A Robust Integrated Control Framework for Trajectory Tracking of the Distributed Drive Autonomous Electric Vehicles
Author(s) -
Hamid Rahmanei,
Abbas Aliabadi,
Ali Ghaffari,
Shahram Azadi
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3616936
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The problem of coordinated control for autonomous electric vehicles has attracted many attentions in the literature. However, the controllers employing four independent torque and brake, and active front steering actuators still need more investigation. In this paper, an integrated control structure is proposed to navigate the autonomous vehicle in trajectory tracking task at high speeds. A kinematic-based approach is introduced to estimate the longitudinal forces of each wheel. The steering angle is designed based on a robust sliding mode control, which is responsible for the convergence of the lateral errors to zero. The proof of stability for both longitudinal and lateral controllers in the integrated framework are provide based on the Lyapunov’s stability theorem. Finally, a co-simulation is performed in MATLAB/Simulink and Carsim software to appraise the performance of the control system. The results show that the control method is able to perform the trajectory tracking in high-speed lane change. Additionally, the proposed control system performs better in terms of maximum amplitude of errors and root mean square of errors when compared to the results of other research. Furthermore, the proposed robust control framework shows promising results in the presence of external disturbance and parametric uncertainties.
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