Stable receding horizon control based on recurrent networks

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Kambhampati, C., Delgado, A., Mason, J. D. and Warwick, K. (1997) Stable receding horizon control based on recurrent networks. IEE Proceedings-Control Theory and Applications, 144 (3). pp. 249-254. ISSN 1350-2379 doi: 10.1049/ip-cta:19970950

Abstract/Summary

The last decade has seen the re-emergence of artificial neural networks as an alternative to traditional modelling techniques for the control of nonlinear systems. Numerous control schemes have been proposed and have been shown to work in simulations. However, very few analyses have been made of the working of these networks. The authors show that a receding horizon control strategy based on a class of recurrent networks can stabilise nonlinear systems.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/18048
Identification Number/DOI 10.1049/ip-cta:19970950
Refereed Yes
Divisions Science
Uncontrolled Keywords nonlinear system control, recurrent neural networks, stable receding horizon control
Publisher IET
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