Design of optimal Fuzzy Logic-based PID controller using Multiple Tabu Search algorithm for AGC including SMES units

This paper proposes a new optimization approach of a fuzzy logic based-proportional-integral-derivative (FLPID) controller by the multiple tabu search (MTS) algorithm for automatic generation control (AGC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the proposed optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters.