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
Link To Document :
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