Stable receding horizon control based on recurrent networksKambhampati, 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 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1049/ip-cta:19970950 Abstract/SummaryThe 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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