Title :
Vehicle lateral stability control based on single neuron network
Author :
Zhang, Jinzhu ; Zhang, Hongtian
Author_Institution :
Harbin Eng. Univ., Harbin, China
Abstract :
According to the nonlinear and parameter time-varying characteristics of vehicle lateral stability control, a novel algorithm of vehicle lateral stability control based on single neuron network was proposed. Based on self-learning and adaptive ability of single neural network, the parameters of vehicle lateral stability controller were self-tuning on-line and the problem of large computation time brought by traditional PID control was avoided, in which the parameters of reference model of the controlled system must be identified with large calculation burden. The hardware in loop simulation platform is established based on the LabVIEW system, and the vehicle lateral stability control system is tested on the platform. The results of the simulation show this algorithm can effectively make vehicle keep and track the desired direction, and has good robustness and adaptability for vehicle lateral stability control system.
Keywords :
adaptive control; learning systems; neurocontrollers; nonlinear control systems; stability; three-term control; time-varying systems; vehicles; LabVIEW system; PID control; adaptive ability; loop simulation platform; nonlinear time varying characteristics; parameter time varying characteristics; single neuron network; vehicle lateral stability control; Adaptive control; Computer networks; Control system synthesis; Hardware; Neural networks; Neurons; Programmable control; Robust stability; Three-term control; Vehicles; hardware in loop simulation; single neuron network; vehicle lateral stability;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5499067
