Open AccessAdaptive dynamic surface longitudinal tracking control of autonomous vehicles
Author(s) -
Guo Jinghua,
Luo Yugong,
Li Keqiang,
Guo Lie
Publication year - 2019
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.2018.5534
Subject(s) - tracking (education) , computer science , adaptive control , control (management) , road surface , control theory (sociology) , computer vision , artificial intelligence , control engineering , engineering , psychology , pedagogy , civil engineering
Autonomous vehicles offer the opportunity of significant benefits to social life, such as improving safety, reducing crashes, decreasing fuel consumption and so on. This study presents a novel adaptive dynamic surface longitudinal tracking control strategy for autonomous vehicles to deal with the effects of non‐linearities and parametric uncertainties of vehicles. First, a longitudinal vehicle model, which can describe the features of non‐linear and external disturbances of autonomous vehicles, is established. Then, an adaptive dynamic surface longitudinal control system is proposed to avoid the explosion of complexity. In addition, an adaptive estimated approach based on neural networks technique is designed to approximate the model uncertainties of autonomous vehicles. The stability of the proposed adaptive control system is discussed by the Lyapunov theory. It has been illustrated for both simulation and experimental tests that the proposed adaptive control system has a remarkable longitudinal tracking performance of the autonomous vehicle.