Robust Model Predictive Control of Permanent Magnet Synchronous Motor Under Parameter Mismatch

Permanent magnet synchronous motors (PMSMs) are essential in electromechanical systems like urban rail vehicles and wind power generation, thanks to their fast torque response and wide speed range.

Model predictive control (MPC) offers high accuracy and dynamic response, making it suitable for PMSMs. However, MPC relies on accurate motor parameters, which may vary over time, leading to mismatches that affect performance.

These mismatches can cause unstable switching frequencies and increased torque/flux ripples, becoming a common fault in PMSM systems.

This book presents improved MPC methods to enhance robustness against parameter mismatches.

It aims to help researchers understand advanced motor control strategies and assist engineers in applying these algorithms effectively to improve the operational performance of industrial motor systems.