Fuzzy Control for Anti-Lock Automobile Brake Systems
Abstract
Introduction: Anti-lock braking systems are used in modern cars to prevent the wheels from locking after brakes were applied. A vehicle model has a nonlinear form. The controller should provide a controlled torque necessary to maintain the optimum value of the wheel slip ratio. Purpose: The goal of this study is building genetically adjusted fuzzy PID controllers to improve the control performance of anti-lock braking systems compared to the conventional PID controllers. Results: An anti-lock braking system has been developed which uses a quarter vehicle model and a brake actuator. The vehicle model is derived and simulated in the longitudinal direction. Three types of controller are proposed for building of anti-lock braking systems: a bang-bang controller, a linear PID and a fuzzy PID-type controller (the two latter ones are genetically adjusted). The system performance is evaluated with MatLab by the stopping distance and longitudinal slip of the vehicle. The fuzzy logic controller has shown the best performance for the anti-lock braking system model, reducing the stopping distance up to 10% compared to the conventional PID and over 30% compared to the bang-bang controller. Practical relevance: The control algorithm proposed in this paper has great potentials for its implementaion in real-time anti-lock braking systems.Published
2016-04-21
How to Cite
Burakov, M., & Konovalov, A. (2016). Fuzzy Control for Anti-Lock Automobile Brake Systems. Information and Control Systems, (2), 35-41. https://doi.org/10.15217/issn1684-8853.2016.2.35
Issue
Section
Information and control systems