The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Neural networks for nonlinear dynamic system modelling and identification
Abstract
Many real-world systems exhibit complex nonlinear characteristics and cannot be treated satisfactorily using linear systems theory. A neural network which has the ability to learn sophisticated nonlinear relationships provides an ideal means of modelling complicated nonlinear systems. This paper addresses the issues related to the identification of nonlinear discrete-time dynamic systems using neural networks. Three network architectures, namely the multi-layer perceptron, the radial basis function network and the functional-link network, are presented and several learning or identification algorithms are derived. Advantages and disadvantages of these structures are discussed and illustrated using simulated and real data. Particular attention is given to the connections between existing techniques for nonlinear systems identification and some aspects of neural network methodology, and this demonstrates that certain techniques employed in the neural network context have long been developed by the control engineering community.
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Cites
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Cited by
A comprehensive review for industrial applicability of artificial neural networks
Meireles, M. R. G., Almeida, P. E. M., & Simoes, M. G. (2003) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2003.812470 · Cited by 482
Dini, P., & Paolini, D. (2025) · Batteries · doi:10.3390/batteries11030107 · Cited by 40
Janjua, M. Y., Azfar, A., Asghar, Z., & Shehzad Quraishi, K. (2024) · Bioresource Technology · doi:10.1016/j.biortech.2024.130687 · Cited by 26
On the analysis of the inverse problem of metabolic pathways using artificial neural networks
Mendes, P., & Kell, D. B. (1996) · Biosystems · doi:10.1016/0303-2647(95)01565-5 · Cited by 24
Metadata
- Authors
- CHEN, S., & BILLINGS, S. A.
- Venue
- International Journal of Control
- Publisher
- Informa UK Limited
- Published
- 1992-08
- Volume
- 56
- Issue
- 2
- Pages
- 319-346
- ISSN
- 0020-7179 (ISSN-L)
- 1366-5820
- OpenAlex
- W2149350706
- Cited by
- 720
- References
- 36
- FWCI
- 16.10
- Type
- journal article
- Language
- en
- Open access
- closed
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