Abstract
A new Neural Network (NN) based observer design method for nonlinear systems represented by nonlinear dynamics and linear/nonlinear measurement is proposed in this paper. In this new approach, as the first step, the observer design problem is changed into a "controller" design problem by establishing the error dynamics, and then the Adaptive Critic (AC) based approach is applied on this error dynamics to design a 'controller', such that the errors are driven to zero. The resulting observer has inherent robustness from the AC based design approach. Some simulations are presented to illustrate the effectiveness of this approach.
Recommended Citation
X. Liu and S. N. Balakrishnan, "Adaptive Critic Based Neuro-Observer," Proceedings of the 2001 American Control Conference, 2001, Institute of Electrical and Electronics Engineers (IEEE), Jan 2001.
The definitive version is available at https://doi.org/10.1109/ACC.2001.945958
Meeting Name
2001 American Control Conference, 2001
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Adaptive Critic; Controller Design; Neural Nets; Neuro-Observer; Nonlinear Control Systems; Nonlinear Systems; Observer Design; Observers
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2001 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2001
