Design of Fuzzy Logic Controller for DC Motor

This contribution presents a simple and efficient approach to the fuzzy logic controller design and simulation. The proposed controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design method is based on anfis (adaptive neuro-fuzzy inference system) training routine. It utilizes a combination of the least-squares method and the backpropagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controller is used for the position control of a linear actuator which is a part of a Stewart platform.

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