Tych, Wlodek and Sadeghi, J. and Smith, Paul and Chotai, Arun and Taylor, C. J. (2012) Multi-State-Dependent parameter model identification and estimation. In: System Identification, Environmental Modelling and Control System Design. Springer, London, pp. 191-210. ISBN 978-0-85729-973-4
Full text not available from this repository.Abstract
This chapter describes the generalisation of the State Dependent Parameter (SDP) approach to the modelling of nonlinear dynamic systems, to now include Multi-State Dependent Parameter (MSDP) nonlinearities. The recursive estimation of the MSDP model parameters in a multivariable state space occurs along a multi-path 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 their use in a multi-state dependent context, so producing efficient parameterisation for a fairly wide class of non-linear, stochastic dynamic systems. The format of the estimated model allows its direct use in control system design. Two worked examples in Matlab are considered.
| Item Type: | Contribution in Book/Report/Proceedings |
|---|---|
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences |
| Departments: | Faculty of Science and Technology > Lancaster Environment Centre Faculty of Science and Technology > Engineering |
| ID Code: | 40761 |
| Deposited By: | Mr Richard Ingham |
| Deposited On: | 03 May 2011 14:03 |
| Refereed?: | No |
| Published?: | Published |
| Last Modified: | 07 Aug 2012 16:28 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/40761 |
Actions (login required)
| View Item |
