INTELLIGENT AND ADAPTIVE CONTROL OF POWER ELECTRONIC CONVERTERS USING ARTIFICIAL INTELLIGENCE

Abstract

Power electronic converters are essential components in modern power systems, renewable energy integration, electric vehicles, and industrial drives. Conventional control strategies such as proportional–integral (PI) controllers often struggle to maintain optimal performance under nonlinear loads, parameter variations, and dynamic operating conditions. This paper presents an intelligent and adaptive control framework for power electronic converters using artificial intelligence techniques. AI-based controllers dynamically adjust control parameters to improve system stability, efficiency, and power quality. The proposed approach integrates learning capabilities to handle uncertainties and disturbances in real time. Experimental analysis demonstrates significant reduction in harmonic distortion, faster dynamic response, and improved conversion efficiency compared to traditional control methods. The results confirm that artificial intelligence enables robust and high-performance control of power electronic converters in complex operating environments.