Distributed Nonlinear Model Predictive Formation Control of Quadcopter Type UAVs in Cluttered and Dynamic Environments

Date

2023-5-10

Author

Satır, Muhlis Sami

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Unmanned aerial vehicles (UAVs) have gained widespread use in various applications, including surveillance, inspection, and delivery. One important aspect in the operation of UAVs is the ability to fly in formation, where a group of UAVs maintains a desired geometric configuration while performing a given task. In this thesis, we use model predictive control (MPC) to address the problem of formation control for a group of UAVs. We first review the literature on formation control for UAVs, highlighting the advantages and limitations of different control approaches. We then describe the MPC formulation for formation control of multi-UAV systems, taking into account the dynamics and constraints of the UAVs. We also discuss the challenges and trade-offs in the design of the MPC controller, including the choice of the prediction horizon and the control input constraints. We present a novel approach that combines MPC formation control with graph generation algorithms to allow for the formation of UAVs to start from arbitrary points providing greater flexibility and adaptability to different scenarios. Finally, we demonstrate the proposed formation control method on a swarm of mini UAV both in simulation and on physical platforms.

Subject Keywords

Model Predictive Control, Swarm, Formation Control, Unmanned Aerial Vehicles

URI

https://hdl.handle.net/11511/103474

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Graduate School of Natural and Applied Sciences, Thesis