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 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.