Open AccessAdaptive non‐linear trajectory tracking control for lane change of autonomous four‐wheel independently drive electric vehicles
Author(s) -
Guo Jinghua,
Luo Yugong,
Li Keqiang
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2017.0278
Subject(s) - control theory (sociology) , trajectory , controller (irrigation) , backstepping , vehicle dynamics , control engineering , lyapunov function , engineering , adaptive control , computer science , nonlinear system , control (management) , automotive engineering , artificial intelligence , physics , astronomy , quantum mechanics , agronomy , biology
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.