Adaptive Fuzzy sliding mode controller for wheel slip control in Antilock Braking System

  • A . Manivanna Boopathi Associate professor, Department of Electrical & Electronics Engineering, PSN COllege of Engineering & Technology, Tirunelveli - 627152
  • A . Abudhahir Professor, Department of Electrical & Electronics Engineering, Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Avadi, Chennai
Keywords: Antilock Braking System, Adaptive control, Sliding Mode Control, Fuzzy Logic Control, Fuzzy Sliding Mode Control

Abstract

Safety features like Antilock Braking Systems (ABSs) have become an essential feature of road vehicles now a days. ABSs are designed for the purpose of maintaining the wheel slip in the required value during sudden braking to ensure the vehicle steerablility and non-skidding. Uncertain factors such as type of road surface, tyre pressure, vehicle mass, etc., cause the required wheel slip to be continuously changing. Hence, controlling the wheel slip remains a difficult task always. This situation leads to a need for design of a controller which will be capable of dealing with these uncertainties. One of the controllers which can effectively deal with the parametric and modeling uncertainties is Sliding Mode Controller (SMC). Fuzzy logic is a knowledge based system which is very much useful in handling the systems whose models are not developed fully or accurately or information about the system is uncertain. In this paper, a robust and adaptive Fuzzy Sliding Mode Controller (FSMC) is proposed for a laboratory ABS model by combining Fuzzy Logic with Sliding Mode Controller. The performance of the proposed FSMC is assessed through digital simulations for various initial conditions of vehicle velocity and road surface conditions.

References

Andon V.Topalov, Yesim Oniz, Erdal Kayacan & Okyay Kaynak, 2011. ‘Neuro-fuzzy control of antilock braking system using sliding mode incremental learning algorithm’, Journal of Neuro-computing, 11, 1883-1893.

Samuel John and Jimoh O. Pedro, 2013. ‘Hybrid Feedback Linearization Slip Control for Anti-lock Braking System’, Acta Polytechnica Hungarica, 10 (1), 81-99.

Houhua Jing, Zhiyuan Liu and Hong Chen, 2011. ‘A switched control strategy for Antilock Braking System with On/Off Valves’, IEEE Transactions on Vehicular Technology, 60 (4), 1470-1484.

Juan Diego Sánchez-Torres, Alexander G Loukianov, Javier Ruiz-León and Jorge Rivera, 2011. ‘ABS + Active Suspension Control via Sliding Mode and Linear Geometric Methods for Disturbance Attenuation’, Proc. 50th IEEE Conf. on Decision and Control and European Control Conference (CDC-ECC), Orlando, FL, USA, 8076-8081.

Amir Poursamad, 2009. ‘Adaptive feedback linearization control of antilock braking systems using neural networks’, Mechatronics, 19(5), 767-773.

Yesim Oniz, Erdal Kayacan and Okyay Kaynak, 2009. ‘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.

Yesim Oniz, 2007. ‘Simulated and experimental study of antilock braking system using Grey Sliding mode control’, M.S.Thesis, Boğaziҫi University, Turkey.

Radac, M.B., Precup, R.E., Preitl, S., Tar, J.K. and Petriu, E.M., 2008. ‘Linear and Fuzzy Control Solutions for a Laboratory Anti-lock Braking System’, 6th International Symposium on Intelligent Systems and Informatics.

Sohel Anwar and Bing Zheng, 2007. ‘An Antilock-Braking Algorithm for an Eddy-Current-Based Brake-By-Wire System’, IEEE Transactions on Vehicular Technology, 56(3), 1100-1107.

Harifi, A., Aghagolzadeh, A., Alizadeh, G., and Sadeghi, M., 2005. ‘Designing a sliding mode controller for antilock brake system’, in Proc. Int. Conf. Comput. Tool, Serbia and Montenegro, Europe, 611–616.

Lin, C.M. and Hsu, C.F., 2003. ‘Self-learning fuzzy sliding-mode control for antilock braking systems’, IEEE Trans. Control Syst. Technol., 11(2), 273–278.

Tor A Johansen, Idar Petersen, Jens Kalkkuhl and Jens Lüdemann, 2003. ‘Gain-Scheduled Wheel Slip Control in Automotive Brake Systems’ IEEE Trans. Control Syst. Technol, 11(6), 799-811.

Choi, S-B., Bang, J-H., Cho, M-S., and Lee, Y-S., 2002. ‘Sliding mode

control for anti-lock brake system of passenger vehicles featuring electrorheological valves’, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 897-908.

Unsal, C. and Kachroo, P., 1999. ‘Sliding mode measurement feedback control for antilock braking systems’, IEEE Trans. Control Syst. Technol., 7(2), 271–281.

Georg F. Mauer, 1995. ‘A Fuzzy Logic Controller for an ABS Braking System’, IEEE Transactions on Fuzzy Systems, 3(4), 381-388.

Kueon YS and Bedi JS, 1995. ‘Fuzzy-Neural-Sliding Mode Controller and its Applications to the Vehicle Anti-Lock Braking Systems’, Proc. of Int. conf. on Industrial Automation and Control, Taipei, 391-398.

Jeffery R. Layne, Kevin M. Passino and Stephen Yurkovich, 1993. ‘Fuzzy Learning Control for Antiskid Braking Systems’, IEEE Transactions on Control Systems Technology, 1(2), 122-129.

Manivanna Boopathi, A., and Abudhahir, A., 2015. ‘Firefly Algorithm tuned Fuzzy Set-point Weighted PID Controller for Antilock Braking Systems’, Journal of Engineering Research. (Accepted for publication)

David Young, K., Vadim I. Utkin, and Umit Ozguner, 1999. ‘A Control Engineer’s guide to sliding mode control’, IEEE Transactions on Control Systems Technology, 7(3), 328-342.

Passino, K., and Yurkovich,S., 1998. Fuzzy Control, Addison-Wesley.

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

Utkin,V.I., 1997. ‘Variable structure systems with sliding modes’, IEEE Transactions on Automatic Control, 22(2), 212-221.

Dragan Antić, Marko Milojković, Zoran Jovanović and Saša Nikolić, 2010. ‘Optimal Design of the Fuzzy Sliding Mode Control for a DC Servo Drive’, Journal of Mechanical Engineering, 455-463.

Published
2016-07-10
Section
Mechanical Engineering