Coordinated motion control for automated vehicles considering steering and driving force saturations. (January 2020)

• Record Type: Journal Article
• Authors: Xia, Hongyang; Chen, Jiqing; Liu, Zhaolin; Lan, Fengchong
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 42:Number 1(2020)
• Page Start: 157
• Page End: 166
• Publication Date: 2020-01
• Subjects: Coordinated motion control -- input saturations -- autonomous vehicle -- sliding-mode control -- RBFNN approximation; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331219879342
• Languages: English
• ISSNs: 0142-3312

Abstract

Steering angle and driving force saturations are inevitable in autonomous vehicle motions, which will degrade the motion control performance and even deteriorate the driving safety. In addition, the strong coupling of lateral and longitudinal motions of autonomous vehicles also contributes to the saturations damage and increases the control difficulty. To reduce these negative impacts on motion control, a novel motion controller for automated vehicles is presented in this paper. Firstly, an extended 3 degree of freedom vehicle dynamic model is built with the unknown saturations, strong-coupled motion characteristics and external disturbance considered simultaneously. Then, a coordinated controller is designed to complete motion control task based on sliding-mode control (SMC) and non-singular fast terminal sliding-mode control (NFTSM). Moreover, a three-layer radial basis function neural network (RBFNN) is adopted as a compensator to approximate modelling uncertainties. Based on Lyapunov stability theory, the uniform ultimate boundednesses of motion control errors are guaranteed. Simulation results show that the proposed controller owns smaller steady-state errors and faster convergence speed.