It is simple, computationally "light," and incredibly well-understood. You don't need a complex mathematical model of your motor to make it work.
It requires a high-performance processor and an accurate mathematical model of the drive. If your motor parameters change (like getting hot), the model might become inaccurate. PID and Predictive Control of Electrical Drives...
Today, many engineers don't choose just one. They use or "Model-Based PID tuning," which uses predictive math to set the PID gains automatically. This offers the stability of PID with the "foresight" of predictive control. If your motor parameters change (like getting hot),
PID control has been the industry workhorse for decades. It works by calculating an "error" (the difference between where the motor is and where you want it to be) and applying a correction based on the past, present, and predicted future of that error. This offers the stability of PID with the
High-performance EV powertrains, precision robotics, and complex power electronic converters. Comparison at a Glance PID Control Predictive Control (MPC) Complexity Computation Power Significant Dynamic Response Constraint Handling Manual (Anti-windup) Model Dependency Independent Heavily Dependent The Modern Hybrid Trend