The application of a fuzzy logic stabilizer to enhance the stability of a superconducting generator
(SCG) in a multi-machine power system is described. The proposed fuzzy stabilizer uses SCG
speed deviation and acceleration as input signals; The stabilizer parameters set includes the scaling
factors for input and output variables, as well as the overlap ratios of neighboring fuzzy
membership functions of input variables. Particle swarm optimization (PSO) technique is
employed lo 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.