DocumentCode
351097
Title
The stabilization control of ball-beam using self-recurrent neural networks
Author
Ho Tack, Han ; Gyu Choo, Yeon ; Geun Kim, Chang ; Woo Jung, Min
Author_Institution
Dept. of Electron. Eng., Chinju Nat. Univ., Kyungnam, South Korea
fYear
1999
fDate
36495
Firstpage
222
Lastpage
225
Abstract
In this paper, applications of self-recurrent neural networks based on an adaptive controller to control the stabilization of a ball-beam are considered. Therefore, a dynamic model for a ball-beam is derived, and then a comparative analysis is made with LQR and a neural network controller through simulation. The results are presented to illustrate the advantages and improved performance of the proposed stabilization controller over the conventional LQR controller
Keywords
adaptive control; neurocontrollers; recurrent neural nets; stability; adaptive controller; ball-beam; dynamic model; neural network controller; self-recurrent neural networks; simulation; stabilization control; Adaptive control; Analytical models; Artificial neural networks; Control system synthesis; Control systems; Error correction; Neural networks; Nonlinear control systems; Nonlinear equations; Proportional control;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-5578-4
Type
conf
DOI
10.1109/KES.1999.820159
Filename
820159
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