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A Virtual MPC-Based Artificial Neural Network Controller for PMSM Drives in Aircraft Electric Propulsion System | IEEE Conference Publication | IEEE Xplore

A Virtual MPC-Based Artificial Neural Network Controller for PMSM Drives in Aircraft Electric Propulsion System

Publisher: IEEE

Abstract:

Model predictive control (MPC) has great potential in PMSM drives due to the advantages of fast dynamic response and multi-variable control. However, due to its exponenti...View more

Abstract:

Model predictive control (MPC) has great potential in PMSM drives due to the advantages of fast dynamic response and multi-variable control. However, due to its exponentially increasing computational load and a large number of online calculations, it greatly increases the computational complexity and resource consumption of the microcontroller. Therefore, overcoming the barriers of computational burden has become a key point for the large-scale application of MPC strategies. This paper proposed a novel virtual MPC-based artificial neural network controller (ANN-MPC) for PWSM drives in aviation electric actuator, with the aim of reducing computational burden and improving the system control performance. Firstly, a traditional MPC controller is designed under circuit simulation to generate the input and output data for training. Next, the design of ANN-MPC controller is trained offline with massive training datasets. The ANN-MPC controller replaces the heavy online calculation of MPC controller through simple mathematical expressions, so ANN-MPC controller significantly reduces the computational burden and resource consumption. Moreover, the simulation results reveal that the proposed ANN-MPC controller have an approximate control performance compared to the conventional MPC controller.
Date of Conference: 09-14 October 2022
Date Added to IEEE Xplore: 17 November 2022
ISBN Information:

ISSN Information:

Publisher: IEEE
Conference Location: Detroit, MI, USA

References

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