Cyber–Physical Optimization for Unmanned Aircraft Systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140662/1/1.i010105.pd

Rethinking Sampled-Data Control for Unmanned Aircraft Systems

Unmanned aircraft systems are expected to provide both increasingly varied functionalities and outstanding application performances, utilizing the available resources. In this paper, we explore the recent advances and challenges at the intersection of real-time computing and control and show how rethinking sampling strategies can improve performance and resource utilization. We showcase a novel design framework, cyber-physical co-regulation, which can efficiently link together computational and physical characteristics of the system, increasing robust performance and avoiding pitfalls of event-triggered sampling strategies. A comparison experiment of different sampling and control strategies was conducted and analyzed. We demonstrate that co-regulation has resource savings similar to event-triggered sampling, but maintains the robustness of traditional fixed-periodic sampling forming a compelling alternative to traditional vehicle control design

Aerospace Cyber-Physical Systems Education

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106495/1/AIAA2013-4809.pd

Optimization and Control of Cyber-Physical Vehicle Systems

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined

Toward Co-Design of Autonomous Aerospace Cyber-Physical Systems.

Modern vehicles are equipped with a complex suite of computing (cyber) and electromechanical (physical) systems. Holistic design, modeling, and optimization of such Cyber-Physical Systems (CPS) requires new techniques capable of integrated analysis across the full CPS. This dissertations introduces two methods for balancing cyber and physical resources in a step toward holistic co-design of CPS. First, an ordinary differential equation model abstraction of controller sampling rate is developed and added to the equations of motion of a physical system to form a holistic discrete-time-varying linear system representing the CPS controller. Using feedback control, this cyber effector, sampling rate, is then co-regulated alongside physical effectors in response to physical system tracking error. This technique is applied to a spring-mass-damper, inverted pendulum, and finally to attitude control of a small satellite (CubeSat). Additionally, two new controllers for discrete-time-varying systems are introduced; a gain-scheduled discrete-time linear regulator (DLQR) in which DLQR gains are scheduled over time-varying sampling rates, and a forward-propagation Riccati-based (FPRB) controller. The FPRB CPS controller shows promise in balancing cyber and physical resources. Second, we propose a cost function of cyber and physical parameters to optimize an Unmanned Aircraft System (UAS) trajectory for a pipeline surveillance mission. Optimization parameters are UAV velocity and mission-critical surveillance task execution rate. Metrics for pipeline image information, energy, cyber utilization, and time comprise the cost function and Pareto fronts are analyzed to gain insight into cyber and physical tradeoffs for mission success. Finally, the cost function is optimized using numerical methods, and results from several cost weightings and Pareto front analyses are tabulated. We show that increased mission success can be achieved by considering both cyber and physical parameters together.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108823/1/justyn_1.pd

Diversity of Fe2+ entry and oxidation in ferritins

The essential metal iron presents two major problems for life: it is potentially highly toxic due to its redox activity, and its extremely low solubility in aqueous solution in the presence of O2 can make it hard to acquire and store safely. Ferritins are part of nature’s answer to these problems, as they store iron in a safe but accessible form in all types of cells. How they achieve this has been the subject of intense research for several decades. Here, we highlight recent progress in elucidating the routes by which Fe2+ ions access the catalytic ferroxidase centers, and the mechanisms by which Fe2+ is oxidized. Emerging from this is a picture of diversity, both in terms of Fe2+ entry pathways and the roles played by the structurally distinct diiron ferroxidase centers

Mission-Aware Cyber-Physical Optimization on a Tabletop Satellite

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106493/1/AIAA2013-4807.pd

Energy-Aware Multiflight Planning for an Unattended Seaplane: Flying Fish

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/143017/4/1.i010484.pd

Locating and eliminating feral swine from a large area of fragmented mixed forest and agriculture habitats in north-central USA

Illinois is one of the US states where elimination of feral swine (Sus scrofa) was determined practical, as only a few isolated populations were established. A particularly important step towards feral swine elimination from Illinois was to eliminate the population in Fulton County. We describe the approaches applied to systematically detect, locate, and eliminate feral swine in a successful county-wide elimination. Detecting and locating feral swine was facilitated by extensive outreach activities, aerial surveys to locate crop damage, and use of camera traps placed over bait in areas where reports, sign, or crop damage occurred. The population was eliminated after 376 feral swine were removed from 2009 to 2016 by trapping, sharpshooting over bait, and aerial shooting. Aerial surveys efficiently located feral swine activity over wide areas during times of the crop cycle when damage would occur and would be most distinguishable from other damage sources. Two applications of aerial shooting in 2014 were particularly efficient for rapidly eliminating most remaining feral swine after they had become difficult to locate and remove. Persistent efforts thereafter led to the successful elimination of feral swine in Fulton County by 2016.We believe this is the first documentation of a widespread feral swine elimination in mixed agriculture and forest habitats