Robust Adaptive Control Barrier Function-Based Model Predictive Speed Control for PMSM Drives With Current Safety Guarantees

Although noncascaded speed control frameworks enable fast dynamic responses, the speed regulation performance of permanent magnet synchronous motors (PMSMs) is often degraded by external loads and uncertain disturbances. This results in a critical coupling between current safety and control performance. This article develops a novel robust adaptive control barrier function (RACBF)-based model predictive speed control for PMSM drives with current safety guarantees. First, an offset-free single-loop model predictive speed controller without current constraint is designed to obtain an enhanced control performance. Then, a novel current-constrained RACBF is devised to strictly enforce current safety under disturbances without relying on overly conservative compensation, while dynamically balancing control performance based on the proximity to current limits. By embedding the RACBF constraint into the model predictive control (MPC) scheme, a synthesized model predictive speed controller is formulated. Experimental results verify that the proposed approach ensures strict current safety under disturbances while delivering superior transient performance, enhanced robustness, and reduced computational complexity.