PreprintArticleVersion 1This version is not peer-reviewed
A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System
Version 1
: Received: 4 October 2024 / Approved: 7 October 2024 / Online: 7 October 2024 (17:41:01 CEST)
How to cite:
Costin, M.; Bivol, I. A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System. Preprints2024, 2024100516. https://doi.org/10.20944/preprints202410.0516.v1
Costin, M.; Bivol, I. A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System. Preprints 2024, 2024100516. https://doi.org/10.20944/preprints202410.0516.v1
Costin, M.; Bivol, I. A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System. Preprints2024, 2024100516. https://doi.org/10.20944/preprints202410.0516.v1
APA Style
Costin, M., & Bivol, I. (2024). A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System. Preprints. https://doi.org/10.20944/preprints202410.0516.v1
Chicago/Turabian Style
Costin, M. and Ion Bivol. 2024 "A New Paradigm in AC Drive Control: Data Driven Based Control by Learning of the High Efficiency Data Set. Generalizations and Applications to a PMSM Drive Control System" Preprints. https://doi.org/10.20944/preprints202410.0516.v1
Abstract
This paper presents a new means to control the processes, which involve the electric energy conversion. Electric machines fed by electronic converters provide the useful power defined by the inner product of two generalized energetic variables: the effort and the speed. The novelty of the paper idea is to control the desired energetics variables by a direct Data Driven Control (DDC) law in terms of the pair effort, speed and corresponding voltage controls of the electronic converter. It must be mentioned that the same desired useful power might be obtained with different controls at different efficiencies. The regularization problem was solved by selecting from a knowledge database, the maximum efficiency operation points. Knowing a reasonable number of optimal efficiency operation points, an interpolative Radial Base Function (RBF) control was built up. The RBF algorithm can find by interpolation the optimal controls for any admissible operation points of the process. The control scheme developed for this purpose has an inner DDC loop, that perform the converter control based on measured speed and demanded torque by the outer loop which handles the speed. A comparison of the DDC with the Model Predictive Control (MPC) schemas highlights the advantages of the new proposed control.
Keywords
data driven control (DDC); model predictive control (MPC); permanent magnet synchronous machine (PMSM); searching algorithm; radial basis function (RBF) neural networks (NN); interpolation technique
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
