Title: Path tracking controller design for autonomous vehicle based on robust tube MPC

Authors: Chuanyang Sun; Han Dong; Xin Zhang; Cong Geng

Addresses: Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic, and Control Engineering, Beijing Jiaotong University, Beijing 100044, China ' Perceptual System Testing Centre, Suzhou Automotive Research Institute, Tsinghua University, Suzhou, 215200, China ' Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic, and Control Engineering, Beijing Jiaotong University, Beijing 100044, China ' Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic, and Control Engineering, Beijing Jiaotong University, Beijing 100044, China

Abstract: A robust tube MPC controller based on tube-division with a linear time-varying (LTV) model is proposed for autonomous vehicle path tracking. To reduce the conservativeness, a novel offline method is designed to calculate the tubes by dividing the original N-steps invariant sets into sequences of tighter candidate tubes. The propagation limits of the vehicle time-varying parameters within a prediction horizon are used in the division to ensure each candidate tube contains any state trajectory starting at its origin. A corresponding tube will be selected instead of being calculated online at each sampling instant in terms of vehicle states, which makes a more efficient online computation. The results of the simulation show the improved performance of the proposed robust tube MPC controller.

Keywords: path tracking; autonomous vehicle; dynamic model; time-varying system; model uncertainties; robust tube MPC; invariant sets; tube design.

DOI: 10.1504/IJVD.2020.113913

International Journal of Vehicle Design, 2020 Vol.82 No.1/2/3/4, pp.120 - 139

Received: 31 Oct 2019
Accepted: 16 May 2020
Published online: 01 Apr 2021 *

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