Design of fuzzy power system stabilizer using adaptive evolutionary algorithm
Engineering Applications of Artificial Intelligence
LMI static output-feedback design of fuzzy power system stabilizers
Expert Systems with Applications: An International Journal
Bio-inspired fuzzy logic based tuning of power system stabilizer
Expert Systems with Applications: An International Journal
Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus (SMIB) and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.