Gain-Scheduled Robust Recursive Lateral Control for Autonomous Ground Vehicles Subject to Polytopic Uncertainties

Author(s)

Bueno, Jose Nuno A. D. ; Rocha, Kaio D. T. ; Terra, Marco H. ; Goncalves, LMG ; Drews, PLJ ; DaSilva, BMF ; DosSantos, DH ; DeMelo, JCP ; Curvelo, CDF ; Fabro, JA

• Document type: Journal article
• Source: 2020 XVIII LATIN AMERICAN ROBOTICS SYMPOSIUM, 2020 XII BRAZILIAN SYMPOSIUM ON ROBOTICS AND 2020 XI WORKSHOP OF ROBOTICS IN EDUCATION (LARS-SBR-WRE 2020); v. N/A, p. 6-pg., 2020-01-01.

Abstract

This paper addresses the lateral control problem for autonomous ground vehicles. In order to better capture the behavior of lateral dynamics, the model is subject to polytopic uncertainties based on different road and load conditions. These uncertainties can potentially degrade the performance of the system and, as a consequence, endanger passengers, pedestrians and surrounding vehicles. It is crucial, then, that the controller handles these parametric deviations to preserve safety and stability. To this end, a robust recursive control algorithm computes a set of feedback gains that minimizes the trajectory tracking error state. Meanwhile, a gain-scheduling strategy interchanges among these recursive gains at each instant. A numerical simulation is also provided to illustrate the effectiveness of the proposed method. (AU)

• FAPESP's process: 17/16346-4 - Communication network fault tolerant control for coordinated movement of heterogeneous robots
• Grantee: Kaio Douglas Teófilo Rocha
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
• Grantee: Marco Henrique Terra
• Support Opportunities: Research Projects - Thematic Grants