Hybrid Control Scheme for Pursuing Performance of an Anti-Lock Brake System

(*) Corresponding author

Authors' affiliations

DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)


In this paper, a hybrid system acted as a component of the standard proportional-integral-derivative (PID) controller along with an intelligent active force control (AFC) and tried to strengthen it by using the third method for tracking control for systems that work in a repetitive mode.  Iterative learning (IL) control was the technique adapted to improve the dynamic system. This technique was developed and implemented in a hybrid scheme as a way to obtain the effective tracking required for slip ratio and stable interaction force between the tire and the road using an anti-lock brake system. The performance of the hybrid control scheme is compared with a PID controller and PID-AFC in terms of the ability to adapt for best slip ratio. It is found that the proposed control strategy copes well with the complexities of the high nonlinearity of the system and has done better than the other two controllers.
Copyright © 2013 Praise Worthy Prize - All rights reserved.


Anti-Lock Braking System; Active Force Control; PID Controller; Iterative Learning Control; Wheel Slip

Full Text:



M. R. Akbarzadeh, K.J. Emami, N. Pariz, Adaptive discrete-time fuzzy sliding mode control for anti-lock braking systems, Proc.Annu.Meeting NAFIPS, pp. 554-559, 2002.

J. R. Hewit, J. S. Burdess, Fast dynamic decoupled control for robotics using active force control, Mechanism and Machine Theory, vol. 16, no. 5, 1981, pp. 535 - 542.

G. Priyandoko, M. Mailah, “Controller design for an active suspension of a quarter car model using fuzzy logic active force control”, Proc. of the 2nd Intl. Conf. on Mechatronics. May 2005, Kuala Lumpur, pp. 693-700.

Z. Omar, Modelling and simulation of an active suspension system using active force control strategy, Universiti Teknologi Malaysia, 2002, Master Thesis.

K. Hudha, H. Jamaluddin, M. P. Samin, and R. A. Rahman, Active roll control suspension system (ARCS) using active force control strategy on a new modified half car model, Society of Automotive Engineers, Warrendale PA, 2003.

Mailah, M., Priyandoko, G., Mechatronic implementation of an intelligent active force, (2010) International Review of Mechanical Engineering (IREME), 4 (7), pp. 899-907.

G. Priyandoko, M. Mailah and H. Jamaluddin, Vehicles active suspension system using skyhook adaptive neuro active force control, Mechanical Systems and Signal Processing, 23(3) (2009) 855-868.

W. Lutfi, Modelling and control of intelligent antilock brake system, Universiti Teknologi Malaysia, Desember. 2005, Malaysia: Master Thesis.

M. H. A. Al-Mola, Robust intelligent active force controller for a Wagner brake model, Universiti Teknologi Malaysia, Faculty of Mechanical Engineering, 2009, Master thesis.

R. Varatharajoo, C. T. Wooi, M. Mailah, Two degree-of-freedom spacecraft attitude controller, Advances in Space Research, vol. 47, no. 4, 2011, pp. 685-689.

M. H. Al-Mola, M. Mailah, S. Kazi, A. H. Muhaimin, and M. Y. Abdullah, Robust active force controller for an automotive brake system, 3rd Intl. Conf. on Intelligent Systems Modelling and Simulation (ISMS 2012), 2012, pp. 467-472.

M. H. Al-Mola, M. Mailah, A. H. Muhaimin, and M. Y. Abdullah, Intelligent active force controller for an anti-lock brake system application, 1st Intl. Conf. on Systems, Control, Power, Robotics in Singapore (SCOPORO 2012), 2012.

M. Al-Mola, M. Mailah, A.H. Muhaimin, M.Y. Abdullah, P.M. Samin, Fuzzy-based PID with iterative learning active force controller for an anti-lock brake system, International Journal of Simulation: Systems, Science and Technology, 13 (3 A), pp. 35-41, 2012.

S. Arimoto, T. Naniwa, and H. Suzuki, Robustness of P-type learning control with a forgetting factor for robotic motions, Proc. of the IEEE 29th Conf. on Decision and Control, Honolulu, Hawaii, U.S.A., 1990, pp. 2640-2645.

K. Hamamoto and T. Sugie, Iterative learning control for robot manipulators using the finite dimensional input subspace, IEEE Trans. Robot. Automat., 2002, 18(4). 632-635.

M. Norrlöf, An adaptive iterative learning control algorithm with experiments on an industrial robot, IEEE Trans. Robot. Automat. 2002, 18: 245–251.

A. R. Tavakolpour, M. Mailah, and I. Z. Mat Darus, Self-learning active vibration control of a flexible plate structure with piezoelectric actuator, Simulation, Modelling Practice and Theory, 2010, vol. 18, no. 5, pp. 516-532.

M. Mailah and J. Chong, Control of a robot arm using iterative learning control with a stopping criterion, Jurnal Teknologi, 2002, vol. 37, pp. 55-72.

S. Chunting Mi, L. Hui, and Y. Zhang, Iterative learning control of antilock braking of electric and hybrid vehicles, IEEE Trans. on Vehicular Technology, 2005, vol. 54, no. 2.

Y. Oniz, E. Kayacan, O. Kaynak, A dynamic method to forecast the wheel slip for antilock braking system and its experimental evaluation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39(2), 551-560, 2009.

F. Tianku, Modeling and performance analysis of ABS systems with nonlinear control, Montreal, Canada, Concordia University, 2000: Master Thesis.

R. Rajamani, Vehicle Dynamics and Control. New York, NY, USA: Springer-Verlag, 2006.

“User’s manual” The Laboratory Antilock Braking System Controlled from PC, Inteco Ltd., Crakow, Poland, 2006.

M. Mailah, Intelligent Active Force Control of a Rigid Robot Arm Using Neural Network and Iterative Learning Algorithms. Doctor Philosophy, University of Dundee, UK, 1998.

S., Arimoto, S. Kawamura, F. Miyazaki, Applications of Learning Method for Dynamic Control of Robot Manipulators. Proc. of 24th Conf. on Decision and Control. Ft. Lauderdale. 1381-1386, 1985.


  • There are currently no refbacks.

Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2023 Praise Worthy Prize