The focus of this dissertation is on developing novel methods and extending existing ones to improve the security and reliability of fixed-wing unmanned aircraft systems (UAS). Specifically, we focus on three strands of work: i) designing UAS controllers with performance guarantees using the robust control framework, ii) developing tools for detection and mitigation of physical-layer security threats in UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS.

Under the first category, we use the robust H-infinity control approach to design a linear parameter-varying (LPV) path-following controller for a fixed-wing UAS that enables the aircraft to follow any arbitrary planar curvature-bounded path under significant environmental disturbances. Three other typical path-following controllers, namely, a linear time-invariant H-infinity controller, a nonlinear rate-tracking controller, and a PID controller, are also designed. We study the relative merits and limitations of each approach and demonstrate through extensive simulations and flight tests that the LPV controller has the most consistent position tracking performance for a wide array of geometric paths. Next, convex synthesis conditions are developed for control of distributed systems with uncertain initial conditions, whereby independent norm constraints are placed on the disturbance input and the uncertain initial state. Using this approach, we design a distributed controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories.

Pertaining to the second strand of this dissertation, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, a probabilistic framework that employs tools from statistical analysis to detect sensor attacks on UAS is proposed. By incorporating knowledge about the physical system and using a Bayesian network, the proposed approach minimizes the false alarm rates, which is a major challenge for UAS that operate in dynamic and uncertain environments. Next, the security vulnerabilities of existing UAS actuators are identified and three different methods of differing complexity and effectiveness are proposed to detect and mitigate the security threats. While two of these methods involve developing algorithms and do not require any hardware modification, the third method entails hardware modifications to the actuators to make them resilient to malicious attacks. The three methods are compared in terms of different attributes such as computational demand and detection latency.

As for the third strand of this dissertation, tools from formal methods such as compositional verification are used to design an unmanned multi-aircraft system that is deployed in a geofencing application, where the design objective is to guarantee a critical global system property. Verifying such a property for the multi-aircraft system using monolithic (system-level) verification techniques is a challenging task due to the complexity of the components and the interactions among them. To overcome these challenges, we design the components of the multi-aircraft system to have a modular architecture, thereby enabling the use of component-based reasoning to simplify the task of verifying the global system property. For component properties that can be formally verified, we employ results from Euclidean geometry and formal methods to prove those properties. For properties that are difficult to be formally verified, we rely on Monte Carlo simulations. We demonstrate how compositional reasoning is effective in reducing the use of simulations/tests needed in the verification process, thereby increasing the reliability of the unmanned multi-aircraft system.