Tracking Deviation Research Articles

Topographic Rainfall of Tropical Cyclones past a Mountain Range as Categorized by Idealized Simulations

Abstract Topographic rainfall induced by westbound tropical cyclones past an island mountain is investigated using an idealized Weather Research and Forecasting (WRF) Model. Idealized simulations with varying vortex core size R (100–250 km), vortex intensity Vmax (20–35 m s−1), and steering wind speed U (4–10 m s−1) are conducted. The results show that the geometric distributions of major rainfall over the island are not greatly sensitive to cloud microphysics schemes using either single momentum or double momentum. Major rainfall is produced over northeastern and southwestern slopes of the mountain for smaller U. As U is doubled, the rainfall, however, is considerably weakened or is present only over southwestern slopes. For smaller U, a bifurcation of island rainfall with a sudden change in intensity or geometric shifting exists within a tiny range of R or Vmax. When the bifurcation occurs with small track deviations, geometric distributions of major rainfall are also more sensitive to cloud microphysics schemes. Such formation of bifurcation or double-peak rainfall, however, is significantly reduced when the terrain size is doubled. Systematic experiments are conducted to relate the topographical rainfalls over the northern half, southern half, and the whole of the mountain slopes to varying R, Vmax, and U. Larger U tends to produce much larger southern rainfall than northern rainfall. The average and maximum rainfalls generally increase with increased Vmax, except for large R. The decrease of average rainfall and maximum rainfall with increased U is more evident for smaller R, while not necessarily true for larger R.

Impact of ocean mixed‐layer depth initialization on the simulation of tropical cyclones over the Bay of Bengal using the WRF‐ARW model

AbstractThe sensitivity of the simulated tropical cyclone (TC) intensity and tracks to the different ocean mixed‐layer depth (MLD) initializations is studied using coupled weather research and forecasting (WRF) and ocean mixed‐layer (OML) models. Four sets of numerical experiments are conducted for two TCs formed during the pre‐ and post‐monsoon. In the control run (CONTROL), the WRF model is initialized without coupling. In the second experiment, the WRF‐OML model is initialized by prescribing the MLD as a constant depth of 50 m (MLD‐CONST). In the third experiment, the spatial varying MLD obtained from the formulation of depth of the isothermal layer (MLD‐TEMP) is used. For the fourth experiment (MLD‐DENS), the model is initialized with the density‐based MLD obtained from ARMOR‐3D data. The results indicate that the CONTROL exhibits an early intensification phase with a faster translation movement, leading to early landfall and the production of large track deviations. The coupled OML simulations captured the deepening phase close to the observed estimates, resulting in the reduction of errors in both the vector and along the tracks of the storm. The initialization of the different estimates of the MLD in the WRF‐OML shows that the TC intensity and translation speed are sensitive to the initial representation of the MLD for the post‐monsoon storm. The gradual improvements in the intensity and translation speed of the storm with the realistic representation of the OML are mainly due to the storm‐induced cooling, which in turn alters the simulated enthalpy fluxes supplied to the TC, leading to the better representation of secondary circulation and the rapid intensification of the storm.

Transformation of Managerial Innovations in Conditions of Digitalization of Market Relations

To date, the changes provoked by the digital economy have affected all industries, from the growing interest in cryptocurrencies, developments in the field of financial technologies, the Internet of things (IoT), intuitive programming, online education and significant progress in gene therapy. Management as a science of management also undergoes innovative changes, turning into a "digital" reality. Production management is implemented through ERP systems that allow you to remotely reconfigure the production line, track deviations in the use of materials, etc. Other types of requirements are also imposed on personnel management, such as the possession and application of emotional intelligence, determined by the person's ability, in this case, the manager, to recognize emotions, understand the intentions, motivation and desires of other people, and the ability to manage their feelings and emotions of other people in order to solve practical problems. Collaboration with freelancers and working with an outsourcing pool allows you to enter the global virtual labour market and attract the best talents on a worldwide scale. All of the above tasks can be attributed to the category of a more high-tech, high-tech level than standard management decisions. To move to this "new" level, significant modernization of both technologies and methodological approaches to the system of managerial innovations is required. The article describes the main types of managerial innovations, offers methodologies for assessing the quality of management, and analyzes the impact of the introduction of individual tools at leading enterprises and outsiders on their effectiveness and competitiveness in the digital economy.

Target tracking from infrared imagery via an improved appearance model

Moving target tracking from the infrared images is a challenging task due to the targets’ unstable appearance, complex background clutters and a limited number of pixels for each target. To address this challenge, we propose an infrared target tracking method that combines the Sparsity-based Generative Model (SGM) and Guided Filter-based Discriminative Classifier (GFDC) with the particle filter. The SGM model extracts an effective template histogram, which considers the spatial information of each image patch. In the GFDC model, the guided filter uses the structural information of the guidance image in order to smooth the input image, while preserving the edges. This enhances the information of templates while suppressing the noise in the image data. The Bayesian classification is then applied to take the background into consideration when the model is fused. The online update scheme not only considers appearance variations but also relieves the tracking deviation problem. At last, we utilize the joint confidence values to measure the candidate templates for the target position estimation. Experiments based on infrared video sequences have validated the superior tracking performance of the proposed method.

Boost Converter based on Photovoltaic Energy System

The study of the PV system are growing because of large, protected, important, exhaustible and available resource for the future energy supply. The solar output power is dependent on the intensity of the solar cell temperature and radiation of the solar cells. Though PV power generation system implements an efficient utilization of the solar energy, but the conversion energy of the solar cell is very low. Therefore, MPPT is employed in the PV system to make the most of the result as an output power, regardless of the power, temperature & irradiation circumstances & of load electrical characteristics. In this work the step up converter is utilized to control the PV power using MPPT control mechanism. The PV module is examined by means of SIMULINK software. The simulation result shows that the proposed MPPT control can be avoided. Tracking deviation and improved result performance in both dynamic state and response can be achieved.

Regulatory-intervented sustainable generation expansion planning in multi-electricity markets

Nowadays, according to sustainable development targets in modern societies, electricity markets are gradually connecting together. In this way, in this paper, a multi-agent generation expansion planning in a joint multi-electricity market environment is proposed. The GENCO (Generation Company) agents, competing in a deregulated structure, try to obtain the most profitable investment and operation plan regarding the incentives/taxes that the regulatory sector legislates. The multi-area market assumption encourages the GENCOs to offer their energy blocks to adjacent electricity markets whenever the production capacity is higher than the local load. To confront the uncertainties such as wind speed, market price, and load demand, the Markov chain method is employed. The regulatory entity which monitors the market feedbacks such as reliability, pollution, and renewable penetration, announces the smart stimulating signals to the agents. The signals are sent back to the agents based on a MIMO (Multi Input Multi Output) PID (Proportional–Integral–Derivative) controller which has predefined social-welfare-oriented reference values. In order to verify the efficacy of the study, the results are compared with conventional single electricity market planning framework. The findings underline that by linking the markets together and applying the MIMO controller, the social welfare goals including costs, emissions, and reliability of supply could be improved. A typical average 25 and 50 percent reduction in carbon emission and tracking deviation respectively, verifies the effectiveness of the proposed model.

Design and Test of Admittance Control with Inner Adaptive Robust Position Control for a Lower Limb Rehabilitation Robot

Although admittance control has been used in rehabilitation robots in many studies as it can realize compliant human-robot interaction, the inner proportional-integral-derivative (PID) controller of conventional admittance schemes is simple and not robust enough. This study presents an admittance control scheme with inner adaptive robust position control (ARC) for a hip-knee-ankle rehabilitation robot. The ARC is capable of eliminating uncertainties and external disturbances. A healthy male subject was required to perform three experiments, including passive exercise (PE) using a position controller, patient-cooperative exercise using an admittance controller (ACE) with fixed and different parameters. The PE experiment results show that the average normalized root mean square deviation (NRMSD) of trajectory tracking of each joint using the ARC is nearly 60% less than that using the PID controller. And the ACE experiment results show that the average NRMSD using the ARC is roughly 45% less than that using the PID controller while the interaction torque using the two controllers are comparable. It demonstrates that the robot becomes not only compliant but also robust based on the proposed control scheme. Moreover, the last experiment results indicate that admittance control with smaller admittance parameters allows the robot to be more compliant.

An Effective Autofocus Method for Fast Factorized Back-Projection

Back-projection (BP) is a reliable synthetic aperture radar (SAR) imaging algorithm because of its high-resolution and strong adaptability. However, it is hard to implement because of its high computational complexity. Fast factorized BP (FFBP) is a new way to fix this problem. Like traditional BP, FFBP is compatible with arbitrary flight paths if the track deviations are measured within fractions of a wavelength. However, when the motion information is not accurate enough, autofocus become an important way to get well-focused images. In this paper, we present an effective autofocus method for FFBP to solve the imaging problem caused by platform’s motion errors. First, an image quality evaluation function with unknown phase error based on image sharpness for FFBP is established. Then, the phase error computation for autofocus is modeled as an optimization problem. Second, the coordinate descent (CD) and secant processing are introduced to the maximum image sharpness problem. The proposed method keeps the rapid imaging performance of FFBP and solves well the motion error compensation problem. In the end, simulated data and real data were used to verify the effectiveness of the proposed algorithm.

A Modified perturb-and-observe-based Maximum Power Point Tracking Technique for Photovoltaic Energy Conversion Systems

One of the most widely used maximum power point tracking (MPPT) methods in photovoltaic systems (PVSs) is perturb and observe (PO (2) the tracking deviation under sudden change as well as gradual variation in the irradiation conditions. This paper proposes a simple modified P&O-based MPPT method for PVSs in which the perturbation size is adaptively determined in such a way that the convergence speed to the MPP is increased and the undesirable oscillations around the MPP are decreased. In addition, the direction of the perturbations is determined on the basis of incremental conductance MPPT method so that the proposed algorithm is capable to extract the maximum power from the PVS, even under sudden or gradual variation in solar irradiation. The validity and effectiveness of the proposed algorithm are investigated using time-domain simulations in the MATLAB® software environment.

Exchange-traded funds as an alternative investment option

We conduct an analysis of Exchange-traded Funds (ETFs), Index and Equity mutual funds and their respective benchmark during the 2010-2015 period for the Portuguese fund industry. For the period 2010-2017, we test ETFs for price inefficiency (existence of deviations between prices and the Net Asset Value) and persistence. We find that the studied ETF does not always outperform index funds in replicating the variations of the PSI 20 index, despite exhibiting better tracking ability when facing downside deviations of the benchmark and a better capacity of smoothing tracking deviations. Regarding ETFs price efficiency and its persistence, the study reveals that the examined ETF is priced at a low average discount with evidence of deviations persistence of at least two days. The investment schemes with the highest ability to track the PSI 20 Index were PSI20 (ETF), BBVA PPA Índice PSI20, and the equity mutual fund BPI Portugal.

Remote laser welding with in-line adaptive 3D seam tracking

Remote laser welding systems can usually focus a laser beam to diameters of 0.1 mm. Therefore, high quality clamping and precise teaching is needed in order to achieve appropriate process tolerance for a sound weld. This brings reservation in the field of small series and user-customized manufacturing, where product individualization requires flexible and adaptive systems as workpiece geometry is not exact due to manufacturing tolerances and thermal deformations during welding. The preparation for welding is therefore often time-consuming. To solve this, we have developed an innovative system, which enables in-line adaptive 3D seam tracking. The system consists of an industrial robot (Yaskawa MC2000), a scanning head (HighYag RLSK; working area 200 mm × 300 mm × 200 mm) with optical triangulation feedback and a fiber laser (IPG, YRL-400-AC; 400 W). A feed-forward loop was used to achieve positioning accuracy of under 0.05 mm during on-the-fly welding. Experimental results show that between welding speeds of 25 and 150 cm/min, average tracking deviations are 0.043 mm and 0.276 mm in y and z directions, respectively. Moreover, teaching times for a specified seam can be shortened for more than 10 times due to the fact that only rough seam teaching is required. The proposed system configuration could be adapted to other classical welding processes.

三轴转台角速度偏差最小跟踪方法

三轴转台角速度偏差最小跟踪方法

A Three-Dimensional Phantom Track Generation for Radar Network Deception (January 2019)

One important issue when multiple cooperating electronic combat air vehicles (ECAVs) are used to generate phantom radar tracks in a radar network is the position inaccuracy, which is the fundamental reasons for the difference between a phantom track and a real track. According to this difference, a radar network can recognize the phantom track from the real target track. In order to solve this problem, first, two kinds of phantom tracks in three-dimensional space are developed from the generalized kinematic framework. Then, the effect of the inaccuracies of radar position and ECAVs position to the phantom track is considered in detail. Finally, the beam rider guidance method is used to compensate the track deviation. The scenario of phantom track generation and the influence factors of the maximum position deviation is simulated and analyzed particularly. The simulation results show that the deviation compensation method can reduce the recognition rate of the phantom track effectively.

A Model Predictive Controller With Switched Tracking Error for Autonomous Vehicle Path Tracking

Autonomous vehicle path tracking accuracy and vehicle stability can hardly be accomplished by one fixed control frame in various conditions due to the changing vehicle dynamics. This paper presents a model predictive control (MPC) path-tracking controller with switched tracking error, which reduces the lateral tracking deviation and maintains vehicle stability for both normal and high-speed conditions. The design begins by comparing the performance of three MPC controllers with different tracking error. The analyzing results indicate that in the steady-state condition the controller with the velocity heading deviation as the tracking error significantly improves the tracking accuracy. Meanwhile, in the transient condition, by substituting the steady-state sideslip for real-time sideslip to compute the velocity heading deviation, the tracking overshoot can be reduced. To combine the strengths of these two methods, an MPC controller with switched tracking error is designed to improve the performance in both steady-state and transient conditions. The regime condition of a vehicle maneuver and the switching instant are determined by a fuzzy-logic-based condition classifier. Both normal and aggressive driving scenarios with the vehicle lateral and longitudinal acceleration combination of 5 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and 8 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> are designed to test the proposed controller through CarSim-Simulink platform. The simulation results show the improved performance of the MPC controller with switched tracking error both in tracking accuracy and vehicle stability in both scenarios.

Recent Studies on Changes in Track and Convection Associated with Tropical Cyclone Landfall

ABSTRACT As a tropical cyclone makes landfall, changes in friction and moisture as well as the presence of topography will modify the flow and subsequently the convection associated with the tropical cyclone. As a result, the distribution of potential vorticity tendencies will be modified, which then leads to track deviations. Modifications of the flow will also lead to changes in the vertical wind shear and hence the convection distribution. It is these interactive processes that cause changes in the track and convective distributions of a tropical cyclone as it moves close to land. This paper presents an overview of some of the recent studies on the changes in track and structure associated with tropical cyclone landfall to provide evidence of these physical processes.

Dependency of tropical cyclone risk on track in South Korea

Abstract. Several previous studies on tropical cyclone (TC) risk assessment have attempted to quantify the relationship between TC damage and its elements (i.e. exposure, vulnerability, and hazard). For hazard parameters, TC intensity (e.g. central minimum pressure, maximum wind speed) and size information (e.g. 30 knot radius of the TC) have been widely utilized. Our risk analysis of 85 TCs that made landfall in South Korea from 1979 to 2010, however, suggests that a small deviation of the TC track in the west–east direction (≤250 km, smaller than the average radius of TC) has a more dominant effect on the extent and distribution of TC damage than TC intensity or size. This significant track dependency of TC damage exists because the TC track is responsible for the realization of hazard change from potential to active. More specifically, although two TCs may have the same intensity and size, locally experienced rainfall and wind speed can vary according to their tracks due to topography. These results suggest that track information should be considered more carefully in assessments of future TC risk.

Identification of the deviation of seam tracking and weld cross type for the derusting of ship hulls using a wall-climbing robot based on three-line laser structural light

To realize fully automatic rust removal from the large splicing weld of a ship hull section, we proposed a laser vision identification method based on three-line laser structural light. First, we calibrated the three-line laser vision sensor and obtained the internal and external parameters of the sensor and the laser plane equation of the three-line stripes. On this basis, to accurately obtain the feature points of the weld, we proposed a stepwise piecewise segmenting method for the laser stripe to approximate the true weld curve near the feature point, and we used a Freeman chain code method to mark the weld feature line to eliminate the abnormal points of the laser stripe. Furthermore, for the vertical and horizontal intersections of large splicing welds, we established a uniform recognition model of the cross-shaped or T-shaped weld based on the height characteristics of the three laser stripes and the distances between adjacent laser stripes. The experimental verification showed that the three-line laser method has better anti-interference ability and more abundant information, and it can accurately calculate the weld deviation and identify the cross-shaped or T-shaped weld types under various working conditions, which laid the foundation for real-time seam tracking and trajectory planning.

Attitude Correction System and Cooperative Control of Tunnel Boring Machine

Recently, trajectory misalignment of tunnel boring machine (TBM) has become a key research area. Although TBMs have been extensively applied in tunneling, hunting motion remains due to inhomogeneous ground encountered during tunneling, TBM structures and ambiguity in attitude correction mechanism. In this paper, TBM attitude correction and motion are studied, and optimized fuzzy rule is obtained by taking into account various TBM constraints and the universe of fuzzy control; then, cooperative control over cylinders in various sections is proposed to reduce TBM trajectory tracking deviation from designed tunnel axis; moreover, a cascade control system combining outer-loop trajectory tracking and inner-loop pressure control is developed to enable unmanned automatic tunneling of the TBM. The practical application results reveal that the proposed system demonstrated accurate TBM attitude correction, high stability, strong engineering applicability and feasible real-time control.

Adaptive-neural-network-based robust lateral motion control for autonomous vehicle at driving limits

Parametric modeling uncertainties and unknown external disturbance are major concerns in the development of advanced lateral motion controller for autonomous vehicle at the limits of driving conditions. Considering that tyre operating at or close to its physical limits of friction exhibits highly nonlinear force response and that unknown external disturbance can be caused by changing driving conditions, this paper presents a novel lateral motion control method that can maintain the yaw stability of autonomous vehicle while minimizing lateral path tracking error at the limits of driving conditions The proposed control scheme consists of a robust steering controller and an adaptive neural network (ANN) approximator. First, based on reference path model, dynamics model and kinematics model of vehicle, the robust steering controller is developed via backstepping variable structure control (BVSC) to suppress lateral path tracking deviation, to withstand unknown external disturbance and guarantee the yaw stability of autonomous vehicle. Then, by combining adaptive control mechanism based on Lyapunov stability theory and radial basis function neural network (RBFNN), the ANN approximator is designed to estimate uncertainty of tyre cornering stiffness and reduce its adverse effects by learning to approximate arbitrary nonlinear functions, and it ensures the uniform ultimate boundedness of the closed-loop system. Both simulation and experiment results show that the proposed control strategy can robustly track the reference path and at the same time maintains the yaw stability of vehicle at or near the physical limits of tyre friction.

Marine invertebrate migrations trace climate change over 450 million years

AbstractAimPoleward migration is a clear response of marine organisms to current global warming but the generality and geographical uniformity of this response are unclear. Marine fossils are expected to record the range shift responses of taxa and ecosystems to past climate change. However, unequal sampling (natural and human) in time and space biases the fossil record, restricting previous studies of ancient migrations to individual taxa and events. We expect that temporal changes in the latitudinal distribution of surviving taxa will reveal range shifts to trace global climate change.LocationGlobal.Time periodPost‐Cambrian Phanerozoic aeon.Major taxa studiedWell‐fossilized marine benthic invertebrates comprising stony corals, bivalves, gastropods, brachiopods, trilobites and calcifying sponges.MethodsWe track deviations in the latitudinal distribution of range centres of age boundary crossing taxa from the expected distribution, and compare responses across latitudes. We build deviation time series, spanning hundreds of million years, from fossil occurrences and test correlations with seawater temperature estimates derived from stable oxygen isotopes of fossils.ResultsSeawater temperature and latitudinal deviations from sampling are positively correlated over the post‐Cambrian Phanerozoic. Simulations suggest that sampling patterns are highly unlikely to drive this putative signal of range shifts. Systematically accounting for known sampling issues strengthens this correlation, so that climate is capable of explaining nearly a third of the variance in ancient latitudinal range shifts. The relationship is stronger in low latitude taxa than higher latitude taxa, and in warm ages than cool ages.Main conclusionsLatitudinal range shifts occurred in concert with climate change throughout the post‐Cambrian Phanerozoic. Low latitude taxa show the clearest climate‐migration signal through time, corroborating predictions of their shift in a warming future.