DocumentCode
1445050
Title
NNSYSID and NNCTRL tools for system identification and control with neural networks
Author
Norgaard, M. ; Ravn, Ole ; Poulsen, Niels Kjelstad
Author_Institution
Dept. of Math. Modelling, Tech. Univ. Denmark, Lyngby, Denmark
Volume
12
Issue
1
fYear
2001
fDate
2/1/2001 12:00:00 AM
Firstpage
29
Lastpage
36
Abstract
Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview of the design of NNSYSID and NNCTRL.
Keywords
control system CAD; control system analysis computing; identification; neural nets; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; MATLAB; NNCTRL; NNSYSID; control; control systems; direct inverse control; feedback linearisation; gain scheduling; instantaneous linearisation; internal model control; model structure selection; model validation; neural network based control system design toolkit; neural network based system identification toolbox; neural networks; nonlinear dynamic systems; nonlinear feedforward; nonlinear model predictive control; nonlinear model structures; optimal control; system identification; training algorithms;
fLanguage
English
Journal_Title
Computing & Control Engineering Journal
Publisher
iet
ISSN
0956-3385
Type
jour
DOI
10.1049/cce:20010105
Filename
905755
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