Real‐Time Implementation of Finite Control Set Model Predictive Control for BLDC Motors With Dynamic Speed References on ESP32

ABSTRACT This paper investigates the application of Finite Control Set Model Predictive Control (FCS‐MPC) for high‐performance speed regulation of Brushless DC (BLDC) motors under dynamic operating conditions. The study addresses the challenge of precise tracking for complex references, including sinusoidal, square, triangular, and sawtooth waveforms essential for advanced applications such as robotic and hydraulic actuator systems in aerospace applications. A key contribution is the analytical investigation of the predictive cost function, which elucidates the trade‐off between inverter switching frequency and tracking accuracy. This analysis identifies an optimal weighting factor that enables a ∼55% reduction in switching frequency while maintaining dynamic tracking errors below 0.5 RPM. For experimental validation, a custom BLDC motor drive was designed and implemented using an ESP32 processor, incorporating a novel bidirectional torque‐limiting strategy for operational safety. Both simulation and experimental results confirm that the proposed approach achieves accurate dynamic speed control for frequencies up to 0.3 Hz. Furthermore, a comparative study demonstrates the superiority of the method, showing an 85% reduction in amplitude error compared to a conventional PWM‐ON strategy for a 0.3 Hz sinusoidal reference.