State-delay estimation for nonlinear systems using inexact output data

This paper considers the problem of using inexact output data to estimate the values of unknown state-delays in a general nonlinear time-delay system. We formulate the problem as a nonlinear optimization problem in which the state-delays are decision parameters and the cost function penalizes a weig...

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Main Authors: Lin, Qun, Loxton, Ryan, Xu, C., Teo, Kok Lay
Other Authors: Shengyuan Xu
Format: Conference Paper
Published: IEEE 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/32780
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author Lin, Qun
Loxton, Ryan
Xu, C.
Teo, Kok Lay
author2 Shengyuan Xu
author_facet Shengyuan Xu
Lin, Qun
Loxton, Ryan
Xu, C.
Teo, Kok Lay
author_sort Lin, Qun
building Curtin Institutional Repository
collection Online Access
description This paper considers the problem of using inexact output data to estimate the values of unknown state-delays in a general nonlinear time-delay system. We formulate the problem as a nonlinear optimization problem in which the state-delays are decision parameters and the cost function penalizes a weighted sum of the mean and variance of the least-squares error between actual and predicted system output. Our main result shows that the gradient of the least-squares cost function can be computed by solving an auxiliary time-advance system backward in time. On this basis, the state-delay estimation problem can be solved efficiently using standard gradient-based optimization algorithms such as sequential quadratic programming. We conclude the paper by testing this approach on a dynamic model of a continuously-stirred tank reactor with recycle loop.
first_indexed 2025-11-14T08:29:36Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:29:36Z
publishDate 2014
publisher IEEE
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spelling curtin-20.500.11937-327802023-02-27T07:34:31Z State-delay estimation for nonlinear systems using inexact output data Lin, Qun Loxton, Ryan Xu, C. Teo, Kok Lay Shengyuan Xu Qianchuan Zhao Nonlinear system Parameter estimation Time-delay system Gradient-based optimization This paper considers the problem of using inexact output data to estimate the values of unknown state-delays in a general nonlinear time-delay system. We formulate the problem as a nonlinear optimization problem in which the state-delays are decision parameters and the cost function penalizes a weighted sum of the mean and variance of the least-squares error between actual and predicted system output. Our main result shows that the gradient of the least-squares cost function can be computed by solving an auxiliary time-advance system backward in time. On this basis, the state-delay estimation problem can be solved efficiently using standard gradient-based optimization algorithms such as sequential quadratic programming. We conclude the paper by testing this approach on a dynamic model of a continuously-stirred tank reactor with recycle loop. 2014 Conference Paper http://hdl.handle.net/20.500.11937/32780 IEEE fulltext
spellingShingle Nonlinear system
Parameter estimation
Time-delay system
Gradient-based optimization
Lin, Qun
Loxton, Ryan
Xu, C.
Teo, Kok Lay
State-delay estimation for nonlinear systems using inexact output data
title State-delay estimation for nonlinear systems using inexact output data
title_full State-delay estimation for nonlinear systems using inexact output data
title_fullStr State-delay estimation for nonlinear systems using inexact output data
title_full_unstemmed State-delay estimation for nonlinear systems using inexact output data
title_short State-delay estimation for nonlinear systems using inexact output data
title_sort state-delay estimation for nonlinear systems using inexact output data
topic Nonlinear system
Parameter estimation
Time-delay system
Gradient-based optimization
url http://hdl.handle.net/20.500.11937/32780