Optimal Design of a Fuzzy Logic Stabilizer For A Superconducting Generator in a Multi-Machine System Using Particle Swarm Optimozation

Abstract

This paper presents and describes an approach for the optimal design of a fuzzy logic stabilizer to enhance the stability of a superconducting generator (SCG) in a multi-machine system. The input signals to the proposed fuzzy stabilizer are the SCG speed deviation and acceleration. In this approach, unsymmetrical nonlinear membership functions are used, while number of stabilizer parameters to be properly designed is 15, including scaling factors for input and output variables along with widths and centers of fuzzy sets of input variables. Particle swarm optimization (PSO) technique is employed to search for optimal settings of the fuzzy stabilizer parameters. Simulation results show that the proposed, PSO-tuned fuzzy stabilizer provides good damping to SCG in a multi-machine environment when operating in conjunction with conventional stabilizers on other machines.