Research Article Dynamic Control Applied to a Laboratory Antilock Braking System Cuauhtémoc Acosta Lúa, 1 Bernardino Castillo Toledo, 2 Stefano Di Gennaro, 3 and Marcela Martinez-Gardea 1 1 Departamento de Ciencias Tecnol´ ogicas, Universidad de Guadalajara, Centro Universitario de la Ci´ enega, Avenida Universidad 1115, 47820 Ocotl´ an, JAL, Mexico 2 Centro de Investigaci´ on y de Estudios Avanzados (CINVESTAV) del IPN, Unidad Guadalajara, Avenida Cient´ ıica, Colonia El Baj´ ıo, 4010 Zapopan, JAL, Mexico 3 Department of Information Engineering, Computer Science and Mathematics, Center of Excellence DEWS, University of L’Aquila, Via G. Gronchi 18, 67100 L’Aquila, Italy Correspondence should be addressed to Cuauht´ emoc Acosta L´ ua; cuauhtemoc.acosta@cuci.udg.mx Received 11 September 2014; Revised 30 December 2014; Accepted 30 December 2014 Academic Editor: Mehmet Onder Efe Copyright © 2015 Cuauht´ emoc Acosta L´ ua et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. he control of an antilock braking system is a diicult problem due to the existence of nonlinear dynamics and uncertainties of its characteristics. To overcome these issues, in this work, a dynamic nonlinear controller is proposed, based on a nonlinear observer. To evaluate its performance, this controller has been implemented on an ABS Laboratory setup, representing a quarter car model. he nonlinear observer reconstructs some of the state variables of the setup, assumed not measurable, to establish a fair benchmark for an ABS system of a real automobile. he dynamic controller ensures exponential convergence of the state estimation, as well as robustness with respect to parameter variations. 1. Introduction he antilock braking system (ABS) was developed to prevent the wheels from locking up while braking. his prevents the slippage of the wheels on the surface, adjusting the brake luid pressure level of each wheel, and helps the driver to keep the control on the vehicle [1–3]. In fact, the ABS is designed to increase the braking eiciency, maintaining the manoeuvrability of the vehicle and reducing the driving instability, while decreasing the braking distance. Modern ABS systems try to not only prevent the wheels from locking up, but also aim to obtain maximum wheel grip on the surface while the vehicle is braking [4, 5]. he technical diiculties in successfully implementing the antilock concept contained in the 1936 patent for an “apparatus for preventing lock braking of wheels in a motor vehicle,” by Robert Bosch [6], were solved between 1967 and 1970, when Mercedes-Benz engineers changed the mechanical sensors for contactless sensors operating under the induction principle [7]. Finally, when the electronic integrated circuits were small and robust enough, it was possible to record data from the wheel’s sensors and to use more reliable actuators for imposing brake hydraulic pressure. he mass production started with the ABS second generation, in 1978 [7]. With the hardware technology breakthroughs, now the challenge is to propose eicient control algorithms for the actuators. Several algorithms had been aimed for controlling the ABS; see [8, 9] for interesting overviews. In this paper, a mechatronic system, the ABS Laboratory setup, manufactured by Inteco Ltd., is used to implement new control strategies and to compare them, avoiding the high costs of tests on real full-sized vehicles. he setup represents a quarter car model and consists of two rolling wheels. he lower wheel, made of aluminum, imitates the relative road motion of the car, whereas the upper wheel, made of rigid plastic, is mounted to the balance lever and simulates the wheel of the vehicle. In order to accelerate the lower wheel, a large DC motor is coupled to it. he upper wheel is equipped with a disk–brake system, driven by a small DC motor [10]. Earlier works on this kind of setup are mainly based on Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2015, Article ID 896859, 10 pages http://dx.doi.org/10.1155/2015/896859