TY - JOUR
T1 - Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance
AU - Hessburg, Thomas
AU - Lee, Michael
AU - Takagi, Hideyuki
AU - Tomizuka, Masayoshi
N1 - Funding Information:
This research is conducted under the Partners for Advanced Transit and Highways (PATH) of UC Berkeley. This research was conducted under the sponsorship of the State of California Business, Transportation, and Housing Agency, Department of Transportation, and the U.S. Department of Transportation, Federal Highway Administration.
Publisher Copyright:
© 1993 SPIE. All rights reserved.
PY - 1993/12/22
Y1 - 1993/12/22
N2 - 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.
AB - 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.
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U2 - 10.1117/12.165047
DO - 10.1117/12.165047
M3 - Conference article
AN - SCOPUS:84894206741
VL - 2061
SP - 452
EP - 463
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
SN - 0277-786X
T2 - Applications of Fuzzy Logic Technology 1993
Y2 - 7 September 1993 through 10 September 1993
ER -