학술논문

Coevolutionary Optimization of a Fuzzy Logic Controller for Antilock Braking Systems Under Changing Road Conditions
Document Type
Periodical
Source
IEEE Transactions on Vehicular Technology IEEE Trans. Veh. Technol. Vehicular Technology, IEEE Transactions on. 70(2):1255-1268 Feb, 2021
Subject
Transportation
Aerospace
Roads
Tires
Optimization
Brakes
Mathematical model
Delays
Vehicle dynamics
Coevolutionary
genetic algorithms
fuzzy logic controller (FLC)
antilock brake system (ABS)
vehicle safety
Language
ISSN
0018-9545
1939-9359
Abstract
An anti-lock brake system based on fuzzy logic has been developed and optimized to cope with changes in adherence road conditions. Conventional control systems have to be tuned by conducting simulations and tests on different surfaces before putting them into use. This way, large amounts of computational and testing times are required. The main objective of this work is to propose a methodology to simplify the process of obtaining a controller for antilock brake systems through a combination of optimization and simulation. To this end, an evolutionary algorithm based on the coevolution of two species has been used to tune the proposed fuzzy logic controller. The controller evolves competitively with the environment to optimize its response to different adherence conditions. Finally, the optimized controller has been implemented in a real motorcycle to compare its performance with a conventional system.