Performance of Anti-Lock Braking Systems Based on Adaptive and Intelligent Control Methodologies

Automobiles of today must constantly change their speeds in reaction to changing road and traffic circumstances as the pace and density of road traffic increases. In sophisticated automobiles, the Anti-lock Braking System (ABS) is a vehicle safety system that enhances the vehicle's stability and steering capabilities by varying the torque to maintain the slip ratio at a safe level. This paper analyzes the performance of classical control, model reference adaptive control (MRAC), and intelligent control for controlling the (ABS). The ABS controller's goal is to keep the wheel slip ratio, which includes nonlinearities, parametric uncertainties, and disturbances as close to an optimal slip value as possible. This will decrease the stopping distance and guarantee safe vehicle operation during braking. A Bang-bang controller, PID, PID based Model Reference Adaptive Control (PID-MRAD), Fuzzy Logic Control (FLC), and Adaptive Neuro-Fuzzy Inference System (ANFIS) controller are used to control the vehicle model. The car was tested on a dry asphalt and ice road with only straight-line braking. Based on slip ratio, vehicle speed, angular velocity, and stopping time, comparisons are performed between all control strategies. To analyze braking characteristics, the simulation changes the road surface condition, vehicle weight, and control methods. The simulation results revealed that our objectives were met. The simulation results clearly show that the ANFIS provides more flexibility and improves system-tracking precision in control action compared to the Bang-bang, PID, PID-MRAC, and FLC

Design and Implementation of a Traffic Control System Based on Congestion

Abstract: The traffic issues have garnered more and more attention on a global scale as the number of cars has grown. One of the biggest problems is the traffic congestion, also the fixed-time settings are still used by the majority of traffic systems today. These technologies are unable to dynamically alter the timing of traffic lights in response to heavy traffic. Thanks to technological advancements, sensors or cameras can now collect data on traffic volume and wait times. This study provided an illustration of a traffic light control system that can manage traffic according to the number of vehicles in each road. Additionally, it showed how the system was designed using the Proteus design suite software and how a prototype of the system was implemented using an Arduino Mega 2560 and an infrared sensor. Through the results obtained, the efficiency of the proposed system is clear by comparing it with the system that depends on the fixed time of traffic signals

Proceedings of First Conference for Engineering Sciences and Technology: Vol. 1

This volume contains contributed articles of Track 1, Track 2 & Track 3, presented in the conference CEST-2018, organized by Faculty of Engineering Garaboulli, and Faculty of Engineering, Al-khoms, Elmergib University (Libya) on 25-27 September 2018. Track 1: Communication and Information Technology Track 2: Electrical and Electronics Engineering Track 3: Oil and Chemical Engineering Other articles of Track 4, 5 & 6 have been published in volume 2 of the proceedings at this lin