Adaptive sliding mode control of chaos in permanent magnet synchronous motor via fuzzy neural networks
type: Item
instance of: scholarly article
title: Adaptive sliding mode control of chaos in permanent magnet synchronous motor via fuzzy neural networks
zbMATH Open document ID: 1407.93173
DOI: 10.1155/2014/868415
author: Tat-Bao-Thien Nguyen
author: Teh-Lu Liao
author: Jun-Juh Yan
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM) drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.
Mathematics Subject Classification ID: 93C40
Mathematics Subject Classification ID: 34H10
Mathematics Subject Classification ID: 93C42
zbMATH DE Number: 7017484
Wikidata QID: Q59070261
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/868415
OpenAlex ID: W2048601044
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description: scientific article; zbMATH DE number 7017484