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dc.contributor.authorChai, Q.
dc.contributor.authorLoxton, Ryan
dc.contributor.authorTeo, Kok Lay
dc.contributor.authorYang, C.
dc.identifier.citationChai, Q. and Loxton, R. and Teo, K.L. and Yang, C. 2013. Time-delay estimation for nonlinear systems with piecewise-constant input. Applied Mathematics and Computations. 219 (7): pp. 9543-9560.

We consider a general nonlinear time-delay system in which the input signal is piecewise-constant. Such systems arise in a wide range of industrial applications, including evaporation and purification processes and chromatography. We assume that the time-delays—one involving the state variables and the other involving the input variables—are unknown and need to be estimated using experimental data. We formulate the problem of estimating the unknown delays as a nonlinear optimization problem in which the cost function measures the least-squares error between predicted and measured system output. The main difficulty with this problem is that the delays are decision variables to be optimized, rather than fixed values. Thus, conventional optimization techniques are not directly applicable. We propose a new computational approach based on a novel algorithm for computing the cost function’s gradient. We then apply this approach to estimate the time-delays in two industrial chemical processes: a zinc sulphate purification process and a sodium aluminate evaporation process.

dc.publisherElsevier Inc.
dc.subjectEvaporation processes
dc.subjectParameter identification
dc.subjectPurification processes
dc.subjectTime-delay system
dc.subjectNonlinear optimization
dc.titleTime-delay estimation for nonlinear systems with piecewise-constant input
dc.typeJournal Article
dcterms.source.titleApplied Mathematics and Computations

NOTICE: This is the author’s version of a work that was accepted for publication in Applied Mathematics and Computations. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published Applied Mathematics and Computations, Vol. 219, Issue 7. (2013). doi: 10.1016/j.amc.2013.03.015

curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access

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