Model Predictive Current Control of Six-Phase Induction Motor using Nine-Switch Converter

Model Predictive Control (MPC) is an automatic control strategy that generates actuations that initialize an operation, aligning the control variables with a specified desired value. This closed-loop operation involves continually revising input variable decisions based on system measurements. MPC u...

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Bibliographic Details
Main Authors: Gulbudak, Ozan, Gokdag, Mustafa, Akbaba, Mehmet
Format: Conference Proceeding
Language:English
Subjects:
Current control
FPGA
Mathematical models
Model-based control
Motors
Multiple motor control
Nine-Switch Converter
Predictive models
System dynamics
Topology
Torque
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Summary:Model Predictive Control (MPC) is an automatic control strategy that generates actuations that initialize an operation, aligning the control variables with a specified desired value. This closed-loop operation involves continually revising input variable decisions based on system measurements. MPC utilizes an explicit process model to forecast system behavior when a particular input sequence is applied in the future. Widely embraced in electrical systems and motor applications for its rapid transient characteristic, MPC excels in manipulating various closed-loop objectives and complexities. This article introduces a useful predictive control approach to minimize trajectory errors. The proposed method seeks to attain control targets with the least energy consumption. The MPC controller designed for six-phase motor control satisfies all specified requirements. Experimental results validate the proposed mathematical concept, demonstrating the stability and effectiveness of the system dynamics regulation using the proposed method. The predictive current control method is considered for operating the drive system.
ISSN:2997-7460
DOI:10.1109/KPEC61529.2024.10676217