文献类型：期刊文献

英文题名：A modified biogeography-based optimization algorithm based on cloud theory for optimizing a fuzzy PID controller

作者：Li, Xiang[1];Chen, Jianjun[1];Zhou, Dingshan[2];Gu, Qingdong[3]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai 200237, Peoples R China;[2]Suzhou Aude High End Equipment Co Ltd, Suzhou, Peoples R China;[3]PetroChina, Huabei Oilfield Co, Engn Technol Res Inst, Renqiu, Peoples R China

年份：2022

卷号：43

期号：3

起止页码：722

外文期刊名：OPTIMAL CONTROL APPLICATIONS & METHODS

收录：;EI(收录号：20220311463546);WOS:【SCI-EXPANDED(收录号:WOS:000741488300001)】；

基金：This work was financially supported by the National Natural Science Foundation of China (No. 51675182).

语种：英文

外文关键词：BBO; benchmark functions testing; cloud theory; fuzzy PID controller

摘要：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 degrees C-die heater to demonstrate its practical application value.