DocumentCode
1989223
Title
Remarks on Servo Controller Using Quantum Neural Network with Qubit Neurons
Author
Takahashi, Kazuhiko
Author_Institution
Dept. of Inf. Syst. Design, Doshisha Univ., Kyotanabe, Japan
fYear
2012
fDate
27-30 May 2012
Firstpage
1
Lastpage
4
Abstract
This paper presents the servo controller design of using a quantum neural network and investigates its characteristics for control systems. A multi-layer quantum neural network that uses qubit neurons as an information processing unit is used to design three types of neural network-based servo controller: the direct controller, the parallel controller and the self-tuning controller. Computational experiments to control the nonlinear discrete-time plant are conducted in order to evaluate the learning performance and the capability of the quantum neural controller. The results of the computational experiments confirm both the feasibility and effectiveness of the quantum neural controllers.
Keywords
control system synthesis; discrete time systems; learning systems; neurocontrollers; nonlinear control systems; quantum computing; self-adjusting systems; servomechanisms; control systems; direct controller; information processing unit; learning performance evaluation; multilayer quantum neural network; neural network-based servo controller design; nonlinear discrete-time plant control; parallel controller; quantum neural controller; qubit neurons; self-tuning controller; Biological neural networks; Logic gates; Neurons; Quantum computing; Servomotors; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering and Technology (S-CET), 2012 Spring Congress on
Conference_Location
Xian
Print_ISBN
978-1-4577-1965-3
Type
conf
DOI
10.1109/SCET.2012.6341959
Filename
6341959
Link To Document