Low-Cost Implementation of an Adaptive Neural Network Controller for a Drive with an Elastic Shaft

This paper deals with the implementation of an adaptive speed controller applied for two electrical machines coupled by a long shaft. The two main parts of the study are the synthesis of the neural adaptive controller and hardware implementation using a low-cost system based on an STM Discovery boar...

Full description

Bibliographic Details
Main Authors: Mateusz Malarczyk, Mateusz Zychlewicz, Radoslaw Stanislawski, Marcin Kaminski
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Signals
Subjects:
Online Access:https://www.mdpi.com/2624-6120/4/1/3
Description
Summary:This paper deals with the implementation of an adaptive speed controller applied for two electrical machines coupled by a long shaft. The two main parts of the study are the synthesis of the neural adaptive controller and hardware implementation using a low-cost system based on an STM Discovery board. The framework between the control system, the power converters, and the motors is established with an ARM device. A radial basis function neural network (RBFNN) is used as an adaptive speed controller. The net coefficients are updated (online mode) to ensure high dynamics of the system and correct work under disturbance. The results contain transients achieved in simulations and experimental tests.
ISSN:2624-6120