Passivity-Based Model-Predictive Control for the Permanent Magnet Synchronous Machine

Context: This study focuses on advanced control techniques for permanent magnet synchronous machines (PMSMs), which are crucial in various industrial applications due to their efficiency and precise control requirements. Passivity-based control methods offer stability and performance, addressing these challenges effectively. Method: A passivity-based model predictive control (MPC) is proposed, integrating port-Hamiltonian representation with optimization. Stability theorems are theoretically explored. The simulation evaluates the performance of our proposal under different prediction horizons and stability constraints. Results: The proposed MPC is analyzed across several horizons, both including and excluding passivity and exponential stability constraints. Conclusions: This study presents a novel passivity-based MPC approach for PMSM speed regulation, highlighting the importance of stability constraints. Future research should extend this controller to synchronous machines in power systems and voltage source converters.