Intelligent nonsingular terminal sliding-mode control using MIMO elman neural network for piezo-flexural nanopositioning stage

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Title:	Intelligent nonsingular terminal sliding-mode control using MIMO elman neural network for piezo-flexural nanopositioning stage
Authors:	林法正;LIN, Faa-Jeng;LEE, Shih-Yang;CHOU, Po-Huan
Contributors:	資訊電機學院電機工程學系
Keywords:	Adaptation models;Applied sciences;Computer science;control theory;systems;Control system analysis;Control systems;Control theory. Systems;Dynamical systems;Dynamics;Exact sciences and technology;Force;Hysteresis;Industrial metrology. Testing;Mathematical model;Mathematical models;Mechanical engineering. Machine design;Modelling and identification;Nanomaterials;Nanostructure;Neural networks;Precision engineering, watch making;Studies;Terminals;Tracking;Uncertainty
Date:	2012-12-18
Issue Date:	2026-04-23 14:18:23 (UTC+8)
Publisher:	Institute of Electrical and Electronics Engineers Inc.;New York, NY: IEEE
Abstract:	摘要： The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS. 其他題名： T-UFFC 其他題名： IEEE Trans Ultrason Ferroelectr Freq Control 出版者： New York, NY: IEEE 出版日期： 2012-12-01 出處： IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2012-12, Vol.59 (12), p.2716-2730 資源來源： IEEE Electronic Library (IEL) 版權： 2014 INIST-CNRS 版權： Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Dec 2012 識別號： ISSN: 0885-3010 識別號： ISSN: 1525-8955 識別號： EISSN: 1525-8955 識別號： DOI: 10.1109/TUFFC.2012.2513 識別號： PMID: 23221221 識別號： CODEN: ITUCER
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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