Multi-UAVs formation autopilot design and performance analysis under interconnection topologies

This paper employs a unique extension-decomposition-aggregation (EDA) scheme to solve the formation flight control problem for multiple unmanned aerial vehicles (UAVs). The corresponding decentralised longitudinal and lateral formation autopilots are novelly designed to maintain the overall formation stability when encountering changes of the formation error and topologies. The concept of propagation layer number (PLN) is also proposed to provide an intuitive criterion to judge which type of formation topology is more suitable to minimise formation error propagation (FEP). The criterion states that the smaller the PLN of the formation is, the quicker the response to the formation error is. A smaller PLN also means that the resulting topology provides better prevention to the FEP. Simulation studies of formation flight of multiple Aerosonde UAVs demonstrate that the designed formation controller based on the EDA strategy performs satisfactorily in maintaining the overall formation stable, and the bidirectional partial-mesh topology is found to provide the best overall response to the formation error propagation based on the PLN criterion.

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Motivated by the need for designing efficient and robust fully-distributed computation in highly dynamic networks such as Peer-to-Peer (P2P) networks, we study distributed protocols for constructing and maintaining dynamic network topologies with good expansion properties. Our goal is to maintain a sparse (bounded degree) expander topology despite heavy {\em churn} (i.e., nodes joining and leaving the network continuously over time). We assume that the churn is controlled by an adversary that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is a randomized distributed protocol that guarantees with high probability the maintenance of a {\em constant} degree graph with {\em high expansion} even under {\em continuous high adversarial} churn. Our protocol can tolerate a churn rate of up to $O(n/\poly\log(n))$ per round (where $n$ is the stable network size). Our protocol is efficient, lightweight, and scalable, and it incurs only $O(\poly\log(n))$ overhead for topology maintenance: only polylogarithmic (in $n$) bits needs to be processed and sent by each node per round and any node's computation cost per round is also polylogarithmic. The given protocol is a fundamental ingredient that is needed for the design of efficient fully-distributed algorithms for solving fundamental distributed computing problems such as agreement, leader election, search, and storage in highly dynamic P2P networks and enables fast and scalable algorithms for these problems that can tolerate a large amount of churn.

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

DEX: self-healing expanders

Split Converter-Fed SRM Drive for Flexible Charging in EV/HEV Applications

Electric vehicles (EVs) and hybrid EVs are the way forward for green transportation and for establishing low-carbon economy. This paper presents a split converter-fed four-phase switched reluctance motor (SRM) drive to realize flexible integrated charging functions (dc and ac sources). The machine is featured with a central-tapped winding node, eight stator slots, and six rotor poles (8/6). In the driving mode, the developed topology has the same characteristics as the traditional asymmetric bridge topology but better fault tolerance. The proposed system supports battery energy balance and on-board dc and ac charging. When connecting with an ac power grid, the proposed topology has a merit of the multilevel converter; the charging current control can be achieved by the improved hysteresis control. The energy flow between the two batteries is balanced by the hysteresis control based on their state-of-charge conditions. Simulation results in MATLAB/Simulink and experiments on a 150-W prototype SRM validate the effectiveness of the proposed technologies, which may provide a solution to EV charging issues associated with significant infrastructure requirements.

Element-Free Galerkin Modelling of Crack Migration in Composite Laminates

The development of a virtual testing environment, as a cost-effective industrial design tool in the design and analysis of composite structures, requires the need to create models efficiently, as well as accelerate the analysis by reducing the number of degrees of freedom, while still satisfying the need for accurately tracking the evolution of a debond, delamination or crack front. The eventual aim is to simulate both damage initiation and propagation in components with realistic geometrical features, where crack propagation paths are not trivial. Meshless approaches, and the Element-Free Galerkin (EFG) method, are particularly suitable for problems involving changes in topology and have been successfully applied to simulate damage in homogeneous materials and concrete. In this work, the method is utilized to model initiation and mixed-mode propagation of cracks in composite laminates, and to simulate experimentally-observed crack migration which is difficult to model using standard finite element analysis. N

A Fast Analysis Method for the Groove Gap Waveguide Using Transmission Line Theory

The Groove Gap Waveguide (GGW) shows a behavior similar to the classical rectangular waveguide (RWG), but it is formed by two pieces which do not require metal contact. This feature suggests the GGW as a suitable alternative to the RGW for mm-wave frequencies, where ensuring the proper metal contact according to the wavelength size results challenging. Nevertheless, there is a lack of effective analysis tools for the complex GGW topology, and assuming a direct equivalence between the RGW and the GGW is too rough, so that dilatory full-wave simulations are required. This work presents a fast analysis method based on transmission line theory, which establishes the proper correspondence between the GGW and the RWG. In addition, below cutoff behavior of the GGW is studied for the first time. Several numerical tests and two manufactured prototypes validate the proposed method, which seems very adequate to optimize future GGW structures.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost.