Design and implementation of industrial neural network controller using backstepping
Kuljaca, O.
Swamy, N.
Lewis, F.L.
Kwan, C.M.
Autom. & Robotics Res. Inst., Univ. of Texas, Arlington, TX, USA;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Feb 2003
Volume: 50,
Issue: 1
On page(s): 193- 201
ISSN: 0278-0046
INSPEC Accession Number: 7517992
Digital Object Identifier: 10.1109/TIE.2002.807675
Current Version Published: 2003-01-29
Abstract
In this paper, a novel neural network (NN) backstepping controller is modified for application to an industrial motor drive system. A control system structure and NN tuning algorithms are presented that are shown to guarantee stability and performance of the closed-loop system. The NN backstepping controller is implemented on an actual motor drive system using a two-PC control system developed at The University of Texas at Arlington. The implementation results show that the NN backstepping controller is highly effective in controlling the industrial motor drive system. It is also shown that the NN controller gives better results on actual systems than a standard backstepping controller developed assuming full knowledge of the dynamics. Moreover, the NN controller does not require the linear-in-the-parameters assumption or the computation of regression matrices required by standard backstepping.
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