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Following paper presents a research aiming to increase the efficiency of an Unmanned Aerial System (UAS) fleet during mission execution. The developed system allows to reduce the mission time by considering the fleet diversity. System is based on a multilevel optimization, applying an innovative trajectory generation method. The Mixed Integer Linear Programming (MILP) algorithm was adopted, so the trajectories for individual platform were optimal (shortest). The developed solution considers not only the area but also the UASs performance and sensors capabilities. The mission operator with the dedicated GUI could control and designate the platforms for various tasks. The method was tested on various platforms with different performance. The method proved its efficiency reducing the mission time up to 15%. Finally, the system was successfully tested in real environment with the use of three various platforms.

This article examines the use of comprehensive dynamic model in helicopter optimal control after power failure. In this study, an eight-degree-of-freedom model of a single main rotor helicopter was developed and implemented. It is shown that the simulation model and the optimal control method proved to be efficient in simulation of low-speed flights covering power failure conditions and autorotation.