications and methods. Volume 43:Number 3(2022)
• Page Start: 722
• Page End: 739
• Publication Date: 2022-01-12
• Subjects: BBO -- benchmark functions testing -- cloud theory -- fuzzy PID controller; Control theory -- Periodicals; Mathematical optimization -- Periodicals; 629.8312
• DOI: 10.1002/oca.2848
• Languages: English
• ISSNs: 0143-2087

Abstract

Abstract: In recent years, the heuristic algorithms used to improve the PID controller have attracted increasing attention. Additionally, there have been many significative explorations into the field of the fuzzy PID controller. Therefore, this article presents a modified biogeography‐based optimization (BBO) algorithm to optimize the fuzzy PID controller. We utilize cloud theory to adapt migration operator and mutation operator of the BBO algorithm to enhance its exploration ability and exploitation ability for better convergence speed and accuracy. The final algorithm is called cloud theory‐biogeography‐based optimization algorithm (CTBBO). The great performance of the CTBBO algorithm is illustrated in the benchmark functions testing compared with other heuristic algorithms. Lastly, the CTBBO algorithm was used in an engineering case—optimizing the fuzzy PID controller in a 180°C‐die heater to demonstrate its practical application value.