Hybrid clonal selection algorithm and the artificial bee colony algorithm for a variable PID-like fuzzy controller design

In this paper, a novel evolutionary learning algorithm is proposed by hybridizing the clonal selection algorithm (CLONALG) and the artificial bee colony algorithm (ABC). The algorithm is thus called HCABC to enhance the CLONALG performance. This algorithm presents a new idea to optimize the parameter and structure of the PID-like fuzzy controller simultaneously. The ABC algorithm has been proven to be very effective for solving global optimization. Hence, in the HCABC, the mutation mechanism of the CLONALG by using the advantages of ABC can improve the capabilities of exploration and ex-ploitation. Simulation results demonstrate that HCABC can effectively achieve the best PID-like fuzzy controller structure and parameters to a nonlinear and uncertainty control plant.