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The paper delves into the problems of stability analysis and state-feedback controller design for discrete-time switched nolinear systems (SNSs), employing mode-dependent average dwell time (MDADT). Dependent on parameter-sensitive discontinuous switching Lyapunov functions and several fundamental lemmas, the key objective is to formulate a controller for the system under consideration to secure stability,and adjusting to the sector's conditions to handle the nested actuator saturation. Then the necessary conditions and the initial zone securing the local exponential stability(LES) of the switched system are put forth. By solving the Linear Matrix Inequality(LMI) conditions, the controller gain is devised, and the system is given a stable attraction domain. The proposed methodology's effectiveness is validated through two illustrative examples.

This paper describes the modeling, simulation and the instrumentation of High Pressure Roller Crusher (HPRC) for the production of silicon carbide grains. The study is to make a model and then simulate a High Pressure Roller Crusher. Selection of sensors for the HPRC is also important in this study. A High Pressure Roller Crusher (HPRC) is an important part in the production of silicon carbide, where the grains are crushed into powder form and then sieved into specified sizes based on its usage. This paper will present a model based on Johanson's theory for roller compactors, considering all the delays. The non-linearity or delays were handled in matlab using. Conclusions were drawn at end of the paper.

Distributed fiber optic vibration sensing system has been widely used in safety monitoring with distinct advantages, and the feature extraction and classification methods of fiber optic signals directly determine the real-time performance and reliability of the monitoring system. The existing research feature extraction methods are unidimensional and time consuming, which cannot balance the goals of high accuracy and low time consumption for safety monitoring systems. In this paper, we propose an efficient recognition framework for fusing signal time-frequency features, called TFF-CNN, based on Gramian Angular Difference Fields(GADF) and FFT co-generation matrix(FFTT) to manually extract two-dimensional time-frequency image features of fiber optic signals, taking the significant advantages of CNN in image processing and combining a two-channel model and a fusion module that simulates human decision-making behavior. The accuracy of TFF-CNN is 99.30% and the detection response time is only 0.6s. Compared with other methods in this field, TFF-CNN has the advantages of low false alarm rate and short time consumption, which is more suitable for deployment in security monitoring field with distributed fiber optic sensing system. Index Terms: Distributed optical fiber vibration sensing system(DVS), Two-dimensional multi-feature, CNN, intrusion detection, real-time monitoring

Graph convolutional networks (GCNs) as the emerging neural networks have shown great success in Prognostics and Health Management because they can not only extract node features but can also mine relationship between nodes in the graph data. However, the most existing GCNs-based methods are still limited by graph quality, variable working conditions, and limited data, making them difficult to obtain remarkable performance. Therefore, it is proposed in this paper a two stage importance-aware subgraph convolutional network based on multi-source sensors named I

We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point (AP) equipped with multiple antennas. The main restriction is that standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is proposed to overcome restrictions imposed by the legacy terminals requirement. In this paper we concentrate on channel estimation over acknowledgement (ACK) bursts and effect of imperfections such as non-ideal channel reciprocity and delayed channel estimates. Simulations based on channel models approved by the IEEE 802.11 Standard Group demonstrate that a near doubling of downlink capacity can be achieved in a conference room environment in the case of low levels of channel reciprocity errors at the AP.

In this work, we present a new and effective method to design discrete-time static output-feedback H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controllers. This new method, based on a Linear Matrix Inequality (LMI) formulation, introduces a suitable transformation of the LMI variables that allows to obtain an explicit expression for the output-feedback gain matrix. Moreover, for problems involving a set of subsystems with information exchange constraints, a convenient structure on the LMI variables can be imposed in order to design semi-decentralized controllers, where the corresponding output-feedback gain matrix has a prescribed zero-nonzero structure. To illustrate the proposed methodology, discrete-time static velocity-feedback H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controllers to mitigate the seismic response of a five-story building are designed. In particular, two different designs are presented: (i) a centralized controller that requires all the inter-story velocities to compute the control actions, and (ii) a semi-decentralized controller that can operate using only the inter-story velocities of neighboring floors.

In this work, we perform a large-scale investigation of teacher connections in online social media. To this end, we first construct a large dataset of teachers on Pinterest, an image-based popular online social media. Our dataset includes 540 teachers across 5 states and 48 districts, as well as thousands of connections they have established. Then, considering some crucial teacher-related attributes (e.g., their states and grade levels), we characterize direct and indirect teacher connections. Through this characterization, we discover that teachers are predominately connected to their peers in the same district or at least within the same state, and seldom there exist links between teachers outside their districts and states. This hinders the proper diffusion of information and many other advantages that a teacher-teacher connection in an online social media can bring about, e.g., getting advice from their peers. To alleviate this problem, we utilize advances in machine learning and propose a link recommendation system suggesting teachers connect with their similar peers on Pinterest. Our system's evaluation reveals that many new teacher-teacher connections are suggested, which leads to a more cohesive network among teachers rather than the existing localized ego networks.

Object Oriented Programming (OOP) is a programming paradigm which be highlighted using the 800xa system. This work will investigate the use of OOP programming for designing industrial application control based on a soft controller. The different types of objects which can be defined in different classes, declaration and implementation using the 800xa will be explored, thus highlighting the use of static, dynamic and embedded objects. In the next phase, an illustration on how to map and use these objects in ABB 800xA for efficient control, hence, providing a systematic approach for accessing any of the plant aspects using a unique plant object.

SUMMARY This paper investigates the problem of delay‐dependent dynamic output feedback control for a class of discrete‐time Markovian jump linear systems (MJLSs). The systems under consideration are subject to time‐varying delay and defective mode information. The defective transition probabilities comprise of three types: exactly known, uncertain, and unknown. By employing a two‐term approximation for the time‐varying delay, the original MJLSs can be equivalently converted into a feedback interconnection form, which contains a forward subsystem with constant time‐delays and a feedback one with norm‐bounded uncertainties. Then, based on the scaled small‐gain theorem, the problem is therefore recast as an control problem in the face of uncertainties via an input–output framework. It is shown that the explicit expressions of the desired controller gains can be characterized in terms of strict linear matrix inequalities via some linearization techniques. Simulation studies are performed to illustrate the effectiveness and less conservatism of the proposed methods. Copyright © 2013 John Wiley &amp; Sons, Ltd.

The problem of sliding mode control design for nonlinear switching semi-Markovian jump delayed systems is investigated in this paper. By choosing a linear switching surface function, we first derive reduced-order sliding mode dynamics; Then, the property of sliding mode dynamics with generally uncertain transition rates is analyzed by checking a set of new conditions; Further, an adaptive sliding mode control law is constructed to ensure the finite-time reaching condition. Finally, a practical example is provided to disseminate the effectiveness of the proposed method numerically.

The paper presents a comprehensive, complex, numerical, optimization methodology (computational framework) dedicated for supporting structures of small-scale wind turbines. The small wind turbine (SWT) supporting structure is one of the key components determining the cost of such a device. Therefore, the supporting structure optimization will allow cost reduction and, hence, popularization of these devices around the world. The presented methodology is based on the following: single-objective (aggregation-approach to multi-objective problem) evolutionary algorithm driven optimization, finite-element structural analyses, estimation of wind energy capture efficiency (coupled aero-servo-elastic numerical simulations), and economic evaluation (based on real meteorological data). Then, the methodology is proposed for a guy-wired mast structure of an arbitrary chosen SWT model. The optimization of chosen design features of the structure is performed and as a result the optimal solution for given assumptions is presented and scaling factor for that case is identified (total mass of the foundations). The successful use of combined numerical methods (genetic algorithms, FE method analyses, coupled aero-servo-elastic numerical simulations, pre-/post-processing scripts, and economic evaluation models) is the main novelty of this work.

This paper develops a cascaded sliding mode observer method to reconstruct actuator faults for a class of descriptor linear systems. Based on a new canonical form, a novel design method is presented to discuss the existence conditions of the sliding mode observer. Furthermore, the proposed method is extended to general descriptor linear systems with actuator faults. Finally, the effectiveness of the proposed technique is illustrated by a simulation example.

In this paper, some small-gain theorems are proposed for stochastic network systems which describe large-scale systems with interconnections, uncertainties and random disturbances. By the aid of conditional dissipativity and showing times of stochastic interval, small-gain conditions proposed for the deterministic case are extended to the stochastic case. When some design parameters are tunable in practice, we invaginate a simpler method to verify small-gain condition by selecting one subsystem as a monitor. Compared with the existing results, the existence-and-uniqueness of solution and ultimate uniform boundedness of input are removed from requirements of input-to-state stability and small-gain theorems.