Self-Healing Control Framework Against Actuator Fault of Single-Rotor Unmanned Helicopters

Unmanned helicopters (UHs) develop quickly because of their ability to hover and low speed flight. Facing different work conditions, UHs require the ability to safely operate under both external environment constraints, such as obstacles, and their own dynamic limits, especially after faults occurrence. To guarantee the postfault UH system safety and maximum ability, a self‐healing control (SHC) framework is presented in this chapter which is composed of fault detection and diagnosis (FDD), fault‐tolerant control (FTC), trajectory (re‐)planning, and evaluation strategy. More specifically, actuator faults and saturation constraints are considered at the same time. Because of the existence of actuator constraints, usable actuator efficiency would be reduced after actuator fault occurrence. Thus, the performance of the postfault UH system should be evaluated to judge whether the original trajectory and reference is reachable, and the SHC would plan a new trajectory to guarantee the safety of the postfault system under environment constraints. At last, the effectiveness of proposed SHC framework is illustrated by numerical simulations

Non-Uniform Sampling Reconstruction for Symmetrical NMR Spectroscopy by Exploiting Inherent Symmetry

Symmetrical NMR spectroscopy constitutes a vital branch of multidimensional NMR spectroscopy, providing a powerful tool for the structural elucidation of biological macromolecules. Non-Uniform Sampling (NUS) serves as an effective strategy for averting the prohibitive acquisition time of multidimensional NMR spectroscopy by only sampling a few points according to NUS sampling schedules and reconstructing missing points via algorithms. However, current sampling schedules are unable to maintain the accurate recovery of cross peaks that are weak but important. In this work, we propose a novel sampling schedule termed as SCPG (Symmetrical Copy Poisson Gap) and employ CS (Compressed Sensing) methods for reconstruction. We theoretically prove that the symmetrical constraint, apart from sparsity, is implicitly implemented when SCPG is combined with CS methods. The simulated and experimental data substantiate the advantage of SCPG over state-of-the-art 2D Woven PG in the NUS reconstruction of symmetrical NMR spectroscopy.Comment: 30 pages, 6 figure

The Expression of irx7 in the Inner Nuclear Layer of Zebrafish Retina Is Essential for a Proper Retinal Development and Lamination.

Irx7, a member in the zebrafish iroquois transcription factor (TF) family, has been shown to control brain patterning. During retinal development, irx7\u27s expression was found to appear exclusively in the inner nuclear layer (INL) as soon as the prospective INL cells withdraw from the cell cycle and during retinal lamination. In Irx7-deficient retinas, the formation of a proper retinal lamination was disrupted and the differentiation of INL cell types, including amacrine, horizontal, bipolar and Muller cells, was compromised. Despite irx7\u27s exclusive expression in the INL, photoreceptors differentiation was also compromised in Irx7-deficient retinas. Compared with other retinal cell types, ganglion cells differentiated relatively well in these retinas, except for their dendritic projections into the inner plexiform layer (IPL). In fact, the neuronal projections of amacrine and bipolar cells into the IPL were also diminished. These indicate that the retinal lamination issue in the Irx7-deficient retinas is likely caused by the attenuation of the neurite outgrowth. Since the expression of known TFs that can specify specific retinal cell type was also altered in Irx7-deficient retinas, thus the irx7 gene network is possibly a novel regulatory circuit for retinal development and lamination

Simulation-Based Analyses and Improvements of the Smart Line Management System in Canned Beverage Industry:A Case Study in Europe

Canned water is one of the thriving markets in the food and beverage industry. Given the tight competition in this market, realistic analysis in such production lines has become even more attractive for all participating parties. In this paper, we apply a KPI-driven simulation-based approach to a smart production plant of a key player in the European beverage market. The project covers realistic discrete-event modeling and analysis of the system together with the suggested scenario-based optimization for performance improvement. Here, the smart line management system is modeled and re-coded while considering machine characteristics, failures, and their overall influence on the production process. Our proposed optimized scenario demonstrates noticeably better results in all performance indicators when compared to the existing state of the system. The total increment of the production speed reaches up to 45 percent, resource utilization is evenly optimal, and the overall work-in-progress inventory is reduced significantly

High-Resolution Probing of Heterogeneous Samples by Spatially Selective Pure Shift NMR Spectroscopy.

Liquid NMR spectroscopy generally encounters two major challenges for high-resolution measurements of heterogeneous samples, namely, magnetic field inhomogeneity caused by spatial variations in magnetic susceptibility and spectral congestion induced by crowded NMR resonances. In this study, we demonstrate a spatially selective pure shift NMR approach for high-resolution probing of heterogeneous samples by suppressing effects of field inhomogeneity and J coupling simultaneously. A Fourier phase encoding strategy is proposed and implemented for spatially selective pure shift experiments to enhance signal intensity and further boost the applicability. The spatially selective pure shift method can serve as an effective tool for high-resolution probing of heterogeneous samples, thus presenting interesting prospects for extensive applications in the fields of chemistry, physics, biology, and food science

Over-the-Air Split Machine Learning in Wireless MIMO Networks

In split machine learning (ML), different partitions of a neural network (NN) are executed by different computing nodes, requiring a large amount of communication cost. To ease communication burden, over-the-air computation (OAC) can efficiently implement all or part of the computation at the same time of communication. Based on the proposed system, the system implementation over wireless network is introduced and we provide the problem formulation. In particular, we show that the inter-layer connection in a NN of any size can be mathematically decomposed into a set of linear precoding and combining transformations over MIMO channels. Therefore, the precoding matrix at the transmitter and the combining matrix at the receiver of each MIMO link, as well as the channel matrix itself, can jointly serve as a fully connected layer of the NN. The generalization of the proposed scheme to the conventional NNs is also introduced. Finally, we extend the proposed scheme to the widely used convolutional neural networks and demonstrate its effectiveness under both the static and quasi-static memory channel conditions with comprehensive simulations. In such a split ML system, the precoding and combining matrices are regarded as trainable parameters, while MIMO channel matrix is regarded as unknown (implicit) parameters.Comment: 15 pages, 13 figures, journal pape

High-Resolution Reconstruction for Diffusion-Ordered NMR Spectroscopy.

Diffusion-ordered NMR spectroscopy (DOSY) presents an essential tool for the analysis of compound mixtures by revealing intrinsic diffusion behaviors of mixed components. The applicability of DOSY measurements on complex mixtures is generally limited by the performance of data reconstruction algorithms. Here, based on constraints on low rank and sparsity of DOSY data, we propose a reconstruction method to achieve high-resolution DOSY spectra with excellent peak alignments and accurate diffusion coefficients for measurements of complex mixtures even when component signals are congested and mixed together along the spectral dimension. This proposed method is robust and suitable for DOSY data acquired from common commercial NMR instruments; thus, it may broaden the scope of DOSY applications