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Intelligent Adaptive Fuzzy Logic Genetic Algorithm Controller for Anti-Lock Braking System

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Braking system plays a major safety feature in any vehicle; it is considered as one of the key points in safe motoring. The main objective of a good braking system is to provide safe stopping, in addition to the fact that it provides repeatable stopping. Anti-lock Braking System (ABS) is one of the recently developed safety feature used in a vehicle in order to prevent wheels from locking.  This article proposes an intelligent adaptive fuzzy logic (FL) genetic algorithm (GA) controller for the Anti-Lock Braking System (ABS) to control the braking of a vehicle by controlling the slip ratio based on quarter car model. The main objective of the proposed controller is to prevent wheels from locking, which is a major safety issue in any braking system for different road conditions. The proposed controller consists of a Fuzzy Logic (FL) Genetic Algorithm (GA) based controller. The Genetic Algorithm is utilized in tuning the membership functions of the Fuzzy logic controller, which is developed to calculate the amount of reduction of the applied torque due to applying brake based on the error of the measured slip ratio signal compared with the desired one. Then a Genetic Algorithm (GA) is utilized in tuning the Fuzzy Logic parameters, which are the center of the Gaussian membership function, and the spread (б). The simulation results of the proposed fuzzy logic genetic algorithm controller are compared with both the results of the Fuzzy logic controller and the PD controller developed in previous work of the authors. The simulation results present many advantages of using Fuzzy Logic Genetic Algorithm based controller over both the Fuzzy Logic and the PD controllers, and the simulation is carried out at different road conditions, namely dry, wet and icy road surface.
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Anti-lock Braking System (ABS); Fuzzy Logic (FL) Controller; Genetic Algorithm (GA); PD Controller; Quarter Car Model

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C. Farmer, A. Lund, R. Trempel, E. Braver, Fatal crashes of Passenger vehicles before and after adding antilock braking systems, Accident Analysis and Prevention 29(6), 745-757, 1997.

C. Farmer, New evidence concerning Fatal crashes of Passenger vehicles before and after adding antilock braking systems, Accident Analysis and Prevention 33(3), 361-369, 2001.

A. Harifi, A. Aghagolzadeh, G. Alizadeh, and M. Sadeghi, Designing a sliding mode controller for slip control of antilock brake systems, Transportation Research Part C 16, 731-741, 2008.

L. Evans, P. Gerrish, Antilock brakes and risk of a front and rear impact in two-vehicle crashes, Accident Analysis and Prevention 28(3), 315-323, 1996.

Y. Toyofuku, K. Matsushima, Y. Irie, H. Yonezawa, K. Mizuno, Study on the effects of motorcycle anti-lock-braking-system for skilled and less-skilled riders: regarding braking in a turn, JSAE Review, 15(3), 223-228, 1994.

A. Zanten, R. Erhardt, A. Lutz, Measurement and Simulation of Transients in Longitudinal and Lateral Tire Forces, SAE Technical Paper 900210, 1990.

R. Bhandari, S. Patil, R. Singh, Surface prediction and control algorithms for anti-lock brake system, Transportation Research Part C, 21, 181-195, 2012.

M. Akbarzadeh, K. Emami, N. Pariz, Adaptive discrete-time fuzzy sliding mode control for anti-lock braking systems, In: Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), 554-559, 2002.

N. Merwe, P. Schalk Els, V. Zuraulis, ABS braking on rough terrain, Journal of Terramechanics, 80, Pp. 49-57, 2018.

E. Dincmen, T. Acarman, B. Aksun Guvenc, ABS Control Algorithm via Extremum Seeking Method with Enhanced Lateral Stability 6th IFAC Symposium Advances in Automotive Control, Munich, Germany, July 12-14, 2010.

M. Mokarram, A. Khoei, K. Hadidi, A fuzzy anti-lock braking system (ABS) controller using CMOS circuits, Microprocessors and Microsystems, 70, Pp. 47-52, 2019.

AL-Mola, M., Mailah, M., Samin, P., Muhaimin, A., Hybrid Control Scheme for Pursuing Performance of an Anti-Lock Brake System, (2013) International Review on Modelling and Simulations (IREMOS), 6 (6), pp. 1961-1967.

Ourabah, L., El Kari, B., Labriji, E., Fuzzy Graph-Based Controller for a Real-Time Urban Traffic Optimization, (2020) International Review on Modelling and Simulations (IREMOS), 13 (5), pp. 354-361.

Massaq, Z., Chbirik, G., Abounada, A., Brahmi, A., Ramzi, M., Control of Photovoltaic Water Pumping System Employing Non-Linear Predictive Control and Fuzzy Logic Control, (2020) International Review on Modelling and Simulations (IREMOS), 13 (6), pp. 373-382.

Essam Harby, M., Elzoghby, H., Elmasry, S., Elsamahy, A., Microgrid Frequency Stability Enhancement Through Controlling Electric Vehicles Batteries Based on Fuzzy Logic Controller, (2020) International Review of Automatic Control (IREACO), 13 (5), pp. 214-223.

Ruvalcaba, F., Llama, M., Jurado, F., Adaptive Type-2 Fuzzy Logic Control Applied to the Inverted Pendulum on a Cart Problem, (2018) International Review of Automatic Control (IREACO), 11 (4), pp. 188-197.

Salem, M., Abd Aziz, A., Al-Selwi, H., Bin Alias, M., Geok, T., Mahmud, A., Bin-Ghooth, A., Machine Learning-Based Node Selection for Cooperative Non-Orthogonal Multi-Access System Under Physical Layer Security, (2020) International Journal on Communications Antenna and Propagation (IRECAP), 10 (5), pp. 311-324.

El-Naggar, M., Application of Fuzzy Logic Technology to Evaluate the Performance of Double-Pontoon-Type BreakwaterApplication of Fuzzy Logic Technology to Evaluate the Performance of Double-Pontoon-Type Breakwater, (2018) International Journal of Earthquake Engineering and Hazard Mitigation (IREHM), 6 (1), pp. 21-29.

Omar, H., Zaky, E., Ibrahim, G., Elsawy, A., An Algorithm Based Levenberg Marquardt Method with Genetic Algorithm for Solving Continuation Problems, (2020) New Trends in Nonlinear Analysis and Applications, 1 (2), pp. 85-99.

Jaber, A., Mohammed, K., Shalash, N., Optimization of Electrical Power Systems Using Hybrid PSO-GA Computational Algorithm: a Review, (2020) International Review of Electrical Engineering (IREE), 15 (6), pp. 502-511.

Loubar, H., Boushaki, R., Aouati, A., Bouanzoul, M., Sliding Mode Controller for Linear and Nonlinear Trajectory Tracking of a Quadrotor, (2020) International Review of Automatic Control (IREACO), 13 (3), pp. 128-138.

W. Batayneh, M. Jaradat, A. Bataineh, Intelligent Adaptive Control for Anti-Lock Braking System, Proceedings of the ASME 2018 International Mechanical Engineering Congress & Exposition IMECE2018 November 9-15, 2018, Pittsburgh, PA, USA IMECE2018-87659

F. Assadin, Mixed HN and Fuzzy Logic controllers for the automobile ABS, PSA Peugeot-Citroen, SAE 2001 World congress, March 5–8, Detroit, Michigan, USA, 2001.

C. Nouillant, F. Assadian, X. Moreau, A. Oustaloup, Feedforward and CRONE feedback control strategies for automobile abs, Vehicle System Dynamics, 38(4):293–315, 2002.

M. Alata, W. Masarweh, S. Kamal, A Fuzzy Monitoring System for an Extrusion Line, Jordan Journal of Mechanical and Industrial Engineering, Vol. 1, No. 1, 17-21, 2007.

M. Balaji, V. Velmurugan, M. Prapa, V. Mythily, A Fuzzy Approach for Modeling and Design of Agile Supply Chains using Interpretive Structural Modeling, Jordan Journal of Mechanical and Industrial Engineering, Vol. 10. No. 1, 67-74., 2016.

M. A. Jaradat, and M. Al-Nimr, Fuzzy Logic Controller for Indoor Air Quality Control in Natural Ventilation Environments, Journal of Electric Engineering 60(1), 2009.

Basjaruddin, N., Margana, D., Kuspriyanto, K., Rinaldi, R., Suhendar, S., Hardware Simulation of Advanced Driver Assistance Systems Based on Fuzzy Logic, (2018) International Review on Modelling and Simulations (IREMOS), 11 (1), pp. 24-31.

O. Al-Araidah, M. Jaradat, W. Batayneh, Using a Fuzzy Poka-Yoke Based Controller to Restrain Emissions in Naturally Ventilated Environments, Expert Systems with Applications 37, 4787-4795, 2010.

J. Barzdžiukas, V. Stasys, S. Augutis, P. Rimvydas, R. Žilinskas, The Precise Measurement Of Car Velocity, Transport, Vol. 27 No. 2, 2012.


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