DocumentCode :
1031254
Title :
Fuzzy and adaptive control simulations for a walking machine
Author :
DeYong, Mark ; Polson, John ; Moore, Roy ; Weng, Che-Chi ; Lara, Jaime
Author_Institution :
Dept. of Electr. & Comput. Eng., New Mexico State Univ., Las Cruces, NM, USA
Volume :
12
Issue :
3
fYear :
1992
fDate :
6/1/1992 12:00:00 AM
Firstpage :
43
Lastpage :
50
Abstract :
The application of fuzzy logic and adaptive control algorithms to an eight-legged multivariable walking-machine system is described. A rule-based fuzzy control algorithm that eliminates the need for an explicit mathematical model of the system dynamics is examined. A model reference adaptive control (MRAC) is then considered. The performance of both the fuzzy logic control and adaptive control are compared on the basis of trajectory tracking ability as well as algorithm time and space complexity. Simulation shows the overall position trajectory tracking performance of both the fuzzy and adaptive controllers is exceptionally accurate.<>
Keywords :
adaptive control; computational complexity; dynamics; fuzzy logic; knowledge based systems; mobile robots; model reference adaptive control systems; multivariable control systems; position control; MRAC; adaptive control; eight-legged multivariable walking-machine; fuzzy logic; mobile robots; rule-based fuzzy control; simulations; space complexity; time complexity; trajectory tracking; Adaptive control; Automotive engineering; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Hydraulic actuators; Leg; Legged locomotion; Trajectory;
fLanguage :
English
Journal_Title :
Control Systems, IEEE
Publisher :
ieee
ISSN :
1066-033X
Type :
jour
DOI :
10.1109/37.165515
Filename :
165515
Link To Document :
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