Nonlinear system identification using recurrent networks

Hyukjoon Lee, Yongseok Park, Kishan Mehrotra, Chilukuri Mohan, Sanjay Ranka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

The authors present empirical results on the application of neural networks to system identification and inverse system identification. Recurrent and feedforward network models were used to build an emulator of a simple nonlinear gantry crane system, and for the inverse dynamics of the system. The relevant data were artificially generated from the differential equations describing the system. The experimental results show that recurrent networks performed marginally better than feedforward networks, in terms of the mean square errors, for the system identification problem, as well as for the inverse system identification problem.

Original languageEnglish (US)
Title of host publication91 IEEE Int Jt Conf Neural Networks IJCNN 91
PublisherIEEE Computer Society
Pages2410-2415
Number of pages6
ISBN (Print)0780302273, 9780780302273
DOIs
StatePublished - 1991
Event1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
Duration: Nov 18 1991Nov 21 1991

Publication series

Name91 IEEE Int Jt Conf Neural Networks IJCNN 91

Other

Other1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
CitySingapore, Singapore
Period11/18/9111/21/91

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Lee, H., Park, Y., Mehrotra, K., Mohan, C., & Ranka, S. (1991). Nonlinear system identification using recurrent networks. In 91 IEEE Int Jt Conf Neural Networks IJCNN 91 (pp. 2410-2415). (91 IEEE Int Jt Conf Neural Networks IJCNN 91). IEEE Computer Society. https://doi.org/10.1109/ijcnn.1991.170749