Development of Neuroxellar Algorithms for Adaptive Pi Adjustable Speed Control Parameters in Mining
Journal Title: International Journal of Multidisciplinary Research and Analysis - Year 2022, Vol 5, Issue 08
Abstract
This article discusses the adaptive Pi regulator based on the basic function of a neural network (RBF) and it is used to control the velocity of a vector directional asynchronous motor. The structure of the control circuit consists of the RBF identifier of the standard Pi controller. The RBF Identifier is used to identify the Jacobian meaning of the asynchronous motor online. The "online" change of neural network parameters is performed by the gradient access method without prior training. Pi controller training is performed by using the "online" identification RBF model. It is advisable to test this controller under different conditions to finally make sure the reliability of the management technology we offer. Research has shown that the proposed controller provides good steadiness and stability of the steering system compared to what a conventional Pi controller provides.
Authors and Affiliations
Maia Kevkhishvili, Valida Sesadze, Gela Chikadze, Marina Shengelia
Keywords
Related Articles
- EP ID EP708691
- DOI 10.47191/ijmra/v5-i8-10
- Views 134
- Downloads 0
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