Efficient Adaptive Regulation Strategy for Control Position of Induction Motors

• Published in: IEEE access Vol. 12; pp. 38512 - 38524
• Main Authors: Tapia-Olvera, Ruben, Valderrabano-Gonzalez, Antonio, Beltran-Carbajal, Francisco
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive algorithms; Adaptive control; Adaptive regulation; Angular position; angular position trajectory tracking; Angular velocity; efficient driver; high performance; Induction motors; Inverters; Mathematical models; Motors; Neural networks; Parameters; Position control; Rotors; Splines (mathematics); Tracking
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3375346

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.