Abstract:
One of the demerits of FLC (fuzzy logic controller) is disability in self-tuning which contribute to contingent on knowledge of experts or expert systems. In most cases, tries and errors methodology is used to tune up FLC that could be so time-consuming and may be could not lead to best response. Whereas, metaheuristic algorithms such as Cuckoo Optimization Algorithm (COA) and Particle Swarm Optimization (PSO) could identify the almost optimum parameters of FLC. COA fuzzy controller is one of the most effective methods in term of conditions which designing FLC on account of insufficient expert knowledge is so problematic. There are several controllers approach to this demand but in this paper with the help of COA, a powerful method for tuning fuzzy logic controller is considered and applied for controlling a steam condenser plant. Finally a comparative study between COA-Fuzzy, PSO-Fuzzy and PID controllers is demonstrated to verify the performance of proposed method.