@ARTICLE{ iet:/content/journals/10.1049/iet-its.2017.0278, author = {Jinghua Guo}, author = {Yugong Luo}, author = {Keqiang Li}, keywords = {dynamic trajectory planning strategy;optimal control allocation method;lane changing manoeuvre;robust adaptive nonlinear fuzzy backstepping controller;parameter uncertainties characteristics;autonomous four-wheel independently drive electric vehicles;redundant actuators;adaptive nonlinear trajectory tracking control strategy;vehicle-to-vehicle communications;quadratic optimisation goal function;tire energy dissipated power;Lyapunov theory;}, ISSN = {1751-956X}, language = {English}, 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.}, title = {Adaptive non-linear trajectory tracking control for lane change of autonomous four-wheel independently drive electric vehicles}, journal = {IET Intelligent Transport Systems}, issue = {7}, volume = {12}, year = {2018}, month = {September}, pages = {712-720(8)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=308ct2212lvv3.x-iet-live-01content/journals/10.1049/iet-its.2017.0278} }