Launch vehicles traditionally rely on gain-scheduled PID controllers, which are time-consuming to develop, and require extensive modelling. Incremental Nonlinear Dynamic Inversion (INDI) may serve as an alternative to reduce model dependency, and streamline launch vehicle control system design and tuning. This work applies a cascaded INDI controller, with an inner attitude loop and an outer position loop, to the model of a small-scale launch vehicle testbed. Such testbeds are used in the context of Guidance, Navigation & Control (GNC) to develop and test algorithms on a physical system in a cost-effective and low-risk fashion. Wind disturbance, propellant sloshing, and tail-wags-dog, i.e. the effect of the engine’s motion on the rest of the vehicle, are considered in the model. The results show that INDI provides a simple way to develop a nonlinear control law that maintains robust position reference tracking in the presence of disturbance and model uncertainty. Finally, it is determined that a small-scale testbed is not suitable for studying the impact of sloshing on the closed loop control systems of launch vehicles, since at this scale the sloshing mass is too small and the natural frequency of the sloshing dynamics is too high.

Drones have been an emerging trend in the last few years. They are used in multiple industries already, from photography and videography to racing. More use cases are now being conceived, such as using drones to deliver packages and food to people at home, using drones for inspections, or even using them as rescue searching vehicles in hostile environments. Even more possibilities open up once the drones bundle their forces to create swarms. The lifting capabilities of drones are still somewhat limited, but in a swarm they might be able to lift heavy payloads. This report covers the design of a concept of a payload carrying swarm, intended to lift cargo up to 500 kg to even the top of a tall building.