A modified biogeography‐based optimization algorithm based on cloud theory for optimizing a fuzzy <scp>PID</scp> controller

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.