Adaptive Model-Free Predictive Current Control of SPMSM Using Cascade Extended State Observers for Enhanced Disturbance Rejection

The conventional model-free predictive current control combined with extended state observer (MFPCC-ESO) is the widely used method in motor driving systems due to its straightforward implementation and high robustness performance. However, measurement noise significantly degrades its performance. To evaluate the performance of the proposed MFPCC with a cascade ESO (CESO), comparative tests were conducted under various operating conditions, including different speeds and loads, as well as nominal and parameter mismatch scenarios. First, the proposed method significantly enhances noise suppression and improves disturbance estimation and rejection capabilities compared to the conventional MPCC. Second, it achieves lower current THD and reduced dynamic overshoot, which indicates enhanced steady-state and dynamic performance, respectively. Finally, a two-level CESO is designed to achieve high-precision estimation of aperiodic disturbances and to reduce the steady-state estimation error of periodic harmonics. Furthermore, the proposed MFPCC-CESO for surface-mounted permanent magnet synchronous motors (PMSMs) eliminates the dependence on motor parameters, requires minimal parameter tuning, and reduces computational time. In conclusion, experimental results validate the effectiveness of the proposed method.