Design and Implementation of Modern Control Algorithms for Unmanned Aerial Vehicles
Kamal El-Din Hafez, Ahmed
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Recently, Unmanned Aerial Vehicles (UAVs) have attracted a great deal of attention in academic, civilian and military communities as prospective solutions to a wide variety of applications. The use of cooperative UAVs has received growing interest in the last decade and this provides an opportunity for new operational paradigms. As applications of UAVs continue to grow in complexity, the trend of using multiple cooperative UAVs to perform these applications rises in order to increase the overall effectiveness and robustness. There is a need for generating suitable control techniques that allow for the real-time implementation of control algorithms for different missions and tactics executed by a group of cooperative UAVs. In this thesis, we investigate possible control patterns and associated algorithms for controlling a group of autonomous UAVs in real-time to perform various tactics. This research proposes new control approaches to solve the dynamic encirclement, tactic switching and formation problems for a group of cooperative UAVs in simulation and real-time. Firstly, a combination of Feedback Linearization (FL) and decentralized Linear Model Predictive Control (LMPC) is used to solve the dynamic encirclement problem. Secondly, a combination of decentralized LMPC and fuzzy logic control is used to solve the problem of tactic switching for a group of cooperative UAVs. Finally, a decentralized Learning Based Model Predictive Control (LBMPC) is used to solve the problem of formation for a group of cooperative UAVs in simulation. We show through simulations and validate through experiments that the proposed control policies succeed to control a group of cooperative UAVs to achieve the desired requirements and control objectives for different tactics. These proposed control policies provide reliable and effective control techniques for multiple cooperative UAV systems.