Control and optimization of the dynamic of a network of UAVs via collective behaviour.

Networks are ubiquitous in today's world. Communication networks are changing the way we live and interact. Social networks are redefning the ways we keep in touch. Transport networks give us access to the remotest parts of the world. The energy needed for our domestic and industrial use is supplied by electric power networks. Human survival depends on the functioning of a number of biological and ecological networks. So, Complexity and complex systems' theory are issues coming more and more into focus as it seems that most systems in our lives must be understood in this perspective. based on Stankovski, the collective dynamics of a network depends not only on the network structure but also on the functional form of the interactions. In certain physical systems one can observe that network connections may be state dependent in the sense that links can be temporarily disabled (named dead zones). The concept of dead zone in the interaction between two dynamical systems is a region of their joint phase space where one system is insensitive to the changes in the other. Therefore, the dead zone concept will be used to materialise the coupling in time and it leads the network to the achievement of intriguing behaviours such as synchronization, cluster formations, chimera states, traveling chimera, traveling waves, etc. The main objective of the work is to answer the question how to exploit these phenomena to solve a concrete problem in the 21st century? This work will focus on the use of physical phenomena obtained in networks for the control of drone swarms and their optimization. Knowing the vast feld of application of UAVs, the challenge will be to design a mobile network made up of swarms where the connection between entities will use the concept of dead zones and fnally use the behaviours obtained for the control of a set of drones. The use of dead zone is justifed by the fact that each drone operates under fluctuating wireless, networking and environment constraints.