Paper
22 December 1993 Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance
Thomas Hessburg, Michael Lee, Hideyuki Takagi, Masayoshi Tomizuka
Author Affiliations +
Proceedings Volume 2061, Applications of Fuzzy Logic Technology; (1993) https://doi.org/10.1117/12.165047
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States
Abstract
A method of tuning a fuzzy logic controller (FLC) by a genetic algorithm (GA) is proposed for lane following maneuvers in an automated highway system. The GA simultaneously determines the shape of membership functions, number of rules, and consequent parameters of the FLC. The GA approach operates on binary representations of FLCs and uses an expression for a fitness score to be maximized, which takes into account the tracking error, yaw rate error, lateral acceleration error, rate of lateral acceleration, front wheel steering angle, and rate of front wheel steering angle, to find an optimal controller. Apriori knowledge about both the physical application and FLCs is incorporated into the design method to increase the performance of the design method and the resulting controller. The controllers designed by this method are compared in simulation to a conventional PID controller, a frequency shaped linear quadratic controller, and previously designed FLCs tuned manually.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Hessburg, Michael Lee, Hideyuki Takagi, and Masayoshi Tomizuka "Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance", Proc. SPIE 2061, Applications of Fuzzy Logic Technology, (22 December 1993); https://doi.org/10.1117/12.165047
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Cited by 18 scholarly publications and 1 patent.
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KEYWORDS
Fuzzy logic

Device simulation

Genetic algorithms

Binary data

Magnetism

Control systems

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