Cyber-physical systems (CPSs) are integrations of computation, communication, control and physical processes. Typical examples where CPSs are deployed include smart grids, civil infrastructure, medical devices and m...
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Cyber-physical systems (CPSs) are integrations of computation, communication, control and physical processes. Typical examples where CPSs are deployed include smart grids, civil infrastructure, medical devices and manufacturing. Security is one of the most important issues that should be investigated in CPSs and hence has received much attention in recent years. This paper surveys recent results in this area and mainly focusses on three important categories: attack detection, attack design and secure estimation and control. We also discuss several future research directions including risk assessment, modeling of attacks and attacks design, counter-attack strategy and testbed and validation.
It is a tendency for Internet of Things to research Zigbee-WiFi hybrid *** paper introduces a heterogeneous network integration module based on protocol conversion which can integrate 802.15.4 network with 802.11 b **...
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ISBN:
(纸本)9781509009107
It is a tendency for Internet of Things to research Zigbee-WiFi hybrid *** paper introduces a heterogeneous network integration module based on protocol conversion which can integrate 802.15.4 network with 802.11 b *** heterogeneous network integration module resolves mismatch problems on physical layer,MAC layer and address mapping,meanwhile it makes a contrast with existing Zigbee-WiFi gateway and found to be advanced and effective in three performance indexes:network connection speed,SINR(signal interference noise ratio) and network *** design and realization of heterogeneous network integration are based on QualNet simulation software.
A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status ...
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For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively....
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For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control(RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.
In the field of machine vision,camera calibration is a key *** self-calibration,one of camera calibration methods,is only based on the images to calculate the camera’s intrinsic *** has simple calibration process and...
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In the field of machine vision,camera calibration is a key *** self-calibration,one of camera calibration methods,is only based on the images to calculate the camera’s intrinsic *** has simple calibration process and strong *** self-calibration algorithm needs to calculate the epipole and fundamental matrix by solving the Kruppa equation,but the uncertainty of the epipole always leads to large error and long operation *** improve the precision of camera calibration and reduce the time consumption,the parallel quantum particle swarm algorithm(QPSO) is introduced to solve the improved Kruppa *** can figure out the camera intrinsic parameters and transform the calculation of epipole into the adaptive value of the cost *** with the ordinary particle swarm optimization algorithm(PSO),QPSO has less parameters,better robustness and faster convergence *** using a multi-core computer platform,its parallel processing has also combined with the characteristics of parallel computing which improves the calculation *** results show that the proposed method is more accurate than ordinary PSO,and the program time consuming is significantly reduced.
The micro-scale fuel consumption model is a tool commonly used to evaluate the effect of traffic flow conditions on vehicle fuel consumptions, which is an essential step in developing traffic management strategies for...
The micro-scale fuel consumption model is a tool commonly used to evaluate the effect of traffic flow conditions on vehicle fuel consumptions, which is an essential step in developing traffic management strategies for saving fuels. In developing any micro-scale fuel consumption model, the Vehicle Specific Power (VSP) binning method has been widely adopted in recent years as a fundamental approach. Existing studies have shown that the high distribution frequency when VSP=0 contributes to high fuel consumptions, so a question quickly emerged about whether VSP=0 should be designed as an independent VSP bin in the VSP binning method. This paper strives to compare different VSP binning methods for Light-Duty Vehicles (LDVs) on urban roads in Beijing in terms of their effects on the estimation of fuel consumptions. After collecting and processing field vehicle activity data and fuel consumption data, three VSP binning methods are proposed for the study. Then, total fuel consumptions and fuel consumption factors are calculated by using the proposed VSP binning methods as well as the second-by-second and average travel speed data. Finally, the estimation accuracy of total fuel consumptions and fuel consumption factors based on the three different VSP binning methods are compared for LDVs on urban roads. The study proves that an independent VSP bin at VSP=0 is indeed necessary, which can improve the estimation accuracy on both total fuel consumptions and fuel consumption factors.
This paper proposes a dependency-enhanced pre-reordering method for Chinese-English statistical machine translation(SMT).Firstly,two kinds of dependency structure-based rules are extracted based on the source-side dep...
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ISBN:
(纸本)9781509009107
This paper proposes a dependency-enhanced pre-reordering method for Chinese-English statistical machine translation(SMT).Firstly,two kinds of dependency structure-based rules are extracted based on the source-side dependency tree and corresponding word alignments between the source-side and the target-side *** a maximum entropy classifier is used to calculate the orientation probability in terms of swap or monotone between two *** a result,a reordering rule set is *** different ways are proposed to filter out the rule ***,the dependency parsing trees of the training data,development set and the test set are traversed,and if the syntactic sub-tree structure matches the rules in the rule set,the word orders will be ***,a reordered source-side sentence is generated and then fed into an SMT system for *** conducted on NIST Chinese-English MT data sets show that the proposed method significantly improves translation performance by 0.46 BLEU compared to the baseline system.
In this paper, a method for a sort of nonlinear system identification with stochastic time-varying parameter is investigated. This kind of nonlinear systems is referring to the system where probability density functio...
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ISBN:
(纸本)9781509009107
In this paper, a method for a sort of nonlinear system identification with stochastic time-varying parameter is investigated. This kind of nonlinear systems is referring to the system where probability density functions(PDFs) of the parameters are known. This parameter identification and states estimation method is realized based on expectation maximization(EM) algorithm and particle filter. Firstly, parameter particles are generated randomly according to the PDF of parameter. Secondly, the particle filter is employed to estimate system states corresponding to each group of the parameters, and the weight of each group parameters is calculated according to the Bayesian theory. Then the new iteration of parameter is obtained by adopting the expectation maximization algorithm. Lastly, the real parameters are obtained along with system operation. Numerical illustrations are presented to exhibit the effectiveness of the method proposed herein, and the performance of the method is examined.
In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stoc...
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In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stochastic equations, we give stochastic sufficient stability criteria for polytopic uncertain Itô SMJSs. As a corollary, stochastic sufficient stability criteria are given for nominal Itô SMJSs. For this two cases of Itô SMJSs, based on the obtained stochastic stability criteria, their time-independent sampled-data controllers are designed, respectively. Then, for designing a time-dependent sampled-data controller for Itô SMJSs, a parameters-dependent time-scheduled Lyapunov functional is developed. New stochastic sufficient stability criteria are obtained for polytopic uncertain Itô SMJSs and nominal Itô SMJSs. Furthermore, their time-dependent sampled-data controllers are designed, respectively. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed method.
This paper investigates the attitude tracking control problem of reentry vehicle with modeling inaccuracies and external disturbances. An improved nonsingular terminal sliding mode control method is presented, and a f...
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ISBN:
(纸本)9781509009107
This paper investigates the attitude tracking control problem of reentry vehicle with modeling inaccuracies and external disturbances. An improved nonsingular terminal sliding mode control method is presented, and a faster convergence rate is obtained in comparison with the conventional nonsingular terminal sliding mode control(NTSM). By the proposed control strategy, the possible singularity during the control phase is avoided, and robustness is also guaranteed. Simulation is made for a reentry vehicle in the condition aerodynamic parameters and atmospheric density are perturbed. The results show the effectiveness of the proposed strategies.
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