DocumentCode :
480218
Title :
Using Neural Network Controller to Control Chaos in an Hexagonal Governor System with a Spring
Author :
Zhang, Jian-Gang ; Chu, Yan-dong ; Li, Xian-feng ; Chang, Ying-xiang
Author_Institution :
Sch. of Math., Phys. & Software Eng., Lanzhou Jiaotong Univ., Lanzhou
Volume :
4
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
781
Lastpage :
784
Abstract :
In this paper, complex dynamic behaviors of the centrifugal flywheel governor systems are studied. These systems have a rich variety of nonlinear behaviors, which are investigated here by numerically integrating the Lagrangian equations of motion. Periodic and chaotic motions can be clearly distinguished by all of the analytical tools applied here, namely bifurcation diagrams, Lyapunov exponents. The chaotic motion of the system is controlled using neural network controller. We obtain the steady periodic orbit of the system under effectively controlling. It is concluded the hyperbolic tangent function is the best candidate as the threshold function of NNC for controlling the centrifugal flywheel governor system.
Keywords :
Lyapunov methods; bifurcation; flywheels; machine control; neurocontrollers; nonlinear control systems; periodic control; springs (mechanical); Lagrangian equations of motion; Lyapunov exponent; bifurcation diagram; centrifugal flywheel governor system; chaos control; chaotic motion; complex dynamic behavior; hexagonal governor system; hyperbolic tangent function; neural network controller; nonlinear behavior; periodic motion; spring; steady periodic orbit; Chaos; Control systems; Flywheels; Lagrangian functions; Motion analysis; Motion control; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Springs; Hopf bifurcation; centrifugal governor; chaos; neural controller;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.940
Filename :
4722735
Link To Document :
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