| The Electrical Discharge Machining (EDM) technology plays an important role in the machining manufacturing. Under many circumstances (such as high rigidity, high tenacity, high brittleness material), it is the only effective method which can achieve the machining that general methods cost a lot or can not accomplish. With the development of machining manufacturing, the EDM technology is required to improve. The progress of the Fuzzy Neural Network (FNN) and its unique control characters give the EDM chances to develop.This paper proposes an improved pulse generator based on the analysis of advantages and disadvantages of the existed ones. The pulse generator not only eliminates the rising slope and machining current tail, but also uses only one set of DC power supply. Based on the platform of Simulink, the pulse generator from Haerbin Institute of technology and this newly proposed one are analyzed and compared to validate the newly designed pulse generator's performance.As for the EDM can not be mathematically modeled and after studying the influences of online parameters to the craft index, this paper designs a real-time adjusting intelligent controller based on the fuzzy RBF Neural-Network theory. The controller takes the rate of correct spark, error spark(including short and electric arc), idle spark and correct spark with regard to the period of raising machining tool and pulse as inputs, and outputs the change of tool-raising period, pulse period and reference voltage so as to level off the EDM process. Using decoupling, the MIMO controller is decoupled into 3 MISO controllers.In order to validate the intelligent controller, this paper takes the gap reference voltage controller for example. The gap reference voltage FNN controller is designed in detail. Using the Simulink, the controller is simulated firstly and accomplished its hardware and software design. The controller is established on the double MPU, and the conmmunation between the 2 MPU is achieved by IDT7007.
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