Control of cooperative and collaborative team tactics in autonomous Unmanned Aerial Vehicles using decentralized Model Predictive Control

In recent years, Unmanned Aerial Vehicles (UAVs) have attracted a great deal of attention in academic, civilian and military communities as potential solutions to a wide variety of problems. As applications of UAVs continue to grow in complexity, the trend is to apply teams of UAVs to perform a task, increasing the overall effectiveness and robustness. As this trend continues, intelligent and flexible control strategies will be required to allow teams of UAVs to collaborate and cooperate to perform challenging group tasks. Encirclement is a tactic that can be employed by a team of UAVs to neutralize a target by restricting its movement, requiring a high level of cooperation. The aim of the UAV team encircling the target is to move close to the target and maintain a formation around the target. In this thesis the problem of creating a dynamic encirclement around a target is considered, and a decentralized Model Predictive Control (MPC) strategy is formulated. It is shown through both theoretical results and validation in simulation that the proposed control policy is effective for the cases of a single UAV encircling a stationary target, a group of UAVs encircling a stationary target, and a group of UAVs encircling a moving target. The effects of various parameters of the control strategy are also explored, showing that the method allows for high performance in a variety of scenarios.;Keywords: Model Predictive Control, Unmanned Aerial Vehicles, Autonomous Vehicles.