Comparison of an adaptive stabilizer and a fuzzy logic stabilizer for superconducting generator governor control

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 sche...

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Bibliographic Details
Published in:Electric power systems research 2001-03, Vol.57 (2), p.65-71
Main Authors: Saleh, R.A.F., Bolton, H.R.
Format: Article
Language:English
Subjects:
Adaptive control
Fuzzy logic control
Genetic algorithms
Superconducting generator
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Summary: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.
ISSN:0378-7796
1873-2046
DOI:10.1016/S0378-7796(01)00089-X