This research work designs a high-order iterative learning control (HO-ILC) for permanent magnet synchronous motors (PMSMs) which is fed by
a neutral-point clamped three-level inverter. Unlike the classical ILC which depends on the information captured only from one iteration, the proposed
HO-ILC approach is capable of storing the data of the state errors from a number of preceding iterations so it can prove a better tracking
performance. Apart from improving the dynamic response (i.e., smooth and quick tracking performance), it can offer a robust steady-
state response such as reduced steady-state error (ess), minimized total harmonic distortion (THD), etc., owing to the inclusion of some important
dynamics, i.e., captured stator currents errors. Therefore, the proposed method ensures both improved dynamic/steady-state control
performance, e.g., fast settling time, less THD, etc. The conducted simulation via the PSIM simulation tool validates the superiority of the proposed
approach.