A system identification model for adaptive nonlinear control

Dennis J. Linse, Robert F. Stengel

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

3 Scopus citations

Abstract

A system identification model that combines generalized-spline function approximation with a nonlinear control system is described. The complete control system contains three main elements: a nonlinear-inverse-dynamic control law that depends on a comprehensive model of the plant, a state estimator whose outputs drive the control law, and a function approximation scheme that models the system dynamics. The system-identification task, which combines an extended Kalman filter with a function approximator modeled as an artificial neural network, is considered. The results of an application of the identification techniques to a nonlinear transport aircraft model are presented.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherPubl by American Automatic Control Council
Pages1752-1757
Number of pages6
ISBN (Print)0879425652, 9780879425654
DOIs
StatePublished - Jan 1 1991
EventProceedings of the 1991 American Control Conference - Boston, MA, USA
Duration: Jun 26 1991Jun 28 1991

Publication series

NameProceedings of the American Control Conference
Volume2
ISSN (Print)0743-1619

Other

OtherProceedings of the 1991 American Control Conference
CityBoston, MA, USA
Period6/26/916/28/91

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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    Linse, D. J., & Stengel, R. F. (1991). A system identification model for adaptive nonlinear control. In Proceedings of the American Control Conference (pp. 1752-1757). (Proceedings of the American Control Conference; Vol. 2). Publ by American Automatic Control Council. https://doi.org/10.23919/acc.1991.4791685