Tuning of PID controllers with CMAC-based genetic algorithm

Based on cerebellar model articulation controller (CMAC), this paper attempts to propose a new chromosome representation scheme for representing real number parameters in genetic algorithms (GAs), which is termed CMAC-based GAs. The central idea of CMAC-based GAs is that each memory unit in a CMAC network is regarded as a real-valued gene in GAs. By this way, a chromosome is represented as those memory units addressed by a specific state and each gene involves partial information about a potential solution, not a potential solution as the conventional GAs. In addition, the corresponding crossover and mutation operators are also derived for the proposed GAs. The proposed CMAC-based GAs is applied to optimize the parameters of the proportional-integral-derivative controller. Simulation results are compared with several previous findings to demonstrate the search performance of the proposed method.