Model-Free Finite-Set Predictive Current Control With Optimal Cycle Time for a Switched Reluctance Motor

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Pereira, M (Author) Other; Rui Esteves Araújo (Author) FEUP

Journal

Title: IEEE Transactions on Industrial Electronics

Vol. 70

Pages: 8355-8364

ISSN: 0278-0046

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

Other information

Authenticus ID: P-00Y-3E5

DOI: 10.1109/tie.2022.3222629

Abstract (EN): Traditional use of predictive control techniques require the knowledge of the systems model to control and the use of constant cycle-time. In the case of a switched reluctance motor its model is highly nonlinear and time-varying with current magnitude and rotor position. The use of look-up tables has been one solution, but requires a complete knowledge of the motor and mismatches from the original model used in the design can happen due temperature variation or changes in operating regimes. To address these issues as well as to increase the tracking performance of current control, a model-free predictive algorithm is developed by updating the next cycle time of the next time step of the predictive control. A new parameter estimation method is proposed that identifies the parameters of the switched reluctance model with low computational burden. Based on knowledge of the parameters at real time, not only the ideal voltage vector is applied at each cycle but the ideal time that each cycle must have is also calculated. As result, the advanced current controller requires almost no knowledge of the motor in use. The performance of the proposed schemes is validated through simulation and by a prototype experimental setup. Experimental data shows a decreasing in prediction error around 78 per cent, when comparing to the predefined model controller.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10