Explicit model predictive control for linear time-variant systems with application to double-lane-change maneuver

PLoS One. 2018 Dec 4;13(12):e0208071. doi: 10.1371/journal.pone.0208071. eCollection 2018.

Abstract

Explicit model predictive control (eMPC) has been proposed to reduce the huge computational complexity of MPC while maintaining the performance of MPC. Therefore, this control method has been more widely employed in the automotive industry than MPC. In this paper, an eMPC is designed to perform a double-lane-change (DLC) maneuver. This task has been employed to demonstrate the efficacy of controllers in an autonomous driving situation. In this sense, the proposed controller shows better performance than a driver model designed in CarSim at a high vehicle longitudinal velocity. The main contribution of this paper is to present an eMPC for discrete-time linear time-variant (LTV) systems so that the proposed controller can be robust against parameter variation. In a state-space representation of the vehicle, the longitudinal velocity of the vehicle is assumed to be a constant so that the whole system is linear time-invariant (LTI). However, it is inevitable that this velocity varies in an actual driving situation. Therefore, an eMPC controller is designed using an add-on unit to consider the varying parameter without modification of the eMPC solution. The CarSim simulation results of eMPC show enhanced performance compared to that of eMPC for the LTI system.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Automation / methods*
  • Automobile Driving*
  • Automobiles
  • Computer Simulation*
  • Equipment Design
  • Linear Models
  • Software
  • Time Factors

Grants and funding

This study was supported by National Research Foundation of Korea, grant funded by the Korean Government, BK21 (Secured Smart Electric Vehicle Specialize Education Team: SSEV),” and also supported by National Research Foundation of Korea, grant funded by the Korean Government (NRF-2018R1D1A1B07043462).” The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.