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Parameter-Free Ultralocal Model-Based Deadbeat Predictive Current Control for PMVMs Using Finite-Time Gradient Method | IEEE Journals & Magazine | IEEE Xplore

Parameter-Free Ultralocal Model-Based Deadbeat Predictive Current Control for PMVMs Using Finite-Time Gradient Method


Abstract:

Traditional ultralocal model-based predictive current control (UL-PCC) method has strong robustness on current control; however, the UL-PCC still relies on inductance to ...Show More

Abstract:

Traditional ultralocal model-based predictive current control (UL-PCC) method has strong robustness on current control; however, the UL-PCC still relies on inductance to design the controller gain, which really deteriorates its robustness on parameter. To solve it, a parameter-free ultralocal model-based deadbeat predictive current control (PF-DPCC) method using finite-time gradient method (FGM) is proposed in this article for permanent magnet vernier motor (PMVM) drives. The UL-PCC is first modified considering rotor speed without any extra parameter. Then, the impact of initial controller gain on robustness is analyzed and an extreme low duty-cycle current signal which has negligible impact on current is injected to estimate the controller gain of PF-DPCC adaptively on the basis of the deadbeat concept and the FGM. Hence, all motor parameters are not required in advance and the initial controller gain can be set as 1 directly. Then, the robustness can be effectively improved and the dependence on initial value of controller gain can be eliminated. Finally, the effectiveness and the correctness of the proposed PF-DPCC are experimentally verified on a 400-W PMVM drive platform.
Published in: IEEE Transactions on Industrial Electronics ( Volume: 70, Issue: 6, June 2023)
Page(s): 5549 - 5559
Date of Publication: 10 August 2022

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