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