Model predictive current controllers (MPCCs) are widely applied in motor drive control and operations. To date, however, the presence of large current errors in conventional predictive current control remains a significant predicament, due to harmonic distortions and current ripples. Naturally, noticeable current estimation inaccuracies lead to poor performance. To improve the above situation, a modulated model predictive current controller (MMPCC) is proposed for interior permanent-magnet synchronous motors (IPMSMs) in this paper. Two successive voltage vectors will be applied in a sampling period to greatly boost the number of candidate switching modes from seven to thirteen. A cost function, which is defined as the quadratic sum of current prediction errors, is employed to find an optimal switching mode and an optimized duty ratio to be applied in the next sampling period, such that the cost value is minimal. The effectiveness of the proposed method is verified through eight experiments using a TMS320F28379D microcontroller, and performance comparisons are made against an existing MPCC. In terms of quantitative improvements made to the MPCC, the proposed MMPCC reduces its current ripple and total harmonic distortion (THD) by, on average, 27.17% and 21.84%, respectively.
Design of a Robust Current Controller to Position Estimation Error for Positioning of a Sensorless Control of Interior Permanent Magnet Synchronous Motors under High-speed Drives.IEEJ Transactions on Electrical and Electronic Engineering
