Comparative Analysis of V/F and Vector Control of Induction Motors Using AI-Based Optimization Methods

Abstract

This paper presents a comparative analysis of scalar V/F and field-oriented control (FOC) control strategies for induction motor drives, including classical and AI-enhanced implementations. AI-based optimization is used to improve dynamic performance, energy efficiency, and robustness under various load conditions. The evaluation combines time-domain simulations with multi-objective Pareto analysis, taking into account speed-tracking accuracy, current voltage, control effort, and energy consumption. The results show that AI-enhanced controllers achieve superior trade-offs compared to conventional approaches. AI-enhanced V/F control also shows significant improvements over classical scalar control, offering a low-complexity alternative. The study demonstrates that AI effectively complements classical control structures, enabling efficient and reliable operation of induction motor drives.