The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Neural networks for nonlinear internal model control
Abstract
A novel technique, directly using artificial neural networks, is proposed for the adaptive control of nonlinear systems. The ability of neural networks to model arbitrary nonlinear functions and their inverses is exploited. The use of nonlinear function inverses raises questions of the existence of the inverse operators. These are investigated and results are given characterising the invertibility of a class of nonlinear dynamical systems. The control structure used is internal model control. It is used to directly incorporate networks modelling the plant and its inverse within the control strategy. The potential of the proposed method is demonstrated by an example.
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Citations
Cites
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
Feedback Systems: Input-Output Properties
Desoer, C. A., Vidyasagar, M., & Willson, A. N. (1975) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3426967 · Cited by 3,225
Morari, M., & Zafiriou, E. (1988) · International Linear Collider · Cited by 2,735
Internal model control. A unifying review and some new results
Garcia, C. E., & Morari, M. (1982) · Industrial & Engineering Chemistry Process Design and Development · doi:10.1021/i200017a016 · Cited by 1,534
A multilayered neural network controller
Psaltis, D., Sideris, A., & Yamamura, A. A. (1988) · IEEE Control Systems Magazine · doi:10.1109/37.1868 · Cited by 1,056
Non-linear system identification using neural networks
CHEN, S., BILLINGS, S. A., & GRANT, P. M. (1990) · International Journal of Control · doi:10.1080/00207179008934126 · Cited by 1,043
Networks and the best approximation property
Girosi, F., & Poggio, T. (1990) · Biological Cybernetics · doi:10.1007/bf00195855 · Cited by 888
PREDICTING THE FUTURE: A CONNECTIONIST APPROACH
Weigend, A. S., Huberman, B. A., & Rumelhart, D. E. (1990) · International Journal of Neural Systems · doi:10.1142/s0129065790000102 · Cited by 721
Use of neural nets for dynamic modeling and control of chemical process systems
Bhat, N., & McAvoy, T. J. (1990) · Computers & Chemical Engineering · doi:10.1016/0098-1354(90)87028-n · Cited by 669
IDENTIFICATION AND CONTROL OF DYNAMIC SYSTEMS USING NEURAL NETWORKS
Narendra, K. S., & Parthasarathy, K. (1990) · Cited by 647
Metadata
- Authors
- Hunt, K. J., & Sbarbaro, D.
- Venue
- IEE Proceedings D Control Theory and Applications
- Published
- 1991
- Volume
- 138
- Issue
- 5
- Pages
- 431
- ISSN
- 0143-7054 (ISSN-L)
- OpenAlex
- W2166985410
- Cited by
- 367
- References
- 11
- FWCI
- 38.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hunt, K. J., & Sbarbaro, D. (1991). Neural networks for nonlinear internal model control. IEE Proceedings D Control Theory and Applications. https://doi.org/10.1049/ip-d.1991.0059
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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