Search

The virtual inertia technology of DGs (Distributed Generations) can provide inertia and damping support for the power system by imitating the traditional synchronous machine. However, the inherent delay problems around the communication and process links of the virtual inertia control will make an impact on the fast support effect. In this paper, the virtual inertia based hierarchical control scheme considering communication delay for distributed generations integration systems is proposed. The hierarchical control architecture including the PQ primary control and the virtual inertia based secondary control method which can realize the optimal power utilization and certain frequency support under the situation of communication signal delay at the same time. Firstly, the basic hierarchical control scheme for distributed generations and corresponding small signal modeling considering communication delay are presented. Then to enhance the inertia support ability of the distributed generation integration system, an improved hierarchical control strategy considering communication delay is designed based on the robust passivity method to compensate the equivalent delay disturbance. Finally, the effectiveness verification of the proposed control is carried out with the simulation cases in PSCAD platform.

The advancement of hardware and software technology makes multiple cooperative unmanned surface vehicles (USVs) utilized in maritime escorting with low cost and high efficiency. USVs can work as edge computing devices to locally and cooperatively perform heavy computational tasks without dependence of remote cloud servers. As such, we organize a team of USVs to escort a high value ship (e.g., mother ship) in a complex maritime environment with hostile intruder ships, where the significant challenge is to learn cooperation of USVs and assign each USV tasks to achieve optimal performance. To this end, in this paper, a hierarchical scheme is proposed for the USV team to guard a valuable ship, which belongs to problems of sparse rewards and long-time horizons in multi-agent reinforcement learning. The core idea utilized in the proposed scheme is centralized training with decentralized execution, where USVs learn policies to guard a high-value ship with extra shared environmental data from other USVs through communication. Specifically, the ships are divided into two groups, i.e., high-level ship and low-level USVs. The high-level ship optimizes decision-level policy to predict intercept points, while each low-level USV utilizes multi-agent reinforcement learning to learn task-level policy to intercept intruders. The hierarchical task guidance is exploited in maritime escorting, whereby high-level ship's decision-level policy guides the training and execution of task-level policies of USVs. Simulation results and experiment analysis show that the proposed hierarchical scheme can efficiently execute the escort mission. [ABSTRACT FROM AUTHOR]

• A Chebyshev center model is proposed to localize a target node in its estimative region without range measurements. • An ADMM-based parallel efficient projection algorithm (PEPA) with simple iterations is proposed to solve the model. • The proposed PEPA is applied to localize multiple target nodes via a hierarchical scheme with low communication burden. • The localization performance is improved by a layer-wise error correction mechanism. Localizing target nodes is a fundamental problem for wireless sensor networks (WSNs). Without range measurements, the range-free techniques, which only exploit the connectivity information among nodes, have been widely studied in the past score years. How to achieve a good balance between the localization accuracy and the communication cost has not been well solved. In this paper, we first decide the estimative region of a target node using the information from both its one-hop and two-hop neighboring anchors. Then we establish a Chebyshev center model to localize a single target inside its estimative region via a nonconvex optimization problem, which is solved by the proposed ADMM-based parallel efficient projection algorithm (PEPA). By introducing a hierarchical scheme, the PEPA is further applied to localize multiple targets layer by layer, which enjoys very low communication cost. Moreover, a novel heuristic layer-wise error correction mechanism is proposed to enhance the positioning precision. Simulation results illustrate the advantage of the proposed algorithms against the existing major range-free methods. [ABSTRACT FROM AUTHOR]

This paper presents a novel recognition scheme for vehicle make and model recognition (VMMR) from frontal images of vehicles. In general, we introduce some domain knowledge to cope with this task. The structural components contained in the frontal appearance of vehicles present different visual characteristics and their discriminating ability varies when vehicle models belonging to the same brand or different brands are compared. In light of the particularities, we take advantage of the varying discriminating ability of these structural components to perform the recognition task sequentially in two stages. At the first stage, the logo sub-region (which is one of the component-related sub-regions in the region of interest) is applied to classify the vehicle models at the brand level. Different from the traditional brand-level classification that the models of the same brand are considered as a single class, in this paper, multiple sub-classes in one brand class are allowed, since the intra-brand models also exhibit a certain degree of diversity. In this way, the problem of inter-class similarity is remitted. At the second stage, several customized classifiers are trained for each sub-class in the light of the discriminant ability of the remaining sub-regions. The proposed approach has been tested on a large-scale vehicle image database collected in this paper and has achieved the state-of-the-art results. [ABSTRACT FROM AUTHOR]

This paper proposes a distance-based two-stage energy management strategy for power-split plug-in hybrid electric vehicles (PHEVs). One stage is for long-term optimization and the other is for short-term adaptation to actual traffic conditions. Energy consumption in PHEVs depends on the characteristics of the drivetrain as well as the operating conditions such as power demands and their split. Thus, prior to departure, the operating conditions for a whole trip are optimized for the drivetrain characteristics and trip information, which generates optimal speed and state-of-charge profiles. While driving, the operating conditions are adapted to current traffic conditions for a short horizon on the basis of long-term optimization results. In consideration of the changeability of traffic conditions, the proposed energy management strategy is performed in a distance domain, which localizes the effects of changes in traffic conditions on the long-term optimization results. Therefore, this distance-based two-stage strategy improves the balance between the optimality and the real-time computing time, which is suitable for online management. A model for the propulsion system in a PHEV and the energy management strategy were formulated in a distance domain. An estimation of distribution algorithm was used for long-term optimization and local adaptation. [ABSTRACT FROM AUTHOR]

Hierarchical classifications are used in the field of clastic deep-marine sedimentary geology to assign spatial and temporal order to the sedimentary architecture of preserved deep-marine deposits and to genetically related modern landforms. Although such classifications aim to simplify the description of complex systems, the wide range of developed approaches limits the ease with which deep-marine architectural data derived from different sources can be reconciled and compared. This work systematically reviews and compares a selection of the most significant published hierarchical schemes for the description of deep-marine sedimentary architecture. A detailed account of each scheme is provided, outlining its aims, environmental contexts and methods of data collection, together with the diagnostic criteria used to discern each hierarchical order from observational standpoints (e.g., via facies associations, geometry, scale and bounding-surface relationships) and also on interpretational grounds (e.g., processes and sub-environments of deposition). The inconsistencies and pitfalls in the application of each scheme are also considered. The immediate goal of this review is to assist sedimentologists in their attempts to apply hierarchical classifications, both in the contexts in which the classifications were originally developed and in alternative settings. An additional goal is to assess the causes of similarities and differences between schemes, which may arise, for example, in relation to their different aims, scales of interest or environmental focus (e.g., channelized or lobate units, or both). Similarities are found between the approaches that commonly underlie the hierarchical classifications. Hierarchies are largely erected on the basis of common types of observations, in particular relating to the lithology and geometries of deposits, in association with analysis of bounding-surface characteristics and relationships. These factors are commonly considered in parallel with their associated genetic interpretations in terms of processes or (sub-) environments of deposition. A final goal of the review is to assess whether a universal standard for the description of deep-marine sedimentary architecture can be devised. Despite the commonalities that exist between classification approaches, a confident reconciliation of the different hierarchical classification schemes does not appear to be achievable in the current state of knowledge. [ABSTRACT FROM AUTHOR]

Increasing wind power (WP) integration is forcing conventional units to go through more frequent and significant cycling operations, which would accelerate wear and tear to unit components and eventually affect the unit's lifespan. In this context, this paper proposes a hierarchical scheme to control the power of plug-in electric vehicles (PEVs) to mitigate unit ramp cycling (URC) operations. A general-form representation of the URC operation is proposed for the first time. At the top level of the hierarchical scheme, a system net load variation range (NLVR) is constructed first to capture the uncertainty in WP forecasts, and then the PEV power is scheduled to reshape the NLVR so as to minimize the URC operations that can be caused by the possible net load realizations in the NLVR. Based on updated WP forecasts, the middle-level dispatch model exempts overscheduled anti-URC regulation onus on PEVs to promote PEV charging. At the bottom level, a decentralized PEV charging control strategy is used to implement the PEV power dispatch instruction. Simulation results verify that the proposed scheme can avert the URC operations effectively, while preserve most of the desired PEV charging energy. Simulation results also show that the proposed scheme is more capable of withstanding WP forecast errors compared with its deterministic version and a benchmark scheme. [ABSTRACT FROM PUBLISHER]

The Paraguaçu watershed in northeastern Brazil faces increasing water scarcity, with water resources unable to meet the increasing demand. Accurate assessment of water availability is thus essential for efficient planning and management of local resources. In this work, the potential of the SWAT model for predicting daily and monthly variability of the hydrologic regime of the Paraguaçu River was assessed. Model calibration/validation followed: (i) A hierarchical framework; (ii) the assessment of maximum, average and minimum streamflow based on paired t-test and linear regression analysis; and (iii) the definition of permanence curves for streamflow with a probability of occurrence of 90% (Q90) and 95% (Q95). The goodness-of-fit indicators revealed a “satisfactory” model performance (model efficiency ranged from 0.42 to 0.83) when predicting streamflow in monitored sub-basins using a unique set of parameters for wet and dry conditions. The flow duration curves also showed that the model underestimated higher flows resulting from extreme events but performed well for flows with exceedance probabilities of

Given the unavailability of high resolution biostratigraphic data and difficulties in using lithostratigraphy for stratigraphic correlation, it was decided to employ chemostratigraphy to propose a scheme for the Silurian Qusaiba Member encountered in five wells in Eastern Saudi Arabia. Chemostratigraphy may be defined as a reservoir correlation technique involving the utilization of inorganic geochemical data. Although Inductively Coupled Plasma – Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma – Mass Spectrometry (ICP-MS) were used to acquire data for 50 elements, the scheme is based on changes in the following ‘key’ element ratios: Zr/Th, Cr/Ti, Th/Nb, Zr/P, Y/Yb, Zr/Yb and Y/P. Variations in these parameters are largely dependent on changes in source/provenance, reflecting increases or decreases in the abundances of particular detrital heavy minerals. The scheme comprises a hierarchical order of four zones, seven subzones and four divisions. The zones are labelled C1, C2, C3 and C4 is ascending stratigraphic order, with two, three and two subzones identified in C2, C3 and C4 respectively. In addition to this, chemostratigraphic divisions are noted in two of the subzones. The chemostratigraphic scheme is considered robust as chemozones (general term used to describe any zone, subzone or division) are clearly defined in each well using geochemical profiles and binary diagrams plotted for key element ratios. Furthermore, high levels of statistical confidence are associated with the chemozones and most are correlative between three or more wells. The nonexistence of chemozones in particular wells is mainly explained by the sampling strategy employed. For example, the absence of subzone C3-2 (occurring towards the center of zone C3) in wells 4 and 5 is most likely to be explained by the uppermost part of the Qusaiba Member not being sampled. In other instances, particular chemozones may be missing as a result of erosion/non-deposition on a local scale. One positive aspect of the study is that it was possible to identify the mid-Qusaiba reservoir sandstones which occur within chemozone C3-3 (at the top of zone C3) in each well. Consequently, chemostratigraphy may be utilized to recognize these sandstones in future wells, particularly in subhorizonal ones where their identification may be more difficult using wireline log signatures alone. [ABSTRACT FROM AUTHOR]

Automatic target recognition of ground surveillance radars is a beneficial practice that reduces cost, error, duration of detection and response time. The identification of echoes from eight classes using an RF pulsed Doppler radar is studied. Instead of traditional methods, the wavelet packet analysis (WPA) is used. WPA, by providing arbitrary time–frequency resolution, enables analysing signals of stationary and non‐stationary nature. It has better time representation than Fourier analysis and better high‐frequency resolution than wavelet analysis. WPA subimages are further analysed to obtain feature vectors of log energy entropy in all cases except one case where norm entropy is used. These features are fed into a multilayer perceptron for classification which is done in a hierarchical scheme and composed of binary classification steps. Hundred per cent accuracy was possible in all steps except two which were realised at 99.5 and 98.2%. An overall classification rate of 98.2% was achieved. The results were compared with other published results that report accuracy in the same application field. The proposed method achieved the highest accuracy although it had the highest number of classes. The method provides a promising tool for the automatic recognition of ground surveillance radar targets. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have a wide range of applications in our lifetime. Indeed, WSNs perform a various missions and tasks in odor localization, firefighting, medical service, surveillance and security. In order to accomplish these tasks, the sensors have to perform partitioning protocols to form an organization into clusters and cliques. The hierarchical clustering is the key solution for WSNs to deal with the scalability problems in a network composed of millions of nodes. In this paper, a new hierarchical partitioning scheme is presented, named MCCC. It is cliques and clusters based hierarchical scheme that takes into account the size of cliques and clusters, it also minimizes the number of hops between the cluster head and its nodes. The proposed scheme is motivated by the need to have minimum and maximum size for cliques and clusters. This hierarchical scheme is proposed to respond to the energy and memory constraints for WSNs. [ABSTRACT FROM AUTHOR]

In this paper, a structurally optimized wavelet network based adaptive control scheme is presented for a class uncertain underactuated system subjected to input constraints. This paper addresses the issue of curse of dimensionality associated with the multidimensional wavelet networks based on tensor product approach and presents a structural optimization scheme to tackle the problem of curse of dimensionality and to develop a parsimonious network structure. Optimization scheme utilizes genetic algorithm (GA) as the heuristic search technique to determine the optimal subset of the wavelet functions for the construction of wavelet network. Controller is developed by applying a two level hierarchical scheme and it incorporates wavelet network to mimic the system uncertainties as well as the nonlinear dynamics invoked by the actuator saturation. Boundedness of closed loop signals in uniform ultimate sense is proved by constructing a Lyapunov function. Results of the simulation demonstrate the effectiveness of proposed approach. [ABSTRACT FROM AUTHOR]

This paper discusses the necessity, feasibility, and technology of FOPEN GMTI. It argues that this functionality may be one mode in a multi-function UWB UHF system, which jointly possesses the capabilities for air target MTI and high resolution FOPEN SAR. The radar platform may be a UAV or an aircraft, whereas, we propose to use the push boom type of antenna mounting previously adopted with the advantage for the CARABAS II UWB VHF SAR. Presently, the push booms will hold a set of UWB UHF antenna elements. This paper relates GMTI to SAR, extended from imaging stationary ground to the 4-parameter set of targets in linear and uniform motion relative to ground. It is recognised that this extended imaging problem depends on one new parameter, i.e., the SAR focusing velocity. The required signal processing may be tackled in an efficient manner by a hierarchical scheme based on iteratively merging subapertures and increasing the resolution. Rejection of stationary clutter and detection occurs on all levels of increasing resolution. This paper also provides a brief presentation of the Swedish FOA efforts to produce an experimental demonstrator of this multi-function radar system [ABSTRACT FROM PUBLISHER]

A novel IFS coding scheme is proposed for image compression. The present method is based on hierarchical structure or the Gaussian pyramid of contracted images. In comparison with the conventional scheme (IFS or JPEG), the presently introduced hierarchical scheme is found to be useful, especially for relatively low-bit rates. This is considered to be as a result of the subband division of the original image and the existence of the redundancy between the range and domain characteristics in the image. On the basis of the present scheme, it is found that the bit rate may be reduced up to the conventional scheme with the transform coding scheme, for the original monochrome image with 2.56 × 256 size and 8-bit gray-scale levels. [ABSTRACT FROM AUTHOR]

The Paraguaçu watershed in northeastern Brazil faces increasing water scarcity, with water resources unable to meet the increasing demand. Accurate assessment of water availability is thus essential for efficient planning and management of local resources. In this work, the potential of the SWAT model for predicting daily and monthly variability of the hydrologic regime of the Paraguaçu River was assessed. Model calibration/validation followed: (i) A hierarchical framework; (ii) the assessment of maximum, average and minimum streamflow based on paired t-test and linear regression analysis; and (iii) the definition of permanence curves for streamflow with a probability of occurrence of 90% (Q90) and 95% (Q95). The goodness-of-fit indicators revealed a "satisfactory" model performance (model efficiency ranged from 0.42 to 0.83) when predicting streamflow in monitored sub-basins using a unique set of parameters for wet and dry conditions. The flow duration curves also showed that the model underestimated higher flows resulting from extreme events but performed well for flows with exceedance probabilities of <90%. The regression analysis and paired t-test demonstrated that the SWAT model can be used for estimating maximum, average and minimum monthly streamflow in a region where information is insufficient to support water authorities in the decision-making process. The SWAT model can thus be considered adequate for simulating monthly streamflow in the Paraguaçu watershed. [ABSTRACT FROM AUTHOR]