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.
|Number of pages||8|
|Publication status||Published - 2012 Dec 1|
|Event||2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan|
Duration: 2012 Nov 16 → 2012 Nov 18
|Other||2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012|
|Period||12-11-16 → 12-11-18|
All Science Journal Classification (ASJC) codes