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The problem of sliding mode control for a class of Takagi–Sugeno fuzzy model-based nonlinear one-sided Lipschitz systems is investigated in the paper. Due to the state components are not available, a state observer is designed based on an event-triggering mechanism. Meanwhile, the output measurements transmitted through the communication channels suffer from signal delays. Based on the estimated state, an integral sliding surface is proposed. Then, the sliding mode dynamics is obtained by virtue of equivalent control principle. Further, by constructing appropriate sliding mode controller, the finite-time reachability of predefined sliding surface is surely guaranteed. Moreover, the stability with an H ∞ performance analysis of sliding mode dynamics is undertaken via Lyapunov function theory and the criteria are established in terms of LMI. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed method.

This paper studies the problem of H ∞ control design for a class of singular switching semi-Markovian jump systems, in which the transition rates of jumping process are uncertain and the output measurements suffer from random sensor delays. Firstly, a Luenberger observer is designed to estimate the system state components, based on which an error dynamic is obtained. Then, stochastic stability analysis for the overall closed-loop system is given based on the upper and lower bounds of transition rates. Further, the state feedback controller gain matrices are given by solving a set of sufficient conditions in terms of strict linear matrix inequalities (LMIs), which also guarantee the closed-loop system to be stochastically stabilizable and has a prescribed H ∞ performance index γ . Finally, a numerical example is provided to verify the effectiveness of the obtained result.

As an effective way of improving traffic efficiency, vehicle platoon control has attracted extensive interest recently. Communication between vehicles tends to be affected by communication noises. Aimed at improving communication efficiency, an event-triggered vehicle platoon control under random communication noises is studied in this paper. First, for vehicle platoons with linear third-order dynamics, a time-varying consensus gain $c(t)$ is introduced to reduce the effects of the communication noises. Second, with the introduction of the algebraic graph theory and matrix analysis theory, conditions for internal stability and $l_{p}$ -string stability under random additive communication noises are derived. Third, by utilizing the Lyapunov approach and $It\hat {o}$ stochastic differential equations, the consensus of vehicle platoon under random additive communication noises is proved. Last, to reduce the frequent communication between vehicles, an event-triggered mechanism is introduced, and the design for the triggering parameter is derived. The effectiveness of the proposed method is verified with some numerical simulations.

Cell manipulation is a key technique involved in many cell surgery applications. Various automatic frameworks have been developed for optical manipulation of biological cells without consideration of stochastic perturbations, such as Brownian motion. In this brief, a stochastic control scheme for optical manipulation of biological cells is developed. On the basis of the stochastic dynamic model of an optically trapped biological cell, a vectorial backstepping control strategy and its adaptive case is formulated for cell trajectory tracking. The global noise-to-state stability of a closed-loop system in the presence of stochastic perturbations is analyzed. Simulation results demonstrate the performance of the proposed approach.

Adsorption is an important technique for the separation and purification of various gases. In this study, two types of graphene materials with various morphologies are employed to modify metal–orga...

The mechanical properties of biological cells are known as effective label-free biomarkers in many cell physiological events. Several techniques have been proposed to manipulate, measure, and analyze cell mechanical properties, including micropipette aspiration, atomic force microscopy, optical tweezers, and magnetic tweezers. However, most of these methods have inherent problems in practice, including high equipment cost, complex operation, low accuracy, and low throughput. This paper presents a new method for the mechanical characterization of red blood cells (RBCs) on the basis of a dielectrophoresis (DEP) microfluidic system integrated with newly designed parallel ladder electrodes. The proposed microfluidic system not only can stretch RBCs in single-cell level exactly but also has the advantages of high efficiency and throughput. The DEP force generated by the ITO electrodes was theoretically studied, and a series of experiments were performed to stretch RBCs. The relationship between the DEP force and the strain of the RBCs was analyzed, which elucidated the elongation process of RBC under the domination of DEP force, as well as the maximum elongation ability of RBCs. These quantitative results are helpful for people to understand the characteristics of RBCs.

Micro surface modeling has been widely applied in micro scale systems, and the advanced modeling of micro surface is crucial to the development of micro scale systems. In this study, based on $\sqrt {3}$ subdivision schemes, an improved uniform micro subdivision algorithm is proposed for micro surface modeling. The original $\sqrt {3}$ subdivision scheme could not accommodate the sharp features on the micro surface in determining the micro local property of the surface. However, the proposed improved subdivision algorithm can overcome this difficulty without changing the topology of the subdivision surface. The proposed algorithm uses an interpolation subdivision method and obtains excellent results by preserving the dart, crease, corner, and cone. The micro subdivision surface can reach everywhere smoothly except for some infinite sharp features. The proposed algorithm can also deal with nano models, such as micro robots, nano artificial modeling, and micro 3D characters. The experimental results demonstrate the effectiveness of the proposed model.

This paper is concerned with the problem of finite-time H∞ control for stochastic singular systems with partly known transition rates (TRs). The transition of system parameters follows a finite-state Markov process. Firstly, based on stochastic functional method and linear matrix inequalities (LMIs) technique, sufficient conditions are proposed to ensure finite-time stochastic boundedness (FTSB) and finite-time H∞ stochastic boundedness (FTH∞SB) of considered stochastic singular system. Secondly, by designing a state feedback controller, strict LMI conditions are obtained to guarantee the closed-loop system with partly known TRs to be FTSB and FTH∞SB. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed methods.

This study is concerned with the problem of finite-time filter design for a class of Ito stochastic systems with Markovian switching and distributed time-varying delays. Firstly, a partially mode-dependent filter is designed to accommodate to unreliable network transmission. The attention is focused on deriving sufficient conditions for the filtering error system to ensure the finite-time boundedness and to satisfy a prescribed disturbance attenuation. Then based on stochastic functional theory, the existence of filter is presented by solving existing linear matrix inequalities optimisation problems. Furthermore, the result is extended to the case where the mode information is completely transmitted. Finally, a numerical example is provided to show the effectiveness of the proposed results.

This paper deals with the problem of network-based sliding mode observer design and stabilization for nonlinear semi-Markovian jump systems. To design the observer, an event-triggering condition relies on network framework is proposed based on the system output measurement that transmitted through communication channel. Relying on the estimated state, an integral sliding surface is proposed and corresponding sliding mode controller is constructed to guarantee finite-time reachability of predefined sliding surface. In the analysis of sliding mode dynamics and error dynamics, it is considered that the transition rate information suffer from more generally uncertain cases, especially for the type that the mode jumping information from mode to others are totally unknown. Even so, sufficient conditions are developed to ensure stochastic stability of the overall closed-loop system. Finally, a numerical example is provided to verify the effectiveness of the established method.

In our daily life, the scenes around us are always with multiple labels especially in a smart city, i.e., recognizing the information of city operation to response and control. Great efforts have been made by using Deep Neural Networks to recognize multi-label images. Since multi-label image classification is very complicated, people seek to use the attention mechanism to guide the classification process. However, conventional attention-based methods always analyzed images directly and aggressively. It is difficult for them to well understand complicated scenes. In this paper, we propose a global/local attention method that can recognize an image from coarse to fine by mimicking how human-beings observe images. Specifically, our global/local attention method first concentrates on the whole image, and then focuses on local specific objects in the image. We also propose a joint max-margin objective function, which enforces that the minimum score of positive labels should be larger than the maximum score of negative labels horizontally and vertically. This function can further improve our multi-label image classification method. We evaluate the effectiveness of our method on two popular multi-label image datasets (i.e., Pascal VOC and MS-COCO). Our experimental results show that our method outperforms state-of-the-art methods., Accepted by IEEE International Smart Cities Conference 2018

Cellular mechanical properties are closely related to cell physiological functions and status, and their analysis and measurement help understand cell mechanism. In this study, a microfluidic platform was built to measure the mechanical properties of cells by using dielectrophoretic (DEP) force. The electrodes generally used to stretch cells are made of indium tin oxide, Au, and Pt, which have inherent disadvantages. In this paper, galinstan alloy liquid metal was first introduced as microelectrode to form non-uniform electric filed for red blood cell stretching manipulation. The liquid metal microelectrode is easy to manufacture, low in price, stable at high voltage, and reusable. An effective microfluidic chip integrated with liquid metal electrode was designed and simulated, and a series of experiments to capture and stretch red blood cells was performed. The length of the red blood cells increased from 6 μm to 8 μm under the DEP force from 0 pN to 103 pN. This work also revealed the potential use of liquid metal as microelectrode to manipulate the microparticles and cells in a microfluidic chip.

As one of the key components of aerospace power grid, the performance of on load tap changer (OLTC) of power transformer is very important. So it is necessary to realize real-time monitoring of its status. At present, there is no feasible monitoring scheme to carry out on-line monitoring and fault diagnosis for detecting faults of OLTC. The current waveform of the switching process will be abnormal due to the contact fault, the transition resistance fault, and most of the mechanical faults. This paper presents a fault diagnosis method for OLTC based on the current detection in the process of switching. Through on-line acquisition of current waveform in the switching process, empirical mode decomposition and Hilbert–Huang transform is used to calculate normalized time-frequency spectrum, and extract fault characteristic quantity, which can realize the comprehensive diagnosis of the running state of the equipment, and identify the early fault characteristics, and promote the process of the OLTC’s maintenance, from regular test to condition based maintenance. Experiment results prove that the designed fault diagnosis instrument can effectively monitor the working condition of OLTC during the switching process and make effective fault diagnosis.

Reduced graphene oxide (RGO) samples with optimized types of surface functional groups were hybridized with TiO2 to achieve the selective adsorption and removal of various pollutants. A high ratio of hydroxyl groups was found to be remarkably advantageous for the adsorbtion and decomposition of rhodamine-B (and similar pollutants), while a high ratio of carboxyl groups was found to promote the ability to adsorb and decompose phenol. Moreover, the presence of carboxyl groups on the RGO edge provides a pre-condition to form a close chemical connection with TiO2, which has been proven by the obtained electron paramagnetic resonance (EPR) curve, infrared spectroscopy (IR) and electron lifetime. The resulting composite photocatalysts display excellent photocatalytic activities under both UV- and visible-light illumination, indicating that the well-designed surface micro-circumstances of the RGO are quite significant.

Disruptions are prevalent phenomenons that prevent airline from operating as original scheduled. This paper adopts the iterative fixed-point method for integer programming proposed by Dang and Ye [1] to generate feasible flight routes that are used to construct an aircraft reassignment in response to the grounding of one aircraft. Two division methods are proposed with which the solution space can be divided into several independent segments and implemented a distributed computation. The second division method is emphasized in this paper for the good performance of partial feasible flight routes which are generated by this division approach. Comparison with CPLEX CP Optimizer [2] shows that less partial feasible flight routes which are generated by Dang’s algorithm [1] are required to find an aircraft reassignment when disruptions happen, and this division method is more promising when dealing with long haul airline disruption problem.

Possessing the unique and highly valuable properties, graphene sheets (GSs) have attracted increasing attention including that from the building engineer due to the fact that Graphene can be utilized to reinforce concrete and other building materials. In this work, the nonlocal elastic theory and classical plate theory (CLPT) are used to derive the governing equations. The element-free framework for analyzing the buckling behaviors of double layer circular graphene sheets (DLCGSs) relying on an elastic medium is proposed. Pasternak-type model is adopted to describe the elastic medium. Accordingly, the influences of boundary conditions, size of GSs and nonlocal parameters on the buckling behavior of DLCGSs are investigated. The results show that the OP buckling modes are only sensible to the van der Waals forces.

In this article, a deterministic annealing neural network algorithm is proposed to solve the minimum concave cost transportation problem. Specifically, the algorithm is derived from two neural network models and Lagrange–barrier functions. The Lagrange function is used to handle linear equality constraints, and the barrier function is used to force the solution to move to the global or near-global optimal solution. In both neural network models, two descent directions are constructed, and an iterative procedure for the optimization of the neural network is proposed. As a result, two corresponding Lyapunov functions are naturally obtained from these two descent directions. Furthermore, the proposed neural network models are proved to be completely stable and converge to the stable equilibrium state, therefore, the proposed algorithm converges. At last, the computer simulations on several test problems are made, and the results indicate that the proposed algorithm always generates global or near-global optimal solutions.

This paper proposes a sliding mode control (SMC) strategy to solve the problem of independent control of temperature and humidity in air conditioners; the complexity increases due to the need to make full use of the wind side for cooling. First, dynamics of indoor temperature and humidity are determined based on mathematical models. Second, in order to reduce the chattering effect of SMC and coordinate indoor conditions to satisfy people’s needs, the independent control of temperature and humidity is realized via a novel fuzzy sliding mode control strategy based on reaching laws. Finally, simulation results are provided to verify the effectiveness of the proposed method.

Previous studies show that the indoor environment quality (IEQ) of buildings directly affects human health and comfort. This study aims to predict the change of indoor parameters at the next moment under the influences of the current indoor climate and outdoor climate and control the IEQ parameters based on the human thermal adaption in advance. We combine the simulation and the mathematical method to establish the office building model with air-conditioning and lighting systems and construct the bilinear model of the IEQ parameters and control variables. Unknown parameters are identified using the experimental method. Model predictive control (MPC) based on human thermal comfort is discussed by considering human thermal adaptation, and the neutral temperature is calculated through the dynamic relationship between outdoor and indoor temperatures. Results show that the temperature setpoint is adjusted in accordance with human adaptability, and the air-conditioning, fan, and lighting systems are controlled via MPC. The usage time of air-conditioning and light is reduced, and thus, energy is saved.

Airline disruption is universal phenomenon that block the originally scheduled flights, and the slow recovery scheduling causes a lot of losses to both the airline companies and the passengers. However, it is very difficult to generate a new recovery scheduling in a reasonable time by traditional methods, especially for large dimension airline disruption problem. To deal with this problem rapidly, the airline disruption problem will be reformulated as integer programmings and a distributed network, which is based on the fixed-point iterative method for integer programming, will be developed in this paper. In response to the airport closure, an airplane reschedule is constructed by these feasible flight lines. In the implementation of distributed network, a certain number of independent segments are obtained by dividing the solution space. As a feature of this fixed-point method, the number of partial feasible flight lines, which have to be calculated for finding an optimized airplane reschedule, is much fewer compared with the number needed by CPLEX CP Optimizer. This is the first distributed integer programming method to large airline disruption problems caused by airports closure. In the numerical results, the proposed distributed approach shows promising, especially for solving the large dimension airline disruption problem. CA extern

The execution of the airline operation is often deviated from the original schedule due to some unexpected disruptions, such as aircraft breakdowns and severe weather conditions. In this situation, a recovery plan is needed to get the irregular operation back to normal to minimize the losses of the airline. To produce recovery plans and solve the airline disruption problems, a novel modified traveling salesman problem model is proposed to generate sets of the feasible flight routes for each aircraft fleet type. Then, the feasible flight routes are reassigned to the available aircrafts in each fleet to form a recovery plan. Numerical results show that the approach proposed in this paper is efficient and promising.

The quadratic knapsack problem is an NP-hard optimization problem with many diverse applications in industrial and management engineering. However, computational complexities still remain in the quadratic knapsack problem. In this study, a logarithmic descent direction algorithm is proposed to approximate a solution to the quadratic knapsack problem. The proposed algorithm is based on the Karush–Kuhn–Tucker necessary optimality condition and the damped Newton method. The convergence of the algorithm is proven, and the numerical results indicate its effectiveness.

Graph partitioning, a classical NP-hard combinatorial optimization problem, is widely applied to industrial or management problems. In this study, an approximated solution of the graph partitioning problem is obtained by using a deterministic annealing neural network algorithm. The algorithm is a continuation method that attempts to obtain a high-quality solution by following a path of minimum points of a barrier problem as the barrier parameter is reduced from a sufficiently large positive number to 0. With the barrier parameter assumed to be any positive number, one minimum solution of the barrier problem can be found by the algorithm in a feasible descent direction. With a globally convergent iterative procedure, the feasible descent direction could be obtained by renewing Lagrange multipliers red. A distinctive feature of it is that the upper and lower bounds on the variables will be automatically satisfied on the condition that the step length is a value from 0 to 1. Four well-known algorithms are compared with the proposed one on 100 test samples. Simulation results show effectiveness of the proposed algorithm.

Public lighting has become a large energy consumption in the building automation. Therefore, it is a hot topic to design a reasonable and effective controller for smart light. Based on the calculation formula of the personnel location and the related knowledge of solid geometry and optics, this paper develops a lighting model which is mapping form the person’s position to the lighting area. Using this model, the lighting strategy, which satisfies both the energy saving and the personnel comfortableness, will be obtained. Numerical results show that with the movement of person the lamps also change to meet the illumination standard and to minimize the energy consumption. In this situation, the energy consumption of the lighting system reduces.

Considering the privacy requirements on initial states for second-order consensus in wireless sensor and actuator networks (WSAN s), we focus on the design of one privacy-preserving second-order consensus (PPSC) protocol in a distributed way, and investigate this issue from both the viewpoints of limiting the kind of information to be broadcasted and adding random noises to the broadcasted information. We also investigate the convergence rate and the privacy level of the proposed PPSC protocol, and drive that if only limited information of one node is kept by its neighboring nodes, both its initial velocity and position states will be privacy-preserved. Finally, simulation results are presented to verify the effectiveness of the proposed algorithm.

Periodical calibration is necessary to ensure the accuracy and reliability of voltage transformers. The traditional calibration method requires the power to be off, and the calibration period for this method is too long, meaning that problems with the transformer cannot be found in time. In this paper, a voltage transformer error online calibration system based on open&ndash, closed capacitors is proposed. Two open&ndash, closed capacitors and other auxiliary devices are utilized to construct the standard voltage sensor. The outputs of the open&ndash, closed capacitors are compared with each other to realize accurate self-checking. The average value of the output is used as the final output, which can improve the system&rsquo, s accuracy and reliability. An improved algorithm based on a hybrid convolution window is proposed to extract the fundamental and harmonic signals. Test results show that the variation of the ratio error is less than 0.037%, and the variation of the angle error is less than 0.45&rsquo

A new type of electronic voltage transformer is proposed in this study for big data background. By using the conventional inverted SF_6 transformer insulation structure, a coaxial capacitor sensor was constructed by designing a middle coaxial electrode between the high-voltage electrode and the ground electrode. The measurement of the voltage signal could be obtained by detecting the capacitance current i of the SF_6 coaxial capacitor. To improve the accuracy of the integrator, a high-precision digital integrator based on the Romberg algorithm is proposed in this study. This can not only guarantee the accuracy of computation, but also reduce the consumption time; in addition, the sampling point can be reused. By adopting the double shielding effect of the high-voltage shell and the grounding metal shield, the ability and stability of the coaxial capacitor divide could be effectively improved to resist the interference of stray electric fields. The factors that affect the coaxial capacitor were studied, such as position, temperature, and pressure, which will influence the value of the coaxial capacitor. Tests were carried out to verify the performance. The results showed that the voltage transformer based on the SF_6 coaxial capacitor satisfies the requirements of the 0.2 accuracy class. This study can promote the use of new high-performance products for data transmission in the era of big data and specific test analyses.

Classic core-based instrument transformers are more prone to magnetic saturation. This affects the measurement accuracy of such transformers and limits their applications in measuring large direct current (DC). Moreover, protection and control systems may exhibit malfunctions due to such measurement errors. This paper presents a more accurate method for current measurement based on a circular magnetic field sensing array. The proposed measurement approach utilizes multiple hall sensors that are evenly distributed on a circle. The average value of all hall sensors is regarded as the final measurement. The calculation model is established in the case of magnetic field interference of the parallel wire, and the simulation results show that the error decreases significantly when the number of hall sensors n is greater than 8. The measurement error is less than 0.06% when the wire spacing is greater than 2.5 times the radius of the sensor array. A simulation study on the off-center primary conductor is conducted, and a kind of hall sensor compensation method is adopted to improve the accuracy. The simulation and test results indicate that the measurement error of the system is less than 0.1%.

Graphene sheets are widely applied due to their unique and highly valuable properties, such as energy conservation materials in buildings. In this paper, we investigate the vibration behavior of double layer graphene sheets (DLGSs) in thermal environments which helps probe into the mechanism of energy conservation of graphene sheets in buildingmaterials. The nonlocal elastic theory and classical plate theory (CLPT) are used to derive the governing equations. The element-free method is employed to analyze the vibration behaviors of DLGSs embedded in an elastic medium. The accuracy of the solutions in this study is demonstrated by comparison with published results in the literature. Furthermore, a number of numerical results are presented to investigate the effects of various parameters (boundary conditions, nonlocal parameter, aspect ratio, side length, elastic foundation parameter, and temperature) on the frequency of DLGSs. OA gold - CA extern

This paper introduces a novel Loop subdivision method, which produces a C1 continuity surface including boundaries and creases. The new rules develop Loop subdivision surface by adding a parameter known as a knot interval. Sederberg et al. used knot intervals for sharp features in subdivision surface modeling for the first time. This paper extends the subdivision rule to triangular subdivision meshes. It can generate a pleasant result in Loop subdivision surfaces.

The knapsack feasibility problems have been intensively studied both because of their immediate applications in industry and financial management, but more pronounced for theoretical reasons, as knapsack problems frequently occur by relaxation of various integer programming problems. In this work, the large-scale knapsack feasibility problem is divided into two subproblems. The first subproblem is transforming of the knapsack feasibility problem into a polytope judgement problem which is based on lattice basis reduction. In the next subproblem, a distributed implementation of Dang and Ye’s fixed-point iterative algorithm is introduced to solve the polytope judgement problem generated in the former subproblem. Compared with the branch and bound method, numerical results show that this distributed fixed-point method is effective.

The copper-benzene-1,3,5-tricarboxylate (Cu-BTC) attracts increasing attention because of its large BET surface area available for the adsorption of gases. However, low stability in water creates a barrier for its potential applications. In this study, graphene oxide (GO) and reduced graphene oxide (RGO) are adopted to modify the Cu-BTC. The influence of GO and RGO on the resulting BET surface area, pore diameter distribution, morphology and yield of the Cu-BTC are revealed. It is found that the adsorption abilities of the resulting composites for the polar and nonpolar gas molecules are closely related to the presence at surface of the functional groups of the used graphene samples, which provides a potential method to achieve selective adsorption. Furthermore, the preparation processes of the GO/Cu-BTC and RGO/Cu-BTC exert a significant effect on the performances of the resulting product, which is also studied in detail.

A novel thermal-resistance film is proposed, and its thermal post-buckling behavior is studied by using the meshless method. The Von Kármán plate model together with the nonlocal theory is adopted for the formulation of the problem. The post-buckling curve of the graphene sheet (GS) film is obtained. The effect of the parameters, such as nonlocal parameters, geometric size, geometric shape and elastic medium, on the thermal post-buckling response of the GSs film is examined. It is found that it is important to design proper geometric size and geometric shape and control the radius of tensionless area. This study provides theoretical guidance for fire resistance design of thermal-resistance films attached to glass façade.

Given the unique and extremely valuable properties, research has significantly focussed on graphene sheets (GSs). To premeditate the small-scale effect, the present work applies the nonlocal theory to study the buckling behavior of a double-layered GS (DLGS) embedded in an elastic foundation. To derive the equation, classical plate theory is adopted. For the elastic foundation, Pasternak-type model is used. In terms of buckling response, a meshless method is utilized to compute simulation results. Accordingly, we examine the effects of aspect ratio, geometry, boundary conditions and nonlocal parameters on the buckling responses of DLGSs.

A implementation of the distributed Dang and Ye’s fixed-point algorithm, which is a new alternative algorithm for integer programming, is developed in this paper. This fixed-point algorithm is derived from an increasing mapping which satisfies certain properties. A classical problem, which is called market split problem, has been solved by this distributed implementation. It is shown that this implementation is effective in numerical results. Besides, it can be used to other similar integer problems.