NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION

Bibliographic Details
Main Author:	Liu, Yong
Language:	English
Published:	Ohio University / OhioLINK 2007
Subjects:	Nonlinear Control Neural Network Adaptive Control Trajectory Linearization Control System Identification
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159

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spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-ohiou11770921592021-08-03T05:44:25Z NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION Liu, Yong Nonlinear Control Neural Network Adaptive Control Trajectory Linearization Control System Identification <p>Advanced nonlinear control design methods usually depend on an analytical plant model, which in many practical applications, is often inaccurate or unavailable. Neural networks are a powerful tool to enhance a dynamic model if one is available but inaccurate, or to build a system dynamic model from experimental data. Trajectory linearization control (TLC) is a nonlinear control design method, which combines nonlinear dynamic inversion and linear time-varying (LTV) feedback stabilization to achieve robust tracking control for a broad class of nonlinear dynamic systems. In this dissertation, the research goal is to develop theories and methodologies to improve the understanding and applicability of TLC for inaccurate or lack of dynamic models by using neural networks. To this end, the following research objectives have been achieved. First, rigorous stability robustness analyses of TLC subject to the regular perturbation and singular perturbation are established. Second, a continuous-time nonlinear system identification method using neural network is developed. Third, a neural network trajectory linearization control (NNTLC) design procedure with stability analysis is proposed. Fourth, an adaptive neural network trajectory linearization control (ANNTLC) scheme is presented, in which the neural network control compensates for the system uncertainty adaptively. Illustrative examples of nonlinear applications of TLC, NNTLC and ANNTLC are also presented.</p> 2007-08-02 English text Ohio University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159 http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection	NDLTD
language	English
sources	NDLTD
topic	Nonlinear Control Neural Network Adaptive Control Trajectory Linearization Control System Identification
spellingShingle	Nonlinear Control Neural Network Adaptive Control Trajectory Linearization Control System Identification Liu, Yong NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
author	Liu, Yong
author_facet	Liu, Yong
author_sort	Liu, Yong
title	NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
title_short	NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
title_full	NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
title_fullStr	NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
title_full_unstemmed	NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION
title_sort	neural adaptive nonlinear tracking using trajectory linearization
publisher	Ohio University / OhioLINK
publishDate	2007
url	http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159
work_keys_str_mv	AT liuyong neuraladaptivenonlineartrackingusingtrajectorylinearization
_version_	1719424419443507200

NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION

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