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A new explicit dynamic path tracking controller using generalized predictive control

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  • Robot and Applications
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Abstract

Outdoor mobile robots must perform operations with ever-increasing speed and distance. Therefore we are interested in designing controllers of fast rovers which improve mobile robot capacity in natural environment. When designing autonomous path tracking systems for fast rovers, a major problem is the dynamic effect and the non-linearity of the model. Several control laws have been designed to resolve the problem by separating the dynamic of the robot at the problem of trajectory tracking.

This paper presents a path tracking controller for a fast rover with independent front and rear steering. In the first step, a dynamic model of a vehicle that moves on a horizontal plane was developed. Next, the projection of the position of the vehicle in the absolute reference frame was used to define the kinematics non-linear model. We present a new approach to solving a tracking path problem by applying Non-linear Continuous-time Generalized Predictive Control (NCGPC). The controller is based on the dynamic model of a bicycle like vehicle which considers the lateral slippage of the wheels. The prediction model allows anticipation of future changes in setpoints in accordance with the dynamic constraints of the system. Experimental results, show a good control accuracy and appears to be robust with respect to environmental and robot state changes.

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Author information

Authors and Affiliations

  1. Industrial Engineering Department, College of Engineering, King Saud University - KSU, P. O. Box 800, Riyadh, 11421, Saudi Arabia

    Mohamed Krid

  2. Sorbonne Universités, UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris and CNRS UMR 7222 PARIS, 75252, cedex 05, France

    Faiz Benamar

  3. Irstea - Institut national de Recherche en Sciences et Technologies pour l’Environnement et l’Agriculture, 63178, Aubière cedex, France

    Roland Lenain

Authors
  1. Mohamed Krid
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  2. Faiz Benamar
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  3. Roland Lenain
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Corresponding author

Correspondence to Mohamed Krid.

Additional information

Recommended by Associate Editor Yingmin Jia under the direction of Editor Myo Taeg Lim. This work was supported by the French ANR project EquipEx RobotEx (ANR-10-. EQPX-44).

Mohamed Krid was born in Sfax, Tunisia in 1983. He is graduate from the Ecole Nationale Ingenieur de Sfax (ENIS Tunisia), as well as Master degree in Génie des Systèmes Automatisés (GSA) from INSA Lyon. In 2012, he received his Ph.D. degree from the Université Pierre et Marie Curie - UPMC. He is currently an assistance professor at King Saud Univercity. Dr Mohamed Krid developed his researches in the field of design and control of mobile robot and autonomous systems.

Faiz Benamar was born in Sfax, Tunisia in 1965. He is graduate from the Ecole Nationale Supérieure des Arts et Métiers (France) and he received Ph.D. degree in 1994 from the Université Pierre et Marie Curie - UPMC. He is currently a full professor at UPMC. Dr Faiz Ben Amar developed his researches in the field of design and control of high mobility locomotion systems and self-reconfigurable modular systems. He is interested in modeling and simulation of multibody systems interacting with complex environment.

Roland Lenain is a research fellow in Irstea, and currently the leader of the team Romea, dedicated to robotic and mobility for environment and agriculture. His research interests include the modeling and the control of mobile robots, submitted to uncertain and dynamical effects. Currently in Irstea since 2006, after achieving a post doctoral position at the department of Automatic Control in Lund University (Sweden). He received his Ph.D. in 2005 on the topic of automatic control of farm vehicle from Blaise Pascal University in Clermont-Ferrand. He was graduated from IFMA (French Institute for Advanced Mechanics) in 2002.

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Krid, M., Benamar, F. & Lenain, R. A new explicit dynamic path tracking controller using generalized predictive control. Int. J. Control Autom. Syst. 15, 303–314 (2017). https://doi.org/10.1007/s12555-015-0160-6

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  • DOI: https://doi.org/10.1007/s12555-015-0160-6

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