RISE-Based Integrated Motion Control of Autonomous Ground Vehicles With Asymptotic Prescribed Performance

Research output: Contribution to journalArticle

Authors

External departments

  • University of Texas at Austin
  • University of Science and Technology of China
  • Xiamen University
  • Coventry University
  • Beijing Institute of Technology
  • Kunming University of Science and Technology
  • University of Leeds

Details

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Early online date12 Nov 2019
DOIs
Publication statusE-pub ahead of print - 12 Nov 2019
Externally publishedYes
Publication type

Research output: Contribution to journalArticle

Abstract

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.

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