Design and implementation of an advanced guidance and control algorithm for autonomous quadcopter drone

This master’s thesis delves into the development and implementation of a precise dynamic model, a fine-tuned flight controller and several optimized guidance algorithms tailored explicitly for quadcopter drones, with a specific focus on their application in intercepting targets (specifically high-performance drones), indicative of potential military purposes. Drawing inspiration from established algorithms designed for missile interception, the study explores the adaptation and optimization of these algorithms to suit the unique dynamics of quadcopter systems. The primary guidance algorithms under consideration include Proportional Navigation (PN), Augmented Proportional Navigation (APN), Optimal Guidance Law (OGL), and PID Guidance. In the contemporary landscape dominated by unmanned aerial vehicles, quadcopter drones have emerged as integral contributors across diverse sectors, including surveillance and delivery services. In the context of this thesis, Simulink has been employed, a versatile modeling tool, to design and implement robust control systems for quadcopter drones, specifically tailored for intercepting targets. Acknowledging the sensitive nature of the application, the study considers the intricacies of modeling both the quadcopter drone and the target. The objective extends beyond mere emulation of quadcopter dynamics, aiming to contribute substantively to the broader applications of aerial technology in military contexts.