Abstarct: Today, widespread use of air equipment in military operations is inevitable that among these sudden risks rises from weak performance of pilot and also the conditions prevailing at time and space such as low altitude and atmospheric conditions, cause undeniable injuries and damages in control of sensitive military aircraft. These challenges persuade researchers who are looking for a solution to solve this issue. For this purpose, necessity of using unmanned aircraft is seem important in critical operations and designing smart systems to control unmanned aircraft. Due to the importance this issue, in this thesis we have provided a method baxsed on artificial neural network MLP to control the height of unmanned aircraft and have compared it with a model baxsed on fuzzy logic. Then we have calculated root Mean Square of height control error for both methods. The results show that the method baxsed on artificial neural network MLP compared to methods baxsed on fuzzy logic has better accuracy and performance.