Neural observer by coordinate transformation

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

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
• Electronic ISSN: 1359-7035
• Publisher: Institution of Engineering and Technology
• 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