Modelling Reactive Power Compensation with Adaptive Neuro-Fuzzy Inference
Amara Chen
Corresponding
Dhaka University of Engineering & Technology
Kavita García
University of Cape Town
Kwame Saleh
Dhaka University of Engineering & Technology
Abstract
Both academic and industrial communities have shown growing interest in optimising reactive power compensation for industrial automation. The governing equations of the problem were formulated and then solved numerically by means of adaptive neuro-fuzzy inference. The proposed controller shortened the settling time by roughly 47% compared with a conventional design. The results support the adoption of the proposed method in routine engineering practice.
Keywords:
reactive power compensationadaptive neuro-fuzzy inferenceshape memory alloyarsenic removal
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