Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance

Thomas Hessburg, Michael Lee, Hideyuki Takagi, Masayoshi Tomizuka

Research output: Contribution to journalConference articlepeer-review

7 Citations (Scopus)

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 (FSLQ), and previously designed FLCs tuned manually.

Original languageEnglish
Pages (from-to)452-463
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2061
DOIs
Publication statusPublished - Dec 22 1993
Externally publishedYes
EventApplications of Fuzzy Logic Technology 1993 - Boston, United States
Duration: Sep 7 1993Sep 10 1993

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance'. Together they form a unique fingerprint.

Cite this