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Nonlinear adaptive controller applied to an Antilock Braking System with parameters variations

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  • Control Theory and Applications
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Abstract

The control of an Antilock Braking System is a difficult problem, due to its nonlinear dynamics and to the uncertainties in its characteristics and parameters. To overcome these issues, in this work an adaptive controller is proposed. The controller is designed under the assumption that the friction coefficient is unknown, and further perturbing frictions act on the system. Finally, the convergence to an ε-ball of the origin is proved when these perturbing parameters vary. The performance of the nonlinear dynamic controllers is evaluated by some experimental tests on a mechatronic system representing a quarter-car model. The results show how the controller ensures the tracking of the desired reference and identifies the unknown parameters.

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Author information

Authors and Affiliations

  1. Departamento de Ciencias Tecnológicas, Universidad de Guadalajara, Centro Universitario de la Ciénega, Av. Universidad 1115, 47820, Ocotlán, Jalisco, México

    Cuauhtémoc Acosta Lúa & María Eugenia Sánchez Morales

  2. Department of Information Engineering, Computer Science and Mathematics, and with the Center of Excellence DEWS, University of L’Aquila, Via Vetoio, Loc. Coppito, 67100, L’Aquila, Italy

    Stefano Di Gennaro

Authors
  1. Cuauhtémoc Acosta Lúa
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  2. Stefano Di Gennaro
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  3. María Eugenia Sánchez Morales
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Correspondence to Cuauhtémoc Acosta Lúa.

Additional information

Recommended by Associate Editor Changchun Hua under the direction of Editor Myo Taeg Lim. The authors thank Gerardo de Jesús Díaz for his help in the preparation of the experimental setup. The authors also thank the anonymous reviewers for their comments, which allowed improving the paper.

Cuauhtemoc Acosta Lua obtained the B.Sc. in Electronic Engineering from the Technological Institute of Morelia (2001). He obtained the Master (2003) and Ph.D. (2007) in Science in Electrical Engineering from CINVESTAV Guadalajara Unit. He visited INSA Lyon, France, and the Center of Excellence DEWS in L’Aquila, Italy. He carried out his Postdoctoral studies at DEWS and at the Centre for Research and Implementation of the Ford Motor Company. Presently he is engaged in the development of nonlinear techniques for vehicle control, and observers for nonlinear systems.

Stefano Di Gennaro obtained the degree in Nuclear Engineering in 1987 (summa cum laude), and the Ph.D. degree in System Engineering in 1992, both from the University of Rome “La Sapienza”, Rome, Italy. In October 1990 he joined the Department of Electrical Engineering, University of L’Aquila, as Assistant Professor of Automatic Control. Since 2001, he has been an Associate Professor of Automatic Control at the University of L’Aquila. In 2012 he joined the Department of Information Engineering Computer Science and Mathematics. He is also with the Center of Excellence DEWS. He holds courses on Automatic Control and Nonlinear Control. He was visiting various research centers, among which the Department of Electrical Engineering of the Princeton University, the Department of Electrical Engineering and Computer Science at Berkeley, and the Centro de Investigación y Estudios Avanzados del IPN, at Guadalajara. He is working in the area of hybrid systems, regulation theory, and applications of nonlinear control.

Maria Eugenia Sanchez Morales obtained the degree in physics in the Benemérita Autonomous University of Puebla Universidad (2001). She obtained the Master (2003) and the Ph.D. (2007) in Science in Optics from CIO. She participated in stays at CICESE Ensenada, Mexico; UNAM Mexico, DF; UAM Madrid, Spain and Laboratory of Physical Chemistry of Luminescent Materials in University Lyon II, Lyon France. Currently she works at the University of Guadalajara on the dynamics of movements applied to industry and dynamical systems.

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Acosta Lúa, C., Di Gennaro, S. & Sánchez Morales, M.E. Nonlinear adaptive controller applied to an Antilock Braking System with parameters variations. Int. J. Control Autom. Syst. 15, 2043–2052 (2017). https://doi.org/10.1007/s12555-016-0136-1

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  • DOI: https://doi.org/10.1007/s12555-016-0136-1

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