DocumentCode :
2044325
Title :
Backward movement control of a trailer truck system using neuro-controllers evolved by genetic algorithm
Author :
Kinjo, Hiroshi ; Wang, Bingchen ; Yamamoto, Tetsuhiko
Author_Institution :
Dept. of Mech. Eng., Ryukyus Univ., Okinawa, Japan
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
253
Abstract :
Control of the backing movement of a trailer-truck system is very difficult because the dynamics are nonlinear. In this paper, a new control method using neuro- controllers (NCs) developed using a genetic algorithm (GA) is presented. We use a 3-5-1 neural network to control the steering angle. In the GA process, a simple evaluation function is used. We use only final configurations of the trailer-truck system after control trails in the evaluation function. We apply the control method not only to simulations but also to experiments. The results of both show that the control method is very effective. For verifying the effectiveness of this control method, we employ another control method, linear quadratic regulator (LQR). The results show that the control method using NCs evolved by GA exhibits better control performance than the LQR
Keywords :
genetic algorithms; motion control; multilayer perceptrons; neurocontrollers; nonlinear control systems; optimal control; vehicles; 3-5-1 neural network; GA; LQ control; LQR; backing movement; backward movement control; genetic algorithm; linear quadratic regulator; neurocontrollers; nonlinear dynamics; steering angle control; trailer truck system; valuation function; Control systems; Feedforward neural networks; Genetics; Kinematics; Linear systems; Neural networks; Regulators; Riccati equations; Sampling methods; TV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE
Conference_Location :
Nagoya
Print_ISBN :
0-7803-6456-2
Type :
conf
DOI :
10.1109/IECON.2000.973159
Filename :
973159
Link To Document :
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