Abstract:Electronic press position servo system with the properties of nonlinear and timevarying uncertainty requires good controllability of press mounting force, press speed and pressed depth, good system stability, adaptability and antiinterference ability. According to these, a method was proposed of selftuning fuzzy proportion integration differential (PID) control characteristics, realized by neural network, was applied to a mini electronic press position servo system. The control strategy was combined of the reasoning ability of fuzzy control and the learning ability of neural network effectively. Through learning and memorizing the basic rules of PID parameter adjustment, the selftuning of PID controller parameters could be realized so as to meet the requirements of the position servo system of the press, and simulation analysis was carried out by using MATLAB software programming. The simulation results show that this fuzzy neural network PID controller as compared with that composed of conventional neural network combined with traditional PID, have better stability and faster response characteristics for the position servo system of electronic press.