GENETIC-FUZZY CONTROLLER DESIGN FOR PNEUMATIC MOTORS

Zusatztext

Trajectory tracking fuzzy logic controller (TTFLC) is proposed for the speed control of a pneumatic motor (PM). A third order trajectory is defined to determine the trajectory function that has to be tracked by the PM speed. Genetic algorithm (GA) is used to find the TTFLC boundary values of membership functions (MF) and weights of control rules. In addition, artificial neural networks (ANN) modelled dynamic behaviour of PM is given. This ANN model is used to find the optimal TTFLC parameters by offline GA approach. The experimental results showthat designed TTFLC successfully enables thePMspeed track the given trajectory under variousworking conditions.

Autorenportrait

A.Fevzi BABA received the BS,MSc, PhD degrees in electrical and electronics education from Marmara University. He is currently professor and head of Department of Control System.His research interests include intelligent control, fuzzy logic and engineering technology education.

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