Sadeq Ali Qasem Mohammed, Ibrahim Mohd Alsofyani, and Kyo-Beum Lee, "Improved Adaptive CCS-MPCC for Distorted Model Parameters Mitigation of IPMSM Drives," IEEE Transactions on Industrial Electronics, vol. 71, no. 4, pp. 3483-3493, Apr. 2024. -SCI > Paper

In this study, a robust adaptive model continuous-control-set model predictive current control (CCS-MPCC) method is proposed for interior permanent magnet synchronous motors (IPMSMs) considering the existing disturbances, unmodeled dynamics, and parameter variations. The novel aspect of this

research is that it merges the improved dynamic, useful properties of model predictive control (MPC), which including easy implementation and fast 

dynamic response, together with the most effective criterion of an adaptive controller (i.e., robustness to model uncertainties), that result in enhanced dynamic and steady-state control performance despite unknown and changing disturbances. Unlike the conventional CCS-MPCC approach that heavily depends on the accurate knowledge of the system model to attain improved control performance, the proposed method achieves satisfactory control performance (e.g., fast dynamic response, smaller steady-state error, and low stator current THD) by stabilizing the state errors to approach zero and

compensating for variations in the model parameters using the designed feedback control terms and adaptive control terms, respectively. The stability of the proposed control method is ensured by the state errors asymptotically decaying to zero. The proposed approach was simulated and then 

implemented on a PSIM simulation tool and a prototype IPMSM test-bench using TI TMS320F28335 DSP, respectively, to confirm its feasibility.