Multi-Scale Design and Control of Complex Advanced UAV Systems

In this dissertation, we explore the design and control of complex advance systems at various scales with a focus on UAVs in urban environment. In Chapter 2, we introduce a standard for defining routing restrictions based on potential field and propose an air traffic management infrastructure that takes advantage of it. The infrastructure would facilitate the deployment of a collaborative platform, enabling independent parties involved in aerial travel to operate within the same airspace. Chapter 3 introduces a path planning framework tailored for restrictive routing within potential fields. At its core, it decomposes a potential field into multi-scale cells with an estimated risk for restriction violation and utilizes graph-based path planning algorithms to generate routes that are demonstratively safe. Chapter 4 formalizes a new class of neural controllers and an accompanying architecture that use Pontryagin's maximum/minimum principle to generate future state prediction of a system, and the corresponding optimal control needed to drive it to variable online reference state. The proposed model allows for adjustment of the transient characteristics of the system and control. The work sets the stage for the development of advanced flight algorithms for UAVs.