Fuzzy and adaptive control simulations for a walking machine

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.<
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