Robust adaptive observer design for uncertain systems with bounded disturbances

Vahram Stepanyan; Naira Hovakimyan

doi:10.1109/tnn.2007.895837

Robust adaptive observer design for uncertain systems with bounded disturbances

IEEE Trans Neural Netw. 2007 Sep;18(5):1392-403. doi: 10.1109/tnn.2007.895837.

Authors

Vahram Stepanyan¹, Naira Hovakimyan

Affiliation

¹ Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0203, USA. vahrams@vt.edu

PMID: 18220188
DOI: 10.1109/tnn.2007.895837

Abstract

This paper presents a robust adaptive observer design methodology for a class of uncertain nonlinear systems in the presence of time-varying unknown parameters with absolutely integrable derivatives, and nonvanishing disturbances. Using the universal approximation property of radial basis function (RBF) neural networks and the adaptive bounding technique, the developed observer achieves asymptotic convergence of state estimation error to zero, while ensuring boundedness of parameter errors. A comparative simulation study is presented by the end.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Algorithms*
Computer Simulation
Feedback
Models, Theoretical*
Neural Networks, Computer*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity