Optimal Ramp Schemes and Related Combinatorial Objects

In 1996, Jackson and Martin proved that a strong ideal ramp scheme is equivalent to an orthogonal array. However, there was no good characterization of ideal ramp schemes that are not strong. Here we show the equivalence of ideal ramp schemes to a new variant of orthogonal arrays that we term augmented orthogonal arrays. We give some constructions for these new kinds of arrays, and, as a consequence, we also provide parameter situations where ideal ramp schemes exist but strong ideal ramp schemes do not exist

Attitude dynamics simulation subroutines for systems of hinge-connected rigid bodies

Several computer subroutines are designed to provide the solution to minimum-dimension sets of discrete-coordinate equations of motion for systems consisting of an arbitrary number of hinge-connected rigid bodies assembled in a tree topology. In particular, these routines may be applied to: (1) the case of completely unrestricted hinge rotations, (2) the totally linearized case (all system rotations are small), and (3) the mixed, or partially linearized, case. The use of the programs in each case is demonstrated using a five-body spacecraft and attitude control system configuration. The ability of the subroutines to accommodate prescribed motions of system bodies is also demonstrated. Complete listings and user instructions are included for these routines (written in FORTRAN V) which are intended as multi- and general-purpose tools in the simulation of spacecraft and other complex electromechanical systems

Energy extraction from shallow tidal flows

Over the past decade within the renewable energy sector a strong research and development focus has resulted in the growth of an embryonic tidal stream energy industry. Previous assessments of the tidal stream resource appear to have neglected shallow tidal flows. This resource located in water depths of 10-30m is significant because it is generally more accessible for energy extraction than deeper offshore tidal sites and hence a good location for first generation tidal stream arrays or fences. The close proximity to shore may lead to improvements in construction feasibility and economic prospects. The objective of this project is to investigate several aspects concerning the exploitation of shallow tidal flows for energy extraction. Fundamental to this project is the importance of developing research alongside and in conjunction with industrial shallow water prototype projects. The key objectives are: (1) The development and understanding of the use of artificial flow constraint structures in the form of specifically-shaped foundations (herein described as “rampfoundations”) that constrain the flow leading to an increase in the magnitude and quality of power from marine current energy convertors (MCEC) operating in shallow tidal flows. (2) The investigation of seabed and free-surface proximity effects on the downstream wake structure of a MCEC. (3) Commercial shallow water device optimisation; utilising project results to aid with the design and development of full-scale commercial demonstrators.Through theoretical and scaled experimental modelling, and commercial collaboration the project has concluded ramp foundations could be utilised to locally increase tidal flow velocities and increase MCEC output across a tidal cycle in shallow flows. Predicted power benefits are in the region of 5-22% depending on lateral and vertical ramp channel blockage ratios. The ramp width or overall array width must therefore be tuned to the channel width to maximise power benefits. Rampfoundations will thus only be technically viable in relatively narrow channels or ideally in MCEC arrays or tidal fences. Results have shown that the downstream wake length is dependent on and varies with the vertical flow constraint and it is critical that the downstream array spacing of MCECs are tuned to the local flow depth. An optimum device height to flow depth ratio to minimise wake length has been identified. It is hoped that this ramp-foundation concept and the relationship between boundary proximity and wake length will continue to help with the development of a niche shallow tidal energy marke

CONTROL STRATEGY OF MULTIROTOR PLATFORM UNDER NOMINAL AND FAULT CONDITIONS USING A DUAL-LOOP CONTROL SCHEME USED FOR EARTH-BASED SPACECRAFT CONTROL TESTING

Over the last decade, autonomous Unmanned Aerial Vehicles (UAVs) have seen increased usage in industrial, defense, research, and academic applications. Specific attention is given to multirotor platforms due to their high maneuverability, utility, and accessibility. As such, multirotors are often utilized in a variety of operating conditions such as populated areas, hazardous environments, inclement weather, etc. In this study, the effectiveness of multirotor platforms, specifically quadrotors, to behave as Earth-based satellite test platforms is discussed. Additionally, due to concerns over system operations under such circumstances, it becomes critical that multirotors are capable of operation despite experiencing undesired conditions and collisions which make the platform susceptible to on-board hardware faults. Without countermeasures to account for such faults, specifically actuator faults, a multirotors will experience catastrophic failure. In this thesis, a control strategy for a quadrotor under nominal and fault conditions is proposed. The process of defining the quadrotor dynamic model is discussed in detail. A dual-loop SMC/PID control scheme is proposed to control the attitude and position states of the nominal system. Actuator faults on-board the quadrotor are interpreted as motor performance losses, specifically loss in rotor speeds. To control a faulty system, an additive control scheme is implemented in conjunction with the nominal scheme. The quadrotor platform is developed via analysis of the various subcomponents. In addition, various physical parameters of the quadrotor are determined experimentally. Simulated and experimental testing showed promising results, and provide encouragement for further refinement in the future

An Integrity Framework for Image-Based Navigation Systems

This work first examines fundamental differences between measurement models established for GPS and those of proposed image-based navigation systems. In contrast to single value per satellite GPS pseudorange measurements, image measurements are inherently angle-based and represent pixel coordinate pairs for each mapped target. Thus, in the image-based case, special consideration must be given to the units of the transformations between the states and measurements, and also to the fact that multiple rows of the observation matrix relate to particular error states. An algorithm is developed to instantiate a framework for image-based integrity analogous to that of GPS RAIM. The algorithm is applied cases where the navigation system is estimating position only and then extended to cases where both position and attitude estimation is required. Detailed analysis demonstrates the impact of angular error on a single pixel pair measurement and comparisons from both estimation scenario results show that, from an integrity perspective, there is significant benefit in having known attitude information. Additional work demonstrates the impact of pixel pair measurement relative geometries on system integrity, showing potential improvement in image-based integrity through screening and adding measurements, when available, to the navigation system solution

Software-Defined Infrastructure for IoT-based Energy Systems

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT devices need programmability and need to provide software controls in order to manage them efficiently. Further, it will need data-driven modeling techniques to process and analyze a vast amount of data from heterogeneous devices to derive actionable insights. My thesis explores the problems posed by software-defined IoT energy infrastructure. I present four techniques that use systems and machine learning principles to design, analyze and deploy the next generation of smart IoT energy systems. First, I discuss how current state-of-the-art LIDAR-based approaches in identifying ideal locations on rooftops for deploying energy systems such as solar do not scale to many regions of the world. To address the challenges, I propose DeepRoof, a data-driven approach that uses deep learning to estimate the solar potential of roofs using satellite imagery and identify ideal locations for installation. We evaluate our approach on different types of roof and show that our technique is comparable to LIDAR-based methods. Second, I study how excessive solar can cause problems in the grid and examine how programmatic control of the solar output can prevent congestion in the electric grid. Further, I present a decentralized approach that can control the solar arrays in a grid-friendly manner. Also, my approach provides flexible control of solar output, and I show that such mechanisms allow for higher solar penetration in the grid. Third, I discuss the challenges in community-owned (and shared) distributed energy resources that do not provide independent control to users. To do so, I propose vSolar, an approach to virtualize the solar arrays and energy storage that allows independent control. Further, I show how using vSolar users can exercise independent control, implement their custom energy sharing policies, and reduce energy costs through energy trading. Finally, I present the challenges, and the high throughput needs to enable a peer-to-peer energy trading platform using permissioned blockchains. I propose FabricPlus, an enhanced Hyperledger Fabric blockchain, that contains a series of optimizations to enable high throughput transactions. FabricPlus increases the transaction throughput many folds, without requiring any changes to its external interfaces. I also show considerable performance improvement over the baseline Fabric

An overview of lidar imaging systems for autonomous vehicles

Lidar imaging systems are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a race dedicated to deciding the final solution to be implemented. However, the diversity of state-of-the-art approaches to the solution brings a large uncertainty on the decision of the dominant final solution. Furthermore, the performance data of each approach often arise from different manufacturers and developers, which usually have some interest in the dispute. Within this paper, we intend to overcome the situation by providing an introductory, neutral overview of the technology linked to lidar imaging systems for autonomous vehicles, and its current state of development. We start with the main single-point measurement principles utilized, which then are combined with different imaging strategies, also described in the paper. An overview of the features of the light sources and photodetectors specific to lidar imaging systems most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development in autonomous vehicles has been included, in order to present some of the problems which still need to be solved before implementation may be considered as final. The reader is provided with a detailed bibliography containing both relevant books and state-of-the-art papers for further progress in the subject.Peer ReviewedPostprint (published version