Computationally Efficient Model Predictive Torque Control of Permanent Magnet Synchronous Machines Using Numerical Techniques

Abstract

This study presents a computationally efficient model predictive torque control (MPTC) method for permanent magnet synchronous machines (PMSMs). The existing MPTC methods require solving complex optimization problems in iterations; this approach is computationally demanding. In contrast, the proposed MPTC transforms the optimization problem into two subproblems and derives the corresponding solutions explicitly using numerical techniques, which entail linearization of the torque function and current constraint; the proposed approach can significantly reduce the computational burden. Additionally, the proposed MPTC does not involve any control gains and weighting factors; hence, gain tuning is not required for the proposed MPTC. These features are advantageous when implementing torque control. Using a 4-kW PMSM drive, the effectiveness of the proposed MPTC is demonstrated both numerically and experimentally in terms of dynamic performance and computational efficiency. This is realized by comparing the proposed method with the existing methods.