Adaptive neural observer with forward co-state propagation

Author

Salam, Fathi M. ; Zhang, Jian

Author_Institution

Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA

Volume

1

fYear

2001

fDate

2001

Firstpage

675

Abstract

An adaptive nonlinear observer using input and output measurements is described by using techniques of optimization theory, the calculus of variations and gradient descent dynamics. A series of formulations of general parameterized nonlinear observers of continuous-time and discrete-time are given, including a co-state (sensitivity) dynamics equation that propagates forward in time and serves as a filtered version of the measured error signal. Several Matlab simulation examples in the continuous-time and discrete-time cases are given to illustrate the approach

Keywords

adaptive systems; continuous time systems; discrete time systems; dynamics; feedforward neural nets; nonlinear systems; observers; adaptive nonlinear observer; continuous-time systems; costate propagation; discrete-time systems; dynamics; gradient descent dynamics; multilayer neural networks; nonlinear systems; optimization; sensitivity; state estimation; Calculus; Electric variables measurement; Mathematical model; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Observers; Performance analysis; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.939105

Filename

939105