Multi-state dependent parameter model identification and estimation for nonlinear dynamic systems.

Sadeghi, Jafar and Tych, W. and Chotai, A. and Young, P. C. (2010) Multi-state dependent parameter model identification and estimation for nonlinear dynamic systems. Electronics Letters, 46 (18). pp. 1265-1266. ISSN 0013-5194

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Abstract

An important generalisation of the state dependent parameter approach to the modelling of nonlinear dynamic systems to include multi-state dependent parameter (MSDP) nonlinearities is described. The recursive estimation of the MSDP model parameters in a multivariable state space occurs along a multipath trajectory, employing the Kalman filter and fixed interval smoothing algorithms. The novelty of the method lies in redefining the concepts of sequence (predecessor, successor), allowing for its use in a multi-state dependent context, so producing efficient parameterisation for a fairly wide class of nonlinear, stochastic dynamic systems. The format of the estimated model allows its direct use in control system design.

Item Type: Journal Article
Journal or Publication Title: Electronics Letters
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/ge
Subjects:
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 40763
Deposited By: Mr Richard Ingham
Deposited On: 03 May 2011 13:36
Refereed?: Yes
Published?: Published
Last Modified: 22 Jun 2019 03:17
URI: https://eprints.lancs.ac.uk/id/eprint/40763

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