Abstract
Abstract This paper describes the development and application of two different control schemes for stability enhancement of a superconducting generator (SCG). The findings of study of the system performance with an adaptive scheme and a fuzzy logic control scheme are presented and compared. In the first scheme, the stabilizing signal is based on the minimization of a modified version of a quadratic performance index, which includes an additional weighted derivative term. In the second scheme, the stabilizing signal is based on the instantaneous speed deviation and acceleration of the SCG using two fuzzy membership functions and a few simple control rules. A new tuning parameter is introduced to increase the efficiency of the fuzzy logic stabilizer. A genetic algorifimi is used to search for optimal settings of each stabilizer parameters. Simulation results show that both stabilizers are suitable for and effective in damping oscillations and enhancing system stability over a range of operating conditions.
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