Coordination networks under noisy measurements and sensor biases

Large scale network systems have been constructed and utilized to provide services ranging from energy acquisition and water distribution to health monitoring and transportation. The operation of these complex systems relies on sensors and actuators to acquire and control the system states, which are commonly exchanged among the sub-parts of the systems via communication channels, due to the spatial separation of the systems. Considering the pervasiveness of these man-made complex systems and the importance of the data extraction and exchange, attention should be paid in understanding how large scale systems behave when there are uncertainties in the measurements and communications.Aside from transmission delays and information missing, noise is also a major issue in data exchange. In addition, when sensors are used to measure variables, the problem that arises commonly is that the read-out may not be exactly equal to real value. In both cases, the data error prevents the systems to get accurate state information. As the current emergence of Internet of Thing, Industry 4.0, smart city and 5G, sensors and communication mediums are playing more and more important roles in network systems. Considering these facts, this thesis focuses on analysing and addressing the issues in networksystems caused by the error in state measurement and exchange.We first consider two algorithms to deal with the data exchange error, with a particular interest in designing robust network coordination algorithms againstunknown but bounded communication noise. In chapter 3, we propose a self-triggered consensus algorithm to tackle the state drift problem of consensus dynamics caused by the communication noise. In chapter 4, we refine the resultby proposing a different algorithm. Although these two algorithms both can achieve practical consensus and guarantee boundedness of system state, the mechanisms of them are different. The first algorithm relies on an adaptive threshold, which is adjusted based on the node state, to zero the control inputs of the nodes when their disagreements are sufficiently small. The second algorithm imposes the bound on the state of each node by saturating the state received from the node neighbours.Lastly, we consider the state measurement error, and focus on estimating the sensor bias from the incorrect measurement. The sensors in the network measure the relative states of their neighbours, and the measurements may contain biases. We discuss the conditions of the measurement graphs and the number of biased sensors that allow the biases to be reconstructed from the measurements. Furthermore, we provide distributed algorithms to compute the value of the biases

Bias estimation in sensor networks

This paper investigates the problem of estimating biases affecting relative state measurements in a sensor network. Each sensor measures the relative states of its neighbors and this measurement is corrupted by a constant bias. We analyse under what conditions on the network topology and the maximum number of biased sensors the biases can be correctly estimated. We show that for non-bipartite graphs the biases can always be determined even when all the sensors are corrupted, while for bipartite graphs more than half of the sensors should be unbiased to ensure the correctness of the bias estimation. If the biases are heterogeneous, then the number of unbiased sensors can be reduced to two. Based on these conditions, we propose some algorithms to estimate the biases.Comment: 12 pages, 8 figure

Self-Triggered Network Coordination over Noisy Communication Channels

This paper investigates coordination problems over packet-based communication channels. We consider the scenario in which the communication between network nodes is corrupted by unknown-but-bounded noise. We introduce a novel coordination scheme, which ensures practical consensus in the noiseless case, while preserving bounds on the nodes disagreement in the noisy case. The proposed scheme does not require any global information about the network parameters and/or the operating environment (the noise characteristics). Moreover, network nodes can sample at independent rates and in an aperiodic manner. The analysis is substantiated by extensive numerical simulations.Comment: 15 pages, 15 figure

On the benefits of saturating information in consensus networks with noise

In a consensus network subject to non-zero mean noise, the system state may be driven away even when the disagreement exhibits a bounded response. This is unfavourable in applications since the nodes may not work properly and even be faulty outside their operating region. In this paper, we propose a new control algorithm to mitigate this issue by assigning each node a favourite interval that characterizes the nodes desired convergence region. The algorithm is implemented in a self-triggered fashion. If the nodes do not share a global clock, the network operates in a fully asynchronous mode. By this algorithm, we show that the state evolution is confined around the favourite interval and the node disagreement is bounded by a simple linear function of the noise magnitude, without requiring any priori information on the noise. We also show that if the nodes share some global information, then the algorithm can be adjusted to make the nodes evolve into the favourite interval, improve on the disagreement bound and achieve asymptotic consensus in the noiseless case

Self-Triggered Network Coordination Over Noisy Communication Channels

This paper deals with the coordination problems over noisy communication channels. We consider a scenario where the communication between network nodes is corrupted by unknown-but-bounded noise. We introduce a novel coordination scheme which ensures: 1) boundedness of the state trajectories and 2) a linear map from the noise to the nodes disagreement value. The proposed scheme does not require any global information on the network parameters and/or the operating environment (the noise characteristics). Moreover, network nodes can sample at independent rates and in an aperiodic manner

Controllable Synthesis of Zn 2

Zn2GeO4 nanorods were successfully synthesized by a simple hydrothermal method. The composition, morphology, and optical properties of as-synthesized Zn2GeO4 samples were characterized by X-ray diffraction, scan electron microscopy, and UV-vis diffuse reflectance spectra. The photocatalytic properties of Zn2GeO4 nanorods were evaluated by the reduction of Cr(VI) and oxidation of organic pollutants in aqueous solution. The effects of solution pH on Cr(VI) reduction by Zn2GeO4 nanorods were studied in detail. The results indicated that the efficiency of Cr(VI) reduction was highest at pH 5.96. Moreover, Zn2GeO4 nanorods also showed excellent photocatalytic ability for the oxidation of organic pollutants such as rhodamine B and 4-nitrophenol

Attenuation of the influenza virus by microRNA response element in vivo and protective efficacy against 2009 pandemic H1N1 virus in mice

SummaryBackgroundThe 2009 influenza pandemics underscored the need for effective vaccines to block the spread of influenza virus infection. Most live attenuated vaccines utilize cold-adapted, temperature-sensitive virus. An alternative to live attenuated virus is presented here, based on microRNA-induced gene silencing.MethodsIn this study, miR-let-7b target sequences were inserted into the H1N1 genome to engineer a recombinant virus – miRT-H1N1. Female BALB/c mice were vaccinated intranasally with the miRT-H1N1 and challenged with a lethal dose of homologous virus.ResultsThis miRT-H1N1 virus was attenuated in mice, while it exhibited wild-type characteristics in chicken embryos. Mice vaccinated intranasally with the miRT-H1N1 responded with robust immunity that protected the vaccinated mice from a lethal challenge with the wild-type 2009 pandemic H1N1 virus.ConclusionsThese results indicate that the influenza virus containing microRNA response elements (MREs) is attenuated in vivo and can be used to design a live attenuated vaccine

Retinex-guided Channel-grouping based Patch Swap for Arbitrary Style Transfer

The basic principle of the patch-matching based style transfer is to substitute the patches of the content image feature maps by the closest patches from the style image feature maps. Since the finite features harvested from one single aesthetic style image are inadequate to represent the rich textures of the content natural image, existing techniques treat the full-channel style feature patches as simple signal tensors and create new style feature patches via signal-level fusion, which ignore the implicit diversities existed in style features and thus fail for generating better stylised results. In this paper, we propose a Retinex theory guided, channel-grouping based patch swap technique to solve the above challenges. Channel-grouping strategy groups the style feature maps into surface and texture channels, which prevents the winner-takes-all problem. Retinex theory based decomposition controls a more stable channel code rate generation. In addition, we provide complementary fusion and multi-scale generation strategy to prevent unexpected black area and over-stylised results respectively. Experimental results demonstrate that the proposed method outperforms the existing techniques in providing more style-consistent textures while keeping the content fidelity

Stabilizing and maneuvering angle rigid multi-agent formations with double-integrator agent dynamics

This paper studies formation stabilization and maneuvering of mobile agents governed by double-integrator dynamics. The desired formation is described by a set of triple-agent angles. A carefully chosen such set of angle constraints guarantees that the desired formation is angle rigid. To achieve the desired angle rigid formation, a stabilization control law is proposed using only local velocity and direction measurements. We show that the closed-loop dynamics of the formation, when each agent is modeled by a double-integrator, are closely related to the corresponding one in single-integrator agent dynamics. Sufficient conditions are constructed to guarantee the closed-loop stability for identical and distinct velocity damping gains, respectively. To guide an angle rigid formation to move with the desired translational velocity, orientation and scale, formation maneuvering laws are then proposed. Simulation examples are also provided to validate the results