• DocumentCode
    246450
  • Title

    Design and Simulation for Path Tracking Control of a Commercial Vehicle Using MPC

  • Author

    Garcia, O. ; Ferreira, J.V. ; Miranda Neto, A.

  • Author_Institution
    Autonomous Mobility Lab. (LMA in Portuguese), UNICAMP, Campinas, Brazil
  • fYear
    2014
  • fDate
    18-23 Oct. 2014
  • Firstpage
    61
  • Lastpage
    66
  • Abstract
    The design of the robotic vehicle VILMA at UNICAMP is developed in-vehicle platform Fiat Punto. In addition to a set of sensors, actuators, mechanism and components (hardware and/or software), new technologies should be developed in support of Automation, Control, Perception, Localization and Navigation. This work presents the design and simulation of path tracking control using model predictive control (MPC) which attempts to exploit the characteristics of the structured environment where the future path is previously known. The model for design the controller is based in a single tracking model of the vehicle and in a model of the steering which the state variables are observed by the Extended Kalman Filter (EKF). Finally, it is explained how the path is smoothed generating an arc between the points and making an optimization process by the gradient algorithm.
  • Keywords
    Kalman filters; control system synthesis; gradient methods; mobile robots; nonlinear filters; path planning; predictive control; road vehicles; EKF; Fiat Punto; MPC; UNICAMP; VILMA; actuators; autonomous vehicle; commercial vehicle; extended Kalman filter; gradient algorithm; in-vehicle platform; model predictive control; optimization process; path tracking control design; path tracking control simulation; robotic vehicle; sensors; Equations; Mathematical model; Predictive control; Sensors; Vectors; Vehicle dynamics; Vehicles; Autonomous Vehicle; Model Predictive Control; Path Tracking; VDA test;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics: SBR-LARS Robotics Symposium and Robocontrol (SBR LARS Robocontrol), 2014 Joint Conference on
  • Conference_Location
    Sao Carlos
  • Print_ISBN
    978-1-4799-6710-0
  • Type

    conf

  • DOI
    10.1109/SBR.LARS.Robocontrol.2014.23
  • Filename
    7024257