NEURO-FUZZY PROCESS CONTROL SYSTEM FOR SINKING EDM

Electrical-Discharge machining (EDM) stands for highly accurate and very sophisticated metal shaping. The physical process takes advantage of electric field effects between two electrodes, a tool and a workpiece. Material is removed by sequences of electrical discharges. The electrically efficient gap width, which is determined among other parameters by the electric conductivity of the gap and the geometrical distance of the electrodes varies from spark to spark. This leads to a highly non-linear control problem. Various optimization control algorithms have been developed to im-prove the performance of EDM sinking machines. Soft computing technologies like Fuzzy logic and Neural Networks gained much popularity in this field. The following article introduces a process control system consisting of a Fuzzy gap-width controller adapted by a Neural Network. By combining a Neural Network with a Fuzzy controller in this way a learning process control system is achieved. Experimental results show the working efficiency of this Neuro-Fuzzy system