Identification of hammerstain model using stochastic perturbation simultaneous approximation

This project study an identification of continuous Hammerstein based on simultaneous Perturbation Stochastic Approximation (SPSA). Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. The structure of non-linear is assumed to be completely unknown. However...

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Main Author:	Nurriyah, Mohd Noor
Format:	Undergraduates Project Papers
Language:	English English English English
Published:	2016
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/18059/ http://umpir.ump.edu.my/id/eprint/18059/ http://umpir.ump.edu.my/id/eprint/18059/1/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Table%20of%20contents.pdf http://umpir.ump.edu.my/id/eprint/18059/7/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Abstract.pdf http://umpir.ump.edu.my/id/eprint/18059/13/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Chapter%201.pdf http://umpir.ump.edu.my/id/eprint/18059/14/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-References.pdf

id	ump-18059
recordtype	eprints
spelling	ump-180592017-07-05T02:59:41Z http://umpir.ump.edu.my/id/eprint/18059/ Identification of hammerstain model using stochastic perturbation simultaneous approximation Nurriyah, Mohd Noor TK Electrical engineering. Electronics Nuclear engineering This project study an identification of continuous Hammerstein based on simultaneous Perturbation Stochastic Approximation (SPSA). Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. The structure of non-linear is assumed to be completely unknown. However, the system order assumed to be known For handling it, piecewise-linear function are used as a tool to approximate the unknown non-linear function. The SPSA algorithms was proposed to identify the problem of Hammerstein model. The main benefit of the SPSA-based method is it can be applied to identification of Hammerstein systems even though less restrictive assumptions. The SPSA based method is then used to estimate the parameters in both the linear and non-linear parts based on the given input and output data with the present of delay in time. Besides that, this project analysed the efficient of the SPSA in identify nonlinear system in term of object function and error with different noise variance. A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation. 2016-12 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18059/1/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Table%20of%20contents.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/18059/7/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Abstract.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/18059/13/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Chapter%201.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/18059/14/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-References.pdf Nurriyah, Mohd Noor (2016) Identification of hammerstain model using stochastic perturbation simultaneous approximation. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:100081&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Nurriyah, Mohd Noor Identification of hammerstain model using stochastic perturbation simultaneous approximation
description	This project study an identification of continuous Hammerstein based on simultaneous Perturbation Stochastic Approximation (SPSA). Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. The structure of non-linear is assumed to be completely unknown. However, the system order assumed to be known For handling it, piecewise-linear function are used as a tool to approximate the unknown non-linear function. The SPSA algorithms was proposed to identify the problem of Hammerstein model. The main benefit of the SPSA-based method is it can be applied to identification of Hammerstein systems even though less restrictive assumptions. The SPSA based method is then used to estimate the parameters in both the linear and non-linear parts based on the given input and output data with the present of delay in time. Besides that, this project analysed the efficient of the SPSA in identify nonlinear system in term of object function and error with different noise variance. A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation.
format	Undergraduates Project Papers
author	Nurriyah, Mohd Noor
author_facet	Nurriyah, Mohd Noor
author_sort	Nurriyah, Mohd Noor
title	Identification of hammerstain model using stochastic perturbation simultaneous approximation
title_short	Identification of hammerstain model using stochastic perturbation simultaneous approximation
title_full	Identification of hammerstain model using stochastic perturbation simultaneous approximation
title_fullStr	Identification of hammerstain model using stochastic perturbation simultaneous approximation
title_full_unstemmed	Identification of hammerstain model using stochastic perturbation simultaneous approximation
title_sort	identification of hammerstain model using stochastic perturbation simultaneous approximation
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/18059/ http://umpir.ump.edu.my/id/eprint/18059/ http://umpir.ump.edu.my/id/eprint/18059/1/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Table%20of%20contents.pdf http://umpir.ump.edu.my/id/eprint/18059/7/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Abstract.pdf http://umpir.ump.edu.my/id/eprint/18059/13/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-Chapter%201.pdf http://umpir.ump.edu.my/id/eprint/18059/14/Identification%20of%20hammerstain%20model%20using%20stochastic%20perturbation%20simultaneous%20approximation-References.pdf
first_indexed	2023-09-18T22:25:20Z
last_indexed	2023-09-18T22:25:20Z
_version_	1777415928791695360

Identification of hammerstain model using stochastic perturbation simultaneous approximation

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