Improved Iterative Learning Control for Three-Level NPC Inverter-Fed PMSM Drives with DC-Link Balancing

Abstract

This research work designs an improved iterative learning control (ILC) with dc-link balancing capability for three-level neutral-point-clamped inverter-fed permanent magnet synchronous motors (PMSMs). Unlike the classical ILC, which depends only on information captured from the last iteration, the proposed ILC approach is capable of storing the data of the state errors from a number of preceding iterations. Henceforth, the designed control method incorporates the simple dc-link balancing algorithm. It encompasses the integration of essential dynamics, with a dual focus on achieving not only rapid dynamic response but also maintaining a satisfactory steady-state performance. The efficacy of the proposed control approach is validated by experimental findings implemented with a PSIM software package and an experimental PMSM test rig with a TMS320F28335-DSP, respectively. Therefore, the improved transient response and steady-state performance indicate that the suggested control approach outperforms the standard approach.