Robust neural network tracking controller based on simultaneous perturbation stochastic approximation

the robust neural controller based on the SPSA has been developed to obtain the guaranteed stability with a normalized learning algorithm. A three-layered neural network is used for the simulation study with 30 hidden layer neurons and two output neurons, which was trained by the standard back-propa...

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Bibliographic Details
Main Author:	Kyaw, Minn Latt.
Other Authors:	Song, Qing
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Online Access:	http://hdl.handle.net/10356/4539
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Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-4539
record_format	dspace
spelling	sg-ntu-dr.10356-45392023-07-04T15:59:37Z Robust neural network tracking controller based on simultaneous perturbation stochastic approximation Kyaw, Minn Latt. Song, Qing School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics the robust neural controller based on the SPSA has been developed to obtain the guaranteed stability with a normalized learning algorithm. A three-layered neural network is used for the simulation study with 30 hidden layer neurons and two output neurons, which was trained by the standard back-propagation and SPSA training algorithm. Master of Science (Computer Control and Automation) 2008-09-17T09:53:47Z 2008-09-17T09:53:47Z 2003 2003 Thesis http://hdl.handle.net/10356/4539 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Kyaw, Minn Latt. Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
description	the robust neural controller based on the SPSA has been developed to obtain the guaranteed stability with a normalized learning algorithm. A three-layered neural network is used for the simulation study with 30 hidden layer neurons and two output neurons, which was trained by the standard back-propagation and SPSA training algorithm.
author2	Song, Qing
author_facet	Song, Qing Kyaw, Minn Latt.
format	Theses and Dissertations
author	Kyaw, Minn Latt.
author_sort	Kyaw, Minn Latt.
title	Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
title_short	Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
title_full	Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
title_fullStr	Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
title_full_unstemmed	Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
title_sort	robust neural network tracking controller based on simultaneous perturbation stochastic approximation
publishDate	2008
url	http://hdl.handle.net/10356/4539
_version_	1772826905757614080

Robust neural network tracking controller based on simultaneous perturbation stochastic approximation

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