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Memory-Based Model Predictive Control for Parameter Detuning in Multiphase Electric Machines
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DOI：10.1109/TPEL.2023.3328427.png)
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Abstract
En 中文
Model predictive control (MPC) is a popular control technique to regulate multiphase electric drives (EDs). Despite the well-known advantages of MPC, it is sensitive to parameter detuning and lacks the capability to eliminate steady-state errors. The appearance of an offset between the reference and measured currents can significantly jeopardize the performance of the ED. This article suggests the use of a memory-based model predictive control (MB-MPC) that activates a compensation term when the parameter mismatch is detected. The suggested MB-MPC is universal for any multiphase machine if spatial harmonics are neglected since the proposed method does not consider any of the secondary x-y planes. Experimental results in two different rigs with six- and nine-phase induction motors prove this universality as well as its capability to eliminate current and speed offsets.
Keywords:
Model predictive control (MPC)
multiphase electric drives (EDs)
parameter mismatch compensation
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