Constrained MIMO Reference-Based Offline Steady–State (RBOSS) NMPC for PMSM using Voltage Source Inverter

This research introduces a constrained MIMO Reference-Based Offline Steady-State (RBOSS) Nonlinear Model Predictive Control (NMPC) approach for Permanent Magnet Synchronous Motors (PMSM) to address the overlooked aspect of starting conditions in current and speed multi-objective controllers. By employing an offline predictive optimisation technique, the study aims to improve the starting condition for the optimisation process, thus facilitating faster convergence. The RBOSS NMPC precomputes steady-state values of PMSM motors across a range of reference speeds, which are then used as starting conditions via a lookup table during online optimisation. The approach significantly reduces computational burden by ۳۰% compared to the usual successive linearization technique; it also enhances performance parameters such as rise time and settling time while optimizing current usage. This method demonstrates potential adaptability to other nonlinear systems, marking a significant advancement in NMPC controller optimisation techniques and suggesting further exploration to expand its applicability.

Keywords:

PMSM (Permanent Magnet Synchronous Motors) , NMPC (Nonlinear Model Predictive Control) , RBOSS (Reference Based Offline Steady-State) , Optimization , Starting Conditions , Computational Burden