Title :
Adaptive observer for a class of nonlinear systems using neural networks
Author :
Choi, Jin Young ; Farrell, Jay
Author_Institution :
Dept. of Electr. Eng., Seoul Nat. Univ., South Korea
Abstract :
This paper presents an adaptive observer using neural networks for a class of nonlinear systems. The adaptive observer follows the nonlinear model estimation method for automated fault diagnosis. The contributions of this article include: modification of the estimation model as appropriate for certain nonlinear control applications; modification of the stability proofs; investigation of the observer performance through an illustrative simulation
Keywords :
adaptive control; fault diagnosis; feedback; neural nets; nonlinear systems; observers; SISO system; adaptive observer; fault diagnosis; neural networks; nonlinear control systems; output feedback; stability; Adaptive control; Adaptive systems; Approximation error; Biological neural networks; Fault diagnosis; Neural networks; Nonlinear systems; Observers; Output feedback; Stability;
Conference_Titel :
Intelligent Control/Intelligent Systems and Semiotics, 1999. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-5665-9
DOI :
10.1109/ISIC.1999.796640
