TY - JOUR
T1 - Gain-Scheduled LPV/H∞ Strategy for Steering and Braking Coordination of Intelligent Commercial Vehicle Lateral Automation
AU - Sun, Yingbo
AU - Song, Jiarui
AU - He, Haohui
AU - Xu, Tao
AU - Ji, Xuewu
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - This paper studies the steering and braking coordination control in path tracking problems of intelligent commercial vehicles (ICVs). A gain-scheduled LPV/H∞ strategy for ICVs is proposed to improve tracking performance, driving stability and robustness of controller. While establishing lateral-yaw-roll dynamics, a steering and braking coordination control strategy based on scheduling parameters is designed to enhance tracking accuracy and yaw-roll stability under different driving conditions. The robust performance has been guaranteed in the H∞ robust controller by considering the parameter uncertainties in lateral-yaw-roll dynamic model, unmodeled subsystem as well as ground mechanics and aerodynamics disturbance comprehensively. Also, the dynamic characteristics of time-varying parameters and determination of robust boundary is addressed through a LPV polyhedral structure and a novel Gaussian Process Regression (GPR) model respectively, which reduces the conservativeness of H∞ robust controller. Sufficient conditions for closed-loop stability under the diverse disturbances are provided by the Lyapunov method analytically, which ensures the feasibility of system. The results of simulations on MATLAB-Trucksim platform demonstrate that the proposed controller can significantly enhance tracking accuracy, driving stability, and robustness, which guarantees the feasibility and capability of driving in diverse scenarios.
AB - This paper studies the steering and braking coordination control in path tracking problems of intelligent commercial vehicles (ICVs). A gain-scheduled LPV/H∞ strategy for ICVs is proposed to improve tracking performance, driving stability and robustness of controller. While establishing lateral-yaw-roll dynamics, a steering and braking coordination control strategy based on scheduling parameters is designed to enhance tracking accuracy and yaw-roll stability under different driving conditions. The robust performance has been guaranteed in the H∞ robust controller by considering the parameter uncertainties in lateral-yaw-roll dynamic model, unmodeled subsystem as well as ground mechanics and aerodynamics disturbance comprehensively. Also, the dynamic characteristics of time-varying parameters and determination of robust boundary is addressed through a LPV polyhedral structure and a novel Gaussian Process Regression (GPR) model respectively, which reduces the conservativeness of H∞ robust controller. Sufficient conditions for closed-loop stability under the diverse disturbances are provided by the Lyapunov method analytically, which ensures the feasibility of system. The results of simulations on MATLAB-Trucksim platform demonstrate that the proposed controller can significantly enhance tracking accuracy, driving stability, and robustness, which guarantees the feasibility and capability of driving in diverse scenarios.
KW - Intelligent commercial vehicles
KW - LPV/H strategy
KW - lateral automation
KW - path tracking
UR - http://www.scopus.com/inward/record.url?scp=85182951920&partnerID=8YFLogxK
U2 - 10.1109/TIV.2024.3353296
DO - 10.1109/TIV.2024.3353296
M3 - Article
AN - SCOPUS:85182951920
SN - 2379-8858
VL - 9
SP - 3742
EP - 3753
JO - IEEE Transactions on Intelligent Vehicles
JF - IEEE Transactions on Intelligent Vehicles
IS - 2
ER -