Increasing trend towards higher level of autonomy in unmanned aerial systems
(UASs) requires less control by the human operator and increasing capability
to perform complex tasks by reacting to the environmental influences. Nevertheless, current UASs, are designed to function in static, and predictable
environments. Therefore, it is envisaged that the existing uncertainties and dynamic changes, caused when an unmanned aerial vehicle (UAV) is operating
in an unknown environment, would degrade its performance signicantly. The
uncertainties can be also incurred through interaction with other complex and
intelligent systems, such as humans. We present a compact literature survey of
UASs control and navigation as a basic knowledge to develop UASs from the
perspective of control engineer. Besides, we present several control strategies to
maintain a UAS, as well as multi-UASs under a network setting under various
scenarios. Several simulations are given to illustrate the performance of the controllers in MATLAB. Advances in computing power and algorithms currently
enable development of systems with high degree of autonomy. Nonetheless, there is a large gap between practical operation in a real-world and laboratory implementation, as safe deployment of UASs, requires validation of their behaviour under almost all envisaged scenarios. A reliable and autonomous operation of such a system requires design and development of a cognitive control system that acquires knowledge and understanding of the surrounding environment via perception, reasoning and learning. Cognitive control systems in UASs will enhance their safety and performance. Cognitive control can also be used in cooperative execution of complex tasks where multiple agents such as humans, machines or both interact. Such UASs will have a great potential to be used in extreme environments such as search and rescue in case of disaster, nuclear decommissioning operation, deep-sea exploration, mining, etc.