Robust Hybrid Current Control Approach for IPMSM Drives Subjected to System Uncertainty - Mohammed, Sadeq Ali Qasem; Al-Kaf, Hasan Ali Gamal; Lee, Kyo Beum (IEEE Transactions on Industrial Electronics, 2024)
A robust hybrid current control approach is designed in this research work which merges an adaptive control law and iterative learning control law to overcome the system uncertainty of interior-mounted permanent magnet synchronous motor (IPMSM) drives. The former adaptive control law is employed in the steady-state condition, and the ILC law is used exclusively in the transient condition. Compared with the traditional hybrid control approaches, the proposed method combines the adaptive control's resilience against system uncertainty with maintaining a better tracking capability, i.e., better dynamic as well as steady-state control qualities (e.g., fast dynamic response, smaller steady-state error, lower total harmonic distortion [THD], etc.) irrespective of changing perturbations. The stability analysis is then ensured mathematically by the convergence of the current state error goes to zero. The proposed approach's effectiveness is confirmed by experimental findings acquired with an experimental IPMSM test rig employing the TMS320F28335-DSP, respectively. As a result, the improved transient response and steady-state performance indicate that the suggested control approach outperforms the standard approach.
Keywords: Adaptive Control; Control approach; Hybrid controls; Iterative learning; Iterative learning current control; Perturbation method; Robustness against system uncertainty; Steady state; System uncertainties; Uncertainty; Adaptive control; hybrid control; iterative learning current control; robustness against system uncertainty