View in EDS

Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.

Saved in:
Bibliographic Details
Title: Adaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles.
Authors: Guo, Jinghua, Luo, Yugong, Li, Keqiang
Source: IET Intelligent Transport Systems (Wiley-Blackwell); Sep2018, Vol. 12 Issue 7, p712-720, 9p
Subject Terms: VEHICULAR ad hoc networks, BACKSTEPPING control method, LANE changing, ADAPTIVE control systems, LATERAL loads
Abstract: Since autonomous four‐wheel independently drive electric vehicles have the characteristics of parameter uncertainties, non‐linearities and redundant actuators, trajectory tracking control for lane change of autonomous electric vehicles is regarded as a challenging task. A novel non‐linear trajectory tracking control strategy is designed for lane changing manoeuvre. First, a dynamic trajectory planning strategy is proposed to update the desired trajectory according to the real‐time information acquired through vehicle‐to‐vehicle communications. Second, a robust adaptive non‐linear fuzzy backstepping controller is presented to produce the generalised forces/moment of autonomous electric vehicles, and the stability of this proposed adaptive controller is proven by the Lyapunov theory. Then, the quadratic optimisation goal function of tire energy dissipated power is constructed, and the optimal control allocation method is proposed to produce the desired longitudinal and lateral tire forces of autonomous electric vehicles. Finally, simulation results manifest that the proposed adaptive control strategy has the distinguished tracking performance. [ABSTRACT FROM AUTHOR]
Copyright of IET Intelligent Transport Systems (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:Since autonomous four‐wheel independently drive electric vehicles have the characteristics of parameter uncertainties, non‐linearities and redundant actuators, trajectory tracking control for lane change of autonomous electric vehicles is regarded as a challenging task. A novel non‐linear trajectory tracking control strategy is designed for lane changing manoeuvre. First, a dynamic trajectory planning strategy is proposed to update the desired trajectory according to the real‐time information acquired through vehicle‐to‐vehicle communications. Second, a robust adaptive non‐linear fuzzy backstepping controller is presented to produce the generalised forces/moment of autonomous electric vehicles, and the stability of this proposed adaptive controller is proven by the Lyapunov theory. Then, the quadratic optimisation goal function of tire energy dissipated power is constructed, and the optimal control allocation method is proposed to produce the desired longitudinal and lateral tire forces of autonomous electric vehicles. Finally, simulation results manifest that the proposed adaptive control strategy has the distinguished tracking performance. [ABSTRACT FROM AUTHOR]
ISSN:1751956X
DOI:10.1049/iet-its.2017.0278