| Autor: |
Ruben Tapia-Olvera, Antonio Valderrabano-Gonzalez, Francisco Beltran-Carbajal |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 38512-38524 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3375346 |
| Popis: |
In this paper, we introduce an efficient adaptive algorithm based on B-spline neural networks for trajectory tracking of angular position for industrial induction motors. This strategy is developed in a two-axis reference frame and the regulation algorithm is based on four main stages: a) flux observer; b) internal control loop; c) determination of required electrical currents and; d) calculation of the three-phase input voltages. The strategy considers an algebraic regulation scheme based on the model. The control parameters are tuning online to attain the best dynamic behavior, besides, the proposed adaptive controller is subject to non-modeled components as an 84-pulse voltage source converter included in this study. These two aspects make the main contribution of this article. The proposed high-performance strategy for trajectory tracking of angular position is demonstrated by simulation results using the parameters of two induction motors of 500 hp and 50 hp, respectively. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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