Title :
Vehicle stability control based on adaptive PID control with single neuron network
Author :
Jinzhu, Zhang ; Hongtian, Zhang
Author_Institution :
Coll. of Power & Energy Eng., Harbin Eng. Univ., Harbin, China
Abstract :
According to the nonlinear and parameter time-varying characteristics of vehicle stability control, a novel algorithm of vehicle stability adaptive PID control with single neuron network was proposed. Based on self-learning and adaptive ability of single neural network, the parameters of vehicle stability PID controller were self-tuning on-line and the problem of large computation time brought by traditional adaptive PID control was avoided, in which the parameters of reference model of the controlled system must be identified with large calculation burden. 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; vehicle dynamics; computation time; nonlinear time-varying characteristics; parameter time-varying characteristics; reference model; single neuron network; vehicle lateral stability control system; vehicle stability adaptive PID controller; vehicle stability control; Adaptive control; Computational modeling; Computer networks; Control system synthesis; Neural networks; Neurons; Programmable control; Robust stability; Three-term control; Vehicles; PID; nonlinear; single neuron network; vehicle stability;
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
DOI :
10.1109/CAR.2010.5456803