Robust steering assistance control for tracking large-curvature path considering uncertainties of driver’s steering behavior

Autor: Guodong Yin, Jingjing Xia, Pu Li, Zhenwu Fang, Mengmeng Dai, Jinxiang Wang
Rok vydání: 2021
Předmět:
Zdroj: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 235:2013-2028
ISSN: 2041-2991
0954-4070
DOI: 10.1177/0954407020976827
Popis: A human-machine shared steering control is presented in this paper for tracking large-curvature path, considering uncertainties of driver’s steering characteristics. A driver-vehicle-road (DVR) model is proposed in which uncertain characteristic parameters are defined to describe the human driver’s steering behaviors in tracking large-curvature path. Then the radial basis function neural network (RBF) is used to estimate parameters of different drivers’ characteristics and to obtain the boundaries of these parameters. Parameter uncertainties of the driver’s steering characteristics and time-varying vehicle speed of the DVR model are handled with the Takagi-Sugeno (T-S) fuzzy logic. And these parameter uncertainties are considered in the design of the shared steering controller. Then based on the DVR model, a T-S fuzzy full-order dynamic compensator with D-pole assignment is designed to assist driver’s steering for tracking path with large curvature. Simulation results show that the proposed controller can provide individual levels of steering assistance in path following according to driver’s proficiency, and can improve driving comfort significantly.
Databáze: OpenAIRE