This paper reviews the performance difference and similarity in modeling system dynamics and the efficiency of error elimination with fewer fluctuation and adaptability to set point variation between the traditional fixed parameter proportional-integral-derivative controller and the model reference neural net controller applied to aircraft pitch attitude control. The designs of both controllers are presented. System identification using neural net was implemented to capture the system dynamics. Finally, the performances of the controllers were tested using a slow and fast varying input signals within the given bandwidth.