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 |
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Rok vydání: | 2021 |
Předmět: |
050210 logistics & transportation
Computer science Mechanical Engineering 020208 electrical & electronic engineering 05 social sciences Control (management) Aerospace Engineering 02 engineering and technology Tracking (particle physics) Curvature Steering control Control theory 0502 economics and business Path (graph theory) 0202 electrical engineering electronic engineering information engineering |
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 |
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