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Several factors affect existing electric power systems and negatively impact power quality (PQ): the high penetration of renewable and distributed sources that are based on power converters with or without energy storage, non-linear and unbalanced loads, and the deployment of electric vehicles. In addition, the power grid needs more improvement in the performances of real-time PQ monitoring, fault diagnosis, information technology, and advanced control and communication techniques. To overcome these challenges, it is imperative to re-evaluate power quality and requirements to build a smart, self-healing power grid. This will enable early detection of power system disturbances, maximize productivity, and minimize power system downtime. This paper provides an overview of the state-of-the-art signal processing- (SP) and pattern recognition-based power quality disturbances (PQDs) characterization techniques for monitoring purposes.

To achieve precise control of the symmetrical unmanned surface vehicle (USV) under strong external disturbances, we propose a disturbance estimation and conditional disturbance compensation control (CDCC) scheme. First, the differential flatness method is applied to convert the underactuated model into a fully actuated one, simplifying the controller design. Then, a nonlinear disturbance observer (NDOB) is designed to estimate the lumped disturbance. Subsequently, a continuous disturbance characterization index (CDCI) is proposed, which not only indicates whether the disturbance is beneficial to the system stability but also makes the controller switch smoothly and suppresses the chattering phenomenon greatly. Indicated by the CDCI, the proposed CDCC method can not only utilize the beneficial disturbance but also compensate for the detrimental disturbance, which improves the USV’s control performance under strong external disturbances. Moreover, a trajectory-planning method is designed to generate an obstacle avoidance reference trajectory for the controller. Finally, simulations verify the feasibility of applying the proposed control method to USV.

This work studies the trajectory tracking control for unmanned aerial helicopter (UAH) system under both matched disturbance and mismatched ones. Initially, to tackle the strong coupling, an input–output feedback linearization method is utilized to simplify the nonlinear UAH system. Secondly, a set of finite-time disturbance observers (FTDOs) are proposed to estimate mismatched disturbances with their successive derivatives, which are utilized to design the feedforward controller via backstepping. Thirdly, as for matched disturbance, by defining the disturbance characterization index (DCI) to determine whether the disturbance is harmful or not for the UAH system, a feedback controller is proposed and a sufficient condition is established to ensure the convergence of the tracking error. Finally, some numerical simulations and comparisons illustrate the validity and advantages of our control scheme.

This chapter contains sections titled: Network Topology Features of PLC Transmission Channel Electromagnetic Compatibility of PLC Systems Disturbance Characterization Summary

Background To evaluate the stability of jointed rock masses subjected to dynamic disturbance, laboratory dynamic shear test on rock joint is necessary. Developing dynamic shear test equipment for rock joint is currently a pressing issue. Objective To address this issue, a new apparatus is developed to reproduce the shear-slip process of rock joint subjected to dynamic disturbance under various initial stress state. Methods The disturbance load, which has a dominant frequency close to that of seismic waves, is generated by an electromagnetic-driven disturbance generator, and its amplitude and duration can be accurately controlled in a stable manner. The initial normal and shear stresses can be applied in the shear test under dynamic disturbance using servo-controlled loading unit, which facilitates the simulation of the real stress state of rock joint. Results The shear tests under dynamic disturbance show that when an initial shear stress is applied to rock joint, an additional deformation stage of stress recovering can also trigger a slip displacement, which contributes to the destabilization of jointed rock masses. With increasing initial shear stress, the dynamic slip displacement, stress drop and post-disturbing deformation increase. The feasibility of the apparatus to conduct quasi-static direct shear tests with both the constant normal loading (CNL) and constant normal stiffness (CNS) boundaries is also verified. Conclusions Test results demonstrate that using the new apparatus, shear-slip properties of rock joint subjected to dynamic disturbance can be tested in various initial stress states.

We describe and discuss the preprocessing and calibration steps applied to the magnetic data measured by the three “platform magnetometers” on-board the CryoSat-2 satellite. The calibration is performed by comparing the magnetometer sensor readings with magnetic field values for the time and position of the satellite as given by the CHAOS-6 geomagnetic field model. We allow for slow temporal variations of the calibration parameters by solving for scale values, offsets, and non-orthogonalities in monthly bins, and account for non-linearities as well as the magnetic disturbances caused by battery, solar panel and magnetorquer currents. Fully calibrated magnetic vector data, together with time and position, are provided as daily files in CDF data format at swarm-diss.eo.esa.int. The data show good agreement with Swarm satellite magnetic measurements during close encounters (rms difference between 1 and 5 nT for inter-satellite distances below 300 km).

The performance of the solid oxide fuel cell (SOFC) is greatly influenced by its operating temperature. Therefore, making a profound study of the thermal characteristics inside the SOFC stack and maintaining the operating temperature within a reasonable range are the difficulties. This paper proposes a novel modeling and control strategy. Firstly, for studying the thermal characteristics of SOFC under variable load current and designing a more effective control schedule, the problem of SOFC temperature dynamic modeling is resolved by the beetle antennae search (BAS) optimizing–based back propagation (BP) neural network model (BAS-BP) innovatively. The simulation indicated that the mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE) of the designed BAS-BP algorithm are 19.14%, 24.51%, and 27.67% lower than those of the traditional BP model. The designed modeling method is armed with higher accuracy and faster convergence speed. Then, a sliding mode controller (SMC) based on the disturbance observer is represented in this paper, wherein the disturbance observer is first presented to predict disturbance functions, while the SMC realizes the tracking control of the SOFC node temperature by compensating for the observation error instead of ignoring it. It can be seen from the simulation that the proposed control strategy compared to the conventional proportional-integral-derivative (PID) controller achieves a 62.57%, 61.11%, and 6.27% reduction in MAE, MAPE, and MSE. The simulated results demonstrate that the presented strategy has better robustness to disturbances in addition to its validity in compensating for observation error, for the SOFC node temperature control.

The structural integrity of operated components can be assessed by non-destructive mechanical tests performed in-situ with portable instruments. Particularly promising in this context are small scale hardness tests supplemented by the mapping of the residual imprints left on metal surfaces. The data thus collected represent the input of inverse analysis procedures, which determine the material characteristics and their evolution over time. The reliability of these estimates depends on the accuracy of the geometry scans and on the robustness of the data filtering and interpretation methodologies. The objective of the present work is to evaluate the accuracy of the 3D reconstruction of the residual deformation produced on metals by hardness tests performed at a few hundred N load. The geometry data are acquired by portable optical microscopes with variable focal distance. The imperfections introduced by the imaging system, which may not be optimized for all ambient conditions when used in automatic mode, are analysed. Representative examples of the output produced by the scanning tool are examined, focusing attention on the experimental disturbances typical of onsite applications. Proper orthogonal decomposition and data reduction techniques are applied to the information returned by the instrumentation. The essential features of the collected datasets are extracted and the main noise is removed. The results of this investigation show that the accuracy achievable with the considered equipment and regularization procedures can support the development of reliable diagnostic analyses of metal components in existing structures and infrastructures.

The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission carries magnetometers that are dedicated to enhance the satellite’s navigation. After appropriate calibration and characterisation of artificial magnetic disturbances, these observations are valuable assets to characterise the natural variability of Earth’s magnetic field. We describe the data pre-processing, the calibration, and characterisation strategy against a high-precision magnetic field model applied to the GRACE-FO magnetic data. During times of geomagnetic quiet conditions, the mean residual to the magnetic model is around 1 nT with standard deviations below 10 nT. The mean difference to data of ESA’s Swarm mission, which is dedicated to monitor the Earth’s magnetic field, is mainly within ± 10 nT during conjunctions. The performance of GRACE-FO magnetic data is further discussed on selected scientific examples. During a magnetic storm event in August 2018, GRACE-FO reveals the local time dependence of the magnetospheric ring current signature, which is in good agreement with results from a network of ground magnetic observations. Also, derived field-aligned currents (FACs) are applied to monitor auroral FACs that compare well in amplitude and statistical behaviour for local time, hemisphere, and solar wind conditions to approved earlier findings from other missions including Swarm. On a case event, it is demonstrated that the dual-satellite constellation of GRACE-FO is most suitable to derive the persistence of auroral FACs with scale lengths of 180 km or longer. Due to a relatively larger noise level compared to dedicated magnetic missions, GRACE-FO is especially suitable for high-amplitude event studies. However, GRACE-FO is also sensitive to ionospheric signatures even below the noise level within statistical approaches. The combination with data of dedicated magnetic field missions and other missions carrying non-dedicated magnetometers greatly enhances related scientific perspectives.

Helicoidal ferromagnetic materials' spin spirals in the magnetic soliton lattice provide excellent computer storage capability. In this study, we successfully prepared FexCr1−xNb3S6 powders using powder metallurgy. Through elemental analysis and x-ray diffraction analysis, the consistent distribution of Fe elements throughout the powder and the solid solution of Fe into Cr atom occupancy were confirmed . The magnetization response to a magnetic field exhibited a complex behavior, as the gradual replacement of Cr with Fe transformed the material from ferromagnetism to antiferromagnetism. Additionally, step-like magnetic transitions in FeNb3S6 powders were discovered . To further explore these phenomena, we prepared FeNb3S6 single crystals using chemical vapor transport. The single crystal analysis revealed a highly distinct pattern of more stable steps (30–120 K) in the dM/dH curve, indicating a change in spin spirals within the magnetic solitons due to minor magnetic disturbances and a strong anisotropy energy. The replacement of Cr by Fe leads to a rearrangement of the direction of magnetic moments, resulting in the disappearance and emergence of the magnetic solitons. These findings contribute to the development of a novel material system for spintronic memory devices, harnessing a chiral magnetic structure.