DocumentCode
300479
Title
Adaptive control using neural networks and approximate models
Author
Narendra, Kumpati S. ; Mukhopadhyay, Snehasis
Author_Institution
Center for Syst. Sci., Yale Univ., New Haven, CT, USA
Volume
1
fYear
1995
fDate
21-23 Jun 1995
Firstpage
355
Abstract
The NARMA model is an exact representation of the input-output behavior of dynamical systems. However, it is not convenient for purposes of control. In this paper, the authors introduce two classes of models which are approximations to the NARMA model, and at the same time substantially simplifies the control problem
Keywords
adaptive control; autoregressive moving average processes; discrete time systems; multidimensional systems; neural nets; nonlinear dynamical systems; NARMA model; adaptive control; approximate models; dynamical systems; input-output behavior; neural networks; Adaptive control; Books; Control systems; Integrated circuit modeling; Mathematical model; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Process control;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, Proceedings of the 1995
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2445-5
Type
conf
DOI
10.1109/ACC.1995.529269
Filename
529269
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