Hierarchical Adaptive Path-Tracking Control for Autonomous Vehicles

Changfang Chen, Yingmin Jia, Minglei Shu, Yinglong Wang

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

This paper presents a hierarchical controller for an autonomous vehicle to track a reference path in the presence of uncertainties in both tire-road condition and external disturbance. The hierarchical control architecture consists of three layers: high, low, and intermediate levels. The upper-layer module deals with the vehicle motion control objective, which generates the desired longitudinal/lateral forces and yaw moment. The low-level module handles the braking control for each wheel based on the wheel slip dynamics. The intermediate-level controller generates the longitudinal slip reference for the low-level brake control module and the front-wheel steering angles. To cope with the unknown and nonuniform road condition parameters appearing in the actuator models, an adaptive law is designed for each wheel, and the convergence of the adaptive parameters is guaranteed under a certain persistency-of-excitation condition. The stability of the integrated control system is analyzed by utilizing a Lyapunov function approach. Simulation results are included to illustrate the proposed control scheme.

Original languageEnglish
Article number7108027
Pages (from-to)2900-2912
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume16
Issue number5
DOIs
Publication statusPublished - 2015

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