Accessibility navigation


Inverting recurrent neural networks for internal model control of nonlinear systems

Kambhampati, C., Craddock, R., Tham, M. and Warwick, K. (1998) Inverting recurrent neural networks for internal model control of nonlinear systems. In: Proceedings of the 1998 American Control Conference. ACC. IEEE, pp. 975-979. ISBN 0-7803-4530-4

Full text not archived in this repository.

To link to this article DOI: 10.1109/ACC.1998.703554

Abstract/Summary

In this paper, we show how a set of recently derived theoretical results for recurrent neural networks can be applied to the production of an internal model control system for a nonlinear plant. The results include determination of the relative order of a recurrent neural network and invertibility of such a network. A closed loop controller is produced without the need to retrain the neural network plant model. Stability of the closed-loop controller is also demonstrated.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:21623
Uncontrolled Keywords:closed-loop controller, internal model control, internal model control system, nonlinear systems, recurrent neural network invertibility, recurrent neural network relative order determination
Publisher:IEEE

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation