Abstract
This paper utilizes a system identification to model EDM using Arduino and fuzzy controller. System identification is a useful tool for identifying the model depending on the input and output data of the controller. However, derivation of modeling process from first principles is often difficult due to its complexity. The proposed method is used for identifying the mathematical model of EDM from the real time experimental data from gather data from the systemy feeding the DC motor sine sweep or white noise inputs. The model identification of EDM servo system was conducted by using MATLAB/Simulink program and after that the obtained transfer function for the system. The proposed controller has been applied by using FLC .The results showed that the controller can work well with a quick response, no overshoot output and high control precision.
Highlights
Electrical Discharge Machining (EDM) is a method used to eliminate the material electrically from conductive and semi conductive material through series of quickly repeated current discharges between a work piece and electrode in existence of a dielectric (Morimoto and Kunieda, 2009).The EDM process eradicates material through originating controlled sparks between an electrically conductive work piece and a shaped electrode
A research in (Puri and Bhattacharyya, 2003) designed an intelligent controller based on fuzzy RBF (Radial Basis Function) and neural network to achieve a real-time control of EDM online parameters
The simulation results illustrated that this intelligent controller can recognize the real-time adjustment of EDM online parameters, which meets the condition of developing machining effectiveness and enhancing processing stability
Summary
Electrical Discharge Machining (EDM) is a method used to eliminate the material electrically from conductive and semi conductive material through series of quickly repeated current discharges between a work piece and electrode in existence of a dielectric (Morimoto and Kunieda, 2009). The EDM process eradicates material through originating controlled sparks between an electrically conductive work piece and a shaped electrode. In the EDM process an electric spark is used to cut the workpiece, which takes the shape opposite to that of the cutting tool or electrode (Stampfl et al, 2000). A research in (Puri and Bhattacharyya, 2003) designed an intelligent controller based on fuzzy RBF (Radial Basis Function) and neural network to achieve a real-time control of EDM online parameters. The simulation results illustrated that this intelligent controller can recognize the real-time adjustment of EDM online parameters, which meets the condition of developing machining effectiveness and enhancing processing stability
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