FPGA-Based Predictive Control Enhancement for Induction Generators in Wind Energy Conversion Systems: Experimental Validation

This paper introduces a Field-Programmable Gate Array-based predictive control strategy to improve the performance of induction generators in wind energy systems. The proposed method uses Finite Set Model Predictive Control to optimize system behavior in real-time. The strategy is designed to enhance tracking accuracy, minimize harmonic distortion, and speed up response times. The effectiveness of the proposed approach is validated through simulations in MATLAB/SIMULINK, followed by experimental testing on a dedicated test bench. The results demonstrate that the controller delivers low root mean square error and maintains total harmonic distortion below the 5% grid compliance threshold, providing a reliable solution for modern renewable energy applications. Control Diagram of Finite Set Control (FSC)✓ Enhanced control strategy for DFIG-based wind systems: Introduction of a novel Predictive Control method using Finite Set Model Predictive Control (FSC) to improve performance and robustness. ✓ Improved power quality: Achieves low Total Harmonic Distortion (THD) below 5% grid compliance threshold. ✓ Superior dynamic performance : Reduces response time and tracking errors while maintaining system stability.✓ Validated through simulations and experiments : MATLAB/SIMULINK and test bench experiments confirm low RMSE and fast response✓ Comprehensive analysis provided: Includes system modeling , FSC fundamentals, application to wind energy conversion, and detailed result discussion. • Novel control strategy: FPGA-based Finite Set Predictive Control proposed for DFIG wind energy systems. • Improved power quality: THD maintained below the 5% grid compliance threshold. • Superior dynamic performance: Response time and tracking errors reduced while maintaining system stability. • Experimental validation: Simulation and test bench results confirm low RMSE and fast dynamic response. • Comprehensive coverage: System modeling, FSC design, WECS application, and performance evaluation.