Accessibility navigation


Internal model control of nonlinear systems through the inversion of recurrent neural networks

Kambhampati, 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.

To link to this article DOI: 10.1109/IJCNN.1998.685973

Abstract/Summary

Recurrent 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.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:21630
Uncontrolled Keywords:internal model control, inverse controller, neural network model, nonlinear systems, recurrent neural networks
Publisher:IEEE

Centaur Editors: Update this record

Page navigation