Internal model control of nonlinear systems through the inversion of recurrent neural networksKambhampati, C., Craddock, R., Tham, M. and Warwick, K. (1998) Internal model control of nonlinear systems through the inversion of recurrent neural networks. In: 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence. IEEE, pp. 1361-1366. 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: 10.1109/IJCNN.1998.685973 Abstract/SummaryRecurrent neural networks can be used for both the identification and control of nonlinear systems. This paper takes a previously derived set of theoretical results about recurrent neural networks and applies them to the task of providing internal model control for a nonlinear plant. Using the theoretical results, we show how an inverse controller can be produced from a neural network model of the plant, without the need to train an additional network to perform the inverse control.
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