It struggles with "multi-variable" systems (like controlling torque and flux simultaneously) and doesn't handle physical limits—like voltage saturation—very gracefully.
It is simple, computationally "light," and incredibly well-understood. You don't need a complex mathematical model of your motor to make it work. PID and Predictive Control of Electrical Drives...
In the world of electrical drives—the systems that power everything from industrial robots to electric vehicles—choosing the right control strategy is a high-stakes decision. Two heavyweights dominate the landscape: the classic control and the advanced Model Predictive Control (MPC) . 1. The Reliable Classic: PID Control In the world of electrical drives—the systems that
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. The Reliable Classic: PID Control It requires a
MPC is the "smart" alternative. Instead of reacting to errors, MPC uses a mathematical model of the electrical drive to predict its future behavior over a specific time horizon. It then chooses the optimal control action to minimize a "cost function."
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.