Biblio

The work is devoted to the synthesis of an aircraft control system using a synergetic control theory. The paper contains a general description of the apparatus and its control system, a synthesis of control laws, and a computer simulation. The relevance of the work consists in the need to create a vertically take-off aircraft of the “flying platform” type in order to increase the efficiency of rescue operations in disaster zones where helicopters and other modern means can't cope with the task. The scientific novelty of the work consists in the application of synergetic approaches to the development of a hierarchical system for balancing the vehicle spatial position and to the coordinating energy-saving control of electric motors that receive energy from a turbine generator.

Millions of small Unmanned Aircraft System (sUAS) aircraft of various shapes and capabilities will soon fly at low altitudes in urban environments for ambitious applications. It is critical to ensure these remotely piloted aircraft fly safely, predictably, and efficiently in this challenging airspace, without endangering themselves and other occupants sharing that airspace or in proximity. Concepts, technologies, processes, and policies to solve this hard problem of UAS Traffic Management (UTM) are being explored. But, cyber security considerations are largely missing. This paper bridges this gap and addresses UTM cyber security needs and issues. It contributes a comprehensive framework to understand, identify, classify, and assess security threats to UTM, including those resulting from sUAS vulnerabilities. Promising threat mitigations, major challenges, and research directions are discussed to secure UTM.

We propose a methodology for architecture exploration for Cyber-Physical Systems (CPS) based on an iterative, optimization-based approach, where a discrete architecture selection engine is placed in a loop with a continuous sizing engine. The discrete optimization routine proposes a candidate architecture to the sizing engine. The sizing routine optimizes over the continuous parameters using simulation to evaluate the physical models and to monitor the requirements. To decrease the number of simulations, we show how balance equations and conservation laws can be leveraged to prune the discrete space, thus achieving significant reduction in the overall runtime. We demonstrate the effectiveness of our methodology on an industrial case study, namely an aircraft environmental control system, showing more than one order of magnitude reduction in optimization time.