Abstract: To enhance the safety in case of engine flameout failure, a new type of UAV takeoff decision based on neural network capacity model was proposed. Two capacity parameters of takeoff safety in case of engine flameout failure were defined, one is the maximum velocity for a safe takeoff and the other is the minimum velocity for a safe shut down. A calculation method based on iterative simulations for those parameters under multiple flight conditions was introduced. Double layer neural networks were used to model the relationship between flight conditions and the capacity parameters, to realize the compressive storage and high precision adopted of the parameters. A takeoff decision based on online capacity calculation values from neural network capacity model of the UAV was derived. Simulation results show the strong practicality and benefit for enhancing UAV safety robustness of the proposed take off decision strategy.

Key words: takeoff decision, UAV, engine flameout failure, safety robustness, neural network