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It has been established beyond reasonable doubt that a reliable voltage control in power system requires a controller, however the best controller to use in such operation depends on how resilient it is to parametric uncertainties. Thus, the controller has to be robust enough such that unexpected changes in the dynamics would not result in system exceeding requirement or not meeting intent, this necessitate secure, fully flexible and reliable controller that can fine-tune and synchronize the system with precision even on real time for improving resilience with control and coordination. Consequently, in this work an intelligent adaptive neuro-fuzzy inference system (ANFIS) controller trained using hybrid optimization techniques is explored from the point of view of robustness in a model of automatic voltage regulation (AVR). The exceptional transients acquired in all operation under distinct perturbation and/or parameter specification transcend those offered by other techniques considered in this study. Moreover, the worst case scenario analysis demonstrate further the strong performance of the technique to stochasticity, thus the technique is robust enough to be applied for enhancing power system with same or similar specifications.
Mohammed et al. (2024) studied this question.