磁浮定位系統之適應性類神經控制設計

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Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/30301

Title:	磁浮定位系統之適應性類神經控制設計 Adaptive neural control of a magnetic levitation system
Authors:	範青風 Phong, Pham Thanh
Contributors:	機械工程學系數位機電碩士班
Keywords:	magnetic levitation system sliding mode control smooth switching neural network
Date:	2015-06
Issue Date:	2015-08-19 14:17:52 (UTC+8)
Abstract:	This thesis considers the position-tracking problem of a magnetic levitation system in the presence of modeling errors due to uncertainties of physical parameters. First, a dynamic model of the magnetic levitation system is derived. Then, a smooth switching adaptive robust control is proposed. The controller consists of three part, an adaptive linearizing controller using RBFN, robust controller, and an smooth function to switch between the above two controllers . The proposed controller improves the tracking performance and avoids the so-called control singularity occurred in a standard adaptive linearizing controller. Both simulation and experiments are carried out to verify the proposed method.
Appears in Collections:	[Department of Mechanical Engineering ] thesis

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