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Neural observer by coordinate transformation

Delgado, A.; Hou, M.; Kambhampati, C.

Authors

A. Delgado

M. Hou



Abstract

Nonlinear control affine systems with maximum relative degree and a class of nonlinear differential equations can be transformed into a state representation known as the normal form. Based on the normal form an observer is designed using neural networks as approximation of nonlinear terms in the normal form and the observer gain is determined with a previous result in a triangular form.

Citation

Delgado, A., Hou, M., & Kambhampati, C. (2005). Neural observer by coordinate transformation. IEE Proceedings Control Theory and Applications, 152(6), 698-706. https://doi.org/10.1049/ip-cta%3A20045069

Journal Article Type Article
Acceptance Date Dec 31, 2005
Publication Date Nov 1, 2005
Journal IEE Proceedings: Control Theory and Applications
Print ISSN 1350-2379
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 152
Issue 6
Pages 698-706
DOI https://doi.org/10.1049/ip-cta%3A20045069
Keywords Control and Systems Engineering; Instrumentation; Electrical and Electronic Engineering
Public URL https://hull-repository.worktribe.com/output/409681