АННОТАЦИЯ
Classical model-free predictive current control (MFPCC) is a robust control technique for a two-level inverter-fed induction motor drive, with advantages that consist of a simple concept, rapid response, simple implementation, and excellent performance. However, the classic finite-control-set MFPCC still exhibits a significant current ripple. This article presents a method to enhance performance using a combination of model-free predictive current control (MFPCC) and discrete space vector modulation (DSVM). The MFPCC employs an ultra-local model with an extended state observer (ESO) that does not consider motor parameters, thereby improving the control system's reliability by eliminating the parameter dependency. The proposed method integrates DSVM, which divides a single sample period into N equal intervals and generates vir-tual vectors to reduce stator current ripple. It achieves the minimum cost function value across the entire operating range of the induction motor (IM) drive by selecting the optimal vector from the limited set of permissible voltage vectors. Using DSVM effectively reduces the total harmonic distortion (THD) without any detrimental effects during transients or steady states. Experimental studies validate the effectiveness and superiority of the suggested technique over the Finite Control Set (FCS) MFPCC, which only considers the real voltage vectors in its compu-tations.
ЦИТАТА
DSVM-based Model Free Predictive Current Control of Induction Motor / M.A. Hussain, A.S. Hati, P. Chakrabarti, B.T. Hung, V.E. Bolshev, V.A. Panchenko // Energies. – 2023. – Т. 16. – № 15. – P. 5657
