In the past few years, fuzzy-rule-based modeling has become an active research field because of its good merits in solving complex nonlinear system identification and control problems. A Servo System (SS) is a class of a nonlinear position system that needs to be positioned accurately on a commanded position. The strategy followed in this study in designing digital controller for such system is as follows: Building a neuro-model that represents the open loop servo system. This is accomplished by sufficiently collecting input-output data and used it off-line to build the neural network that will represent the plant for the second design stage. Design fuzzy controller through simulation to reach the required closed-loop behavior. The design technique is based on the adjustment of the scale factors, rule base and membership functions of the controller was accomplished by fine tuning and heuristic corrections linked to the knowledge of the process to be controlled. For the specified plant, there are certain parameters, which achieved a well-controlled response.