TY - JOUR
T1 - RISE-Based Integrated Motion Control of Autonomous Ground Vehicles with Asymptotic Prescribed Performance
AU - Hu, Chuan
AU - Gao, Hongbo
AU - Guo, Jinghua
AU - Taghavifar, Hamid
AU - Qin, Yechen
AU - Na, Jing
AU - Wei, Chongfeng
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021/9
Y1 - 2021/9
N2 - This article investigates the integrated lane-keeping and roll control for autonomous ground vehicles (AGVs) considering the transient performance and system disturbances. The robust integral of the sign of error (RISE) control strategy is proposed to achieve the lane-keeping control purpose with rollover prevention, by guaranteeing the asymptotic stability of the closed-loop system, attenuating systematic disturbances, and maintaining the controlled states within the prescribed performance boundaries. Three contributions have been made in this article: 1) a new prescribed performance function (PPF) that does not require accurate initial errors is proposed to guarantee the tracking errors restricted within the predefined asymptotic boundaries; 2) a modified neural network (NN) estimator which requires fewer adaptively updated parameters is proposed to approximate the unknown vertical dynamics; and 3) the improved RISE control based on PPF is proposed to achieve the integrated control objective, which analytically guarantees both the controller continuity and closed-loop system asymptotic stability by integrating the signum error function. The overall system stability is proved with the Lyapunov function. The controller effectiveness and robustness are finally verified by comparative simulations using two representative driving maneuvers, based on the high-fidelity CarSim-Simulink simulation.
AB - This article investigates the integrated lane-keeping and roll control for autonomous ground vehicles (AGVs) considering the transient performance and system disturbances. The robust integral of the sign of error (RISE) control strategy is proposed to achieve the lane-keeping control purpose with rollover prevention, by guaranteeing the asymptotic stability of the closed-loop system, attenuating systematic disturbances, and maintaining the controlled states within the prescribed performance boundaries. Three contributions have been made in this article: 1) a new prescribed performance function (PPF) that does not require accurate initial errors is proposed to guarantee the tracking errors restricted within the predefined asymptotic boundaries; 2) a modified neural network (NN) estimator which requires fewer adaptively updated parameters is proposed to approximate the unknown vertical dynamics; and 3) the improved RISE control based on PPF is proposed to achieve the integrated control objective, which analytically guarantees both the controller continuity and closed-loop system asymptotic stability by integrating the signum error function. The overall system stability is proved with the Lyapunov function. The controller effectiveness and robustness are finally verified by comparative simulations using two representative driving maneuvers, based on the high-fidelity CarSim-Simulink simulation.
KW - Autonomous ground vehicles (AGVs)
KW - lane keeping
KW - neural network (NN)
KW - prescribed performance control (PPC)
KW - robust integral of the sign of the error (RISE)
KW - roll control
UR - https://www.scopus.com/pages/publications/85113265885
U2 - 10.1109/TSMC.2019.2950468
DO - 10.1109/TSMC.2019.2950468
M3 - Article
AN - SCOPUS:85113265885
SN - 2168-2216
VL - 51
SP - 5336
EP - 5348
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 9
M1 - 8897128
ER -