Piecewise affine modeling and hybrid optimal control of intelligent vehicle longitudinal dynamics for velocity regulation. (1st January 2022)

• Record Type: Journal Article
• Authors: Sun, Xiaoqiang; Wu, Pengcheng; Cai, Yingfeng; Wang, Shaohua; Chen, Long
• Is Part Of: Mechanical systems and signal processing. Volume 162(2022)
• Publication Date: 2022-01-01
• Subjects: Longitudinal dynamics control -- Intelligent vehicle -- Piecewise affine system -- Mixed logical dynamical model -- Hybrid model predictive control; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108089
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A complete model of vehicle longitudinal dynamics is built based on the PWA method. A computational MLD framework is derived based on the developed system PWA model. The HMPC control strategy for the MLD model of the intelligent vehicle is designed. Abstract: In this paper, a novel piecewise affine (PWA) modeling framework and a hybrid optimal control scheme based on the developed PWA model for the intelligent vehicle longitudinal dynamics are proposed. The proposed methodology approximates the nonlinear characteristics of the system major components, i.e. the engine, the automatic transmission and the tire, using the PWA representation method firstly. Due to the affine submodel switching behaviors of the PWA model and the fact that the intelligent vehicle must be worked in two discrete modes (driving and braking) for regulating the longitudinal velocity automatically, the control procedure of the intelligent vehicle longitudinal dynamics actually shows a hybrid nature with both continuous variables and discrete events. Thus, to further solve the system hybrid control problem, the intelligent vehicle longitudinal dynamics whose major components are modelled in the PWA form is further transformed into a computational mixed logical dynamical (MLD) model in this work, based on which a hybrid model predictive control (HMPC) strategy, which can simultaneously calculate the switching sequences of the intelligent vehicle longitudinal working modes (binary control inputs) and the throttle angle and braking pressure (continuous control inputs) during autonomous velocity regulation, is designed by solving a mixed-integer quadratic programming (MIQP) problem. Simulation and experimental results are finally provided to verify the superior control performance of the designed hybrid controller in longitudinal velocity regulation under typical driving conditions.