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

• Published in: 2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE) pp. 1 - 6
• Main Authors: Bueno, Jose Nuno A. D., Rocha, Kaio D. T., Terra, Marco H.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09-11-2020
• Subjects: autonomous ground vehicles subject; control system synthesis; different road; feedback; feedback gains; gain-scheduled robust recursive lateral control; gain-scheduling strategy; lateral control problem; lateral dynamics; linear systems; load conditions; mobile robots; Numerical stability; pedestrians; polytopic uncertainties; recursive gains; Regulators; road vehicles; robust control; robust recursive control algorithm computes; scheduling; Stability analysis; Switches; Symmetric matrices; uncertain systems; Uncertainty; vehicle dynamics
• ISSN: 2643-685X
• DOI: 10.1109/LARS/SBR/WRE51543.2020.9307158

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.