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Author Yu, S. ♦ Annaswamy, A.M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1995
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Nonlinear control systems ♦ Control systems ♦ Stability ♦ Neural networks ♦ Nonlinear systems ♦ Adaptive control ♦ Error correction ♦ Mechanical variables control ♦ Mechanical engineering ♦ Information processing
Abstract A stability based approach is introduced to design neural controllers for nonlinear systems. The requisite control input is generated as the output of a neural network which is trained off-line such that the time derivative of a positive definite function of the state variables becomes negative at all points. By using the successfully trained network as a controller, it is shown that the closed-loop system can be made asymptotically stable. The stability framework introduced is shown to permit the generation of more efficient algorithms that can lead to a larger region of stability for a wide class of nonlinear systems.
Description Author affiliation: Dept. of Mech. Eng., MIT, Cambridge, MA, USA (Yu, S.; Annaswamy, A.M.)
ISBN 0780326857
ISSN 01912216
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1995-12-13
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 585.51 kB
Page Count 6
Starting Page 1290
Ending Page 1295


Source: IEEE Xplore Digital Library