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This paper presents a decentralized technique based protection and control scheme for the active radial distribution network. A partitioning method for radial distribution network with multi-distributed energy resources is developed considering island operation possibility of DER, hence, the active distribution network is partitioned into zones with DER and zones without DER. Directional node configuring...
In this paper, a Distance-Weighted K Nearest Neighboring (DW-KNN) topology is proposed to study self-organized aggregation as an emergent swarming behavior within robot swarms. A virtual physics approach is applied among the proposed neighborhood topology to keep the robots together. A distance-weighted function based on a Smoothed Particle Hydrodynamic (SPH) interpolation approach is used as a key...
Accurate detection of cyber-attacks plays a central role in safeguarding computer networks and information systems. This paper addresses the problem of detecting SYN flood attacks, which are the most popular Denial of Service (DoS) attacks. Here, we compare the detection capacity of three commonly monitoring charts namely, a Shewhart chart, a Cumulative Sum (CUSUM) control chart and exponentially...
Based on the dynamic model of semi — active air suspension with two degree of freedom quarter-car, a controller is designed using backstepping technology and sliding mode control. In the MATLAB / Simulink environment, the effect of backstepping sliding mode controller on car body acceleration, suspension dynamic travel and tire dynamic load is studied. The backstepping controller of the semi-active...
In this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results...
This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm,...
Real-time head pose recognition is an important function of Advanced Driver Assistance System that need to consider the driver's intention. The majority of early head pose recognition techniques utilize multi-axis sensors or 2D camera images to estimate the head pose in 3D space. When running the head pose recognition systems, the driver has to carry a device with multi-axis sensors or the system...
In this paper, we address the problem of target tracking control for mobile robots with limited sensing range. An end-to-end Gaussian process regression learning control method is proposed to transfer the human control experiences to the controller. The end-to-end learning architecture directly learns the control mapping from the original sensing input space to the final control output space in an...
This paper presents a computer vision-based methodology for human action recognition. First, the shape based pose features are constructed based on area ratios to identify the human silhouette in images. The proposed features are invariance to translation and scaling. Once the human body features are extracted from videos, different human actions are learned individually on the training frames of...
This paper is concerned with the non-fragile robust model predictive control (MPC) for a class of polytopic uncertain systems with packet dropouts. A novel system with respect to non-fragile controller and packet dropouts is investigated by MPC approach. A non-fragile controller is adopted with hope to deal with the controller perturbations and deviations, which might be a potential factor for system...
Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can considerably reduce the number of required radio-frequency (RF) chains without obvious performance loss. However, most of the existing hybrid precoding schemes require a complicated phase shifter network, which still involves high energy consumption. In this paper, we propose an energy-efficient hybrid precoding architecture,...
In this paper, we address the problem of person re-identification and action recognition for service robots, which undergoes lack of training dataset for model learning, reduction of feature set discriminative power in changing scenarios, and high complexity of the algorithm computation. An online context-based person re-identification algorithm is proposed, which learns the person model online without...
This paper gives an overall review of research status in rehabilitation robot technology. In order to study the status of rehabilitation robot technology, they are divided into two categories. One of them is auxiliary and replacement robots and another is training and therapeutic robots. The fixed and mobile robots, intelligent artificial limbs and supporting tools of the auxiliary and replacement...
Swarm robotics requires continuous monitoring to detect abnormal events and to sustain normal operations. Indeed, swarm robotics with one or more faulty robots leads to degradation of performances complying with the target requirements. This paper present an innovative data-driven fault detection method for monitoring robots swarm. The method combines the flexibility of principal component analysis...
This paper focus on the introduction and summary of static hand gesture segmentation methods. Starting with the research of image segmentation method and the development of hand gesture recognition, we illustrated the most popular methods in static hand gesture segmentation and their advantages and applicable scope in each image processing steps, by comparing different processing methods used in different...
This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short-circuit faults; open-circuit faults; and partial shading faults). Towards this end, we apply exponentially-weighted moving average (EWMA) control chart on the residuals...
We consider a non-convex constrained Lagrangian formulation of a fundamental bi-criteria optimization problem for variable selection in statistical learning; the two criteria are a smooth (possibly) non-convex loss function, measuring the fitness of the model to data, and the latter function is a difference-of-convex (DC) regularization, employed to promote some extra structure on the solution, like...
This paper proposes an efficient data-based anomaly detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between...
Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale...
We study nonconvex distributed optimization in multiagent networks where the communications between nodes is modeled as a time-varying sequence of arbitrary digraphs. We introduce a novel broadcast-based distributed algorithmic framework for the (constrained) minimization of the sum of a smooth (possibly nonconvex and nonseparable) function, i.e., the agents' sum-utility, plus a convex (possibly nonsmooth...
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