Design of differential evolution algorithm-based robust fuzzy logic power system stabiliser using minimum rule base

Power system stabiliser must be capable of providing appropriate stabilisation signals over a broad range of operating conditions and disturbances. Literature shows that a fuzzy logic power system stabiliser (FLPSS) is a controller to cover a wider range of operating conditions. Differential evolution algorithm technique is employed in this study to systematically tune the optimal parameters of the proposed fuzzy logic controller. The decisions in fuzzy logic approach are made by forming a series of control rules. The number of control rules to cover all possible combinations of the `m´-input variables with ´n´-membership functions will be of ´nm´ in number. But more number of rules requires more memory storage and evaluation time. In the proposed work, for a three-input each with three membership functions, the rules are reduced to three rules from 27 rules. The proposed reduced rule-based differential evolution FLPSS not only reduces the memory storage but also reduces the evaluation time. The proposed controller is designed for a linearised model of single machine infinite bus bar system under various operating conditions. The efficacy of the proposed controllers is tested on single machine connected to infinite bus for a three-phase fault and also in multi-machine environment.