Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

A hybrid ventilation scheme applied to bidirectional excavation tunnel construction with a long inclined shaft

The breakage and bending of ducts result in a difficulty to cope with ventilation issues in bidirectional excavation tunnels with a long inclined shaft using a single ventilation method based on ducts.To discuss the hybrid ventilation system applied in bidirectional excavation tunnels with a long inclined shaft,this study has established a full-scale computational fluid dynamics model based on field tests,the Poly-Hexcore method,and the sliding mesh technique.The distribution of wind speed,temperature field,and CO in the tunnel are taken as indices to compare the ventilation efficiency of three ventilation systems(duct,duct-ventilation shaft,duct–ventilated shaft-axial fan).The results show that the hybrid ventilation scheme based on duct-ventilation shaft–axial fan performs the best among the three ventilation systems.Compared to the duct,the wind speed and cooling rate in the tunnel are enhanced by 7.5%–30.6%and 14.1%–17.7%,respectively,for the duct-vent shaft-axial fan condition,and the volume fractions of CO are reduced by 26.9%–73.9%.This contributes to the effective design of combined ventilation for bidirectional excavation tunnels with an inclined shaft,ultimately improving the air quality within the tunnel.

Event-triggered H_(∞) PI state estimation for delayed switched neural networks

On state estimation problems of switched neural networks,most existing results with an event-triggered scheme(ETS)not only ignore the estimator information,but also just employ a fixed triggering threshold,and the estimation error cannot be guaranteed to converge to zero.In addition,the state estimator of non-switched neural networks with integral and exponentially convergent terms cannot be used to improve the estimation performance of switched neural networks due to the difficulties caused by the nonsmoothness of the considered Lyapunov function at the switching instants.In this paper,we aim at overcoming such difficulties and filling in the gaps,by proposing a novel adaptive ETS(AETS)to design an event-based H_(∞)switched proportional-integral(PI)state estimator.A triggering-dependent exponential convergence term and an integral term are introduced into the switched PI state estimator.The relationship among the average dwell time,the AETS and the PI state estimator are established by the triggering-dependent exponential convergence term such that estimation error asymptotically converges to zero with H_(∞)performance level.It is shown that the convergence rate of the resultant error system can be adaptively adjusted according to triggering signals.Finally,the validity of the proposed theoretical results is verified through two illustrative examples.

Robust H_(∞)state estimation for a class of complex networks with dynamic event-triggered scheme against hybrid attacks

We investigate the dynamic event-triggered state estimation for uncertain complex networks with hybrid delays suffering from both deception attacks and denial-of-service attacks.Firstly,the effects of time-varying delays and finitedistributed delays are considered during data transmission between nodes.Secondly,a dynamic event-triggered scheme(ETS)is introduced to reduce the frequency of data transmission between sensors and estimators.Thirdly,by considering the discussed plant,dynamic ETS,state estimator,and hybrid attacks into a unified framework,this framework is transferred into a novel dynamical model.Furthermore,with the help of Lyapunov stability theory and linear matrix inequality techniques,sufficient condition to ensure that the system is exponentially stable and satisfies H∞performance constraints is obtained,and the design algorithm for estimator gains is given.Finally,two numerical examples verify the effectiveness of the proposed method.

A New Hybrid WENO Scheme with the High-Frequency Region for Hyperbolic Conservation Laws

In this paper,a new kind of hybrid method based on the weighted essentially non-oscillatory(WENO)type reconstruction is proposed to solve hyperbolic conservation laws.Comparing the WENO schemes with/without hybridization,the hybrid one can resolve more details in the region containing multi-scale structures and achieve higher resolution in the smooth region;meanwhile,the essentially oscillation-free solution could also be obtained.By adapting the original smoothness indicator in the WENO reconstruction,the stencil is distinguished into three types:smooth,non-smooth,and high-frequency region.In the smooth region,the linear reconstruction is used and the non-smooth region with the WENO reconstruction.In the high-frequency region,the mixed scheme of the linear and WENO schemes is adopted with the smoothness amplification factor,which could capture high-frequency wave efficiently.Spectral analysis and numerous examples are presented to demonstrate the robustness and performance of the hybrid scheme for hyperbolic conservation laws.

Event-Triggered Finite-Time H∞ Filtering for Discrete-Time Nonlinear Stochastic Systems

This paper addresses the problem of event-triggered finite-time H∞ filter design for a class of discrete-time nonlinear stochastic systems with exogenous disturbances. The stochastic Lyapunov-Krasoviskii functional method is adopted to design a filter such that the filtering error system is stochastic finite-time stable (SFTS) and preserves a prescribed performance level according to the pre-defined event-triggered criteria. Based on stochastic differential equations theory, some sufficient conditions for the existence of H∞ filter are obtained for the suggested system by employing linear matrix inequality technique. Finally, the desired H∞ filter gain matrices can be expressed in an explicit form.

HYBRID SCHEME FOR COMPRESSIBLE TURBULENT FLOW AROUND CURVED SURFACE BODY

A hybrid central-upwind scheme is proposed. Two sub-schemes, the central difference scheme and the Roets flux difference splitting scheme, are hybridized by means of a binary sensor function. In order to examine the capability of the proposed hybrid scheme in computing compressible turbulent flow around a curved surface body, especially the flow involving shock wave, three typical eases are investigated by using detached-eddy simulation technique. Numerical results show good agreements with the experimental measurements. The present hybrid scheme can be applied to simulating the compressible flow around a curved surface body involving shock wave and turbulence.

Asynchronous gain-scheduled control of deepwater drilling riser system with hybrid event-triggered sampling and unreliable communication

This paper investigates the recoil control of the deepwater drilling riser system with nonlinear tension force and energy-bounded friction force under the circumstances of limited network resources and unreliable communication.Different from the existing linearization modeling method,a triangle-based polytope modeling method is applied to the nonlinear riser system.Based on the polytope model,to improve resource utilization and accommodate random data loss and communication delay,an asynchronous gain-scheduled control strategy under a hybrid event-triggered scheme is proposed.An asynchronous linear parameter-varying system that blends input delay and impulsive update equation is presented to model the nonlinear networked recoil control system,where the asynchronous deviation bounds of scheduling parameters are calculated.Resorting to the Lyapunov-Krasovskii functional method,some solvable conditions of disturbance attenuation analysis and recoil control design are derived such that the resulting networked system is exponentially mean-square stable with prescribed H∞performance.The obtained numerical results verified that the proposed nonlinear networked control method can achieve a better recoil response of the riser system with less transmission data compared with the linear control method.

Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

This paper investigates the problem of outlier-resistant distributed fusion filtering(DFF)for a class of multi-sensor nonlinear singular systems(MSNSSs)under a dynamic event-triggered scheme(DETS).To relieve the effect of measurement outliers in data transmission,a self-adaptive saturation function is used.Moreover,to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization,a DETS is adopted to regulate the frequency of data transmission.For the addressed MSNSSs,our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS;the local upper bound(UB)on the filtering error covariance(FEC)is derived by solving the difference equations and minimized by designing proper filter gains.Furthermore,according to the local filters and their UBs,a DFF algorithm is presented in terms of the inverse covariance intersection fusion rule.As such,the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers,thereby improving the estimation performance.Moreover,the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is presented.Finally,the validity of the developed algorithm is checked using a simulation example.

Defending Against Link Failure in Virtual Network Embedding Using a Hybrid Scheme

Nowadays network virtualization is utterly popular.As a result,how to protect the virtual networks from attacking on the link is increasingly important.Existing schemes are mainly backup-based,which suffer from data loss and are helpless to such attacks like data tampering.To offer high security level,in this paper,we first propose a multipath and decision-making(MD) scheme which applies multipath simultaneously delivery and decision-making for protecting the virtual network.Considering different security requirement for virtual link,we devise a hybrid scheme to protect the virtual links.For the critical links,MD scheme is adopted.For the other links,we adopt the Shared Backup Scheme.Our simulation results indicate the proposed scheme can significantly increase the security level of the critical link high in the loss of less acceptance ratio.

A HYBRID FINITE ELEMENT SCHEME FOR INVISCID SUPERSONIC FLOWS

A hybrid monotonous finite element algorithm is developed in the present paper, based on a second-order-accurate finite element scheme and a first-accurate monotonous one derived from the former by a unilateral lumping procedure in one dimensional case. The switch functions for the two dimensional Euler equation system are constructed locally, based on the gradient of the flow field, with special consideration on the information from neighboring elements. Examples show that the new scheme can eliminate oscillations near strong shocks obviously.

Discontinuous event-trigger scheme for global stabilization of state-dependent switching neural networks with communication delay

This paper is concerned with the global stabilization of state-dependent switching neural networks(SDSNNs)viadiscontinuous event-triggered control with network-induced communication delay.Aiming at decreasing triggering times,a discontinuous event-trigger scheme is utilized to determine whether the sampling information is required to be sent outor not.Meanwhile,under the effect of communication delay,the trigger condition and SDSNNs are transformed into twotractable models by designing a fictitious delay function.Then,using the Lyapunov–Krasovskii stability theory,someinequality estimation techniques,and extended reciprocally convex combination method,two sufficient criteria are established for ensuring the global stabilization of the resulting closed-loop SDSNNs,respectively.A unified framework isderived that has the ability to handle the simultaneous existence of the communication delay,the properties of discontinuousevent-trigger scheme,as well as feedback controller design.Additionally,the developed results demonstrate a quantitativerelationship among the event trigger parameter,communication delay,and triggering times.Finally,two numerical examples are presented to illustrate the usefulness of the developed stabilization scheme.

Hybrid Mapping Scheme for Recent Orthogonal FDMA Schemes

Single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency division multiple access (OFDMA) systems are new orthogonal multiple access systems. They have been adopted in the 3GPP long term evolution (3GPP-LTE). In these systems, there are only two types of subcarrier mapping schemes which are the interleaved and the localized. So, introducing a new subcarrier mapping scheme is an important issue, which is the main objective of this paper. In this paper, a hybrid subcarrier mapping scheme is proposed and examined for the SC-FDMA system. Monte Carlo simulations are performed to compare the performance of the proposed scheme with that of the interleaved and the localized schemes. It is shown that a hybrid scheme provides better performance than that of the localized and the same performance as that of the interleaved scheme and increased robustness to carrier frequency offset (CFO) at the expense of increased envelope fluctuations.

Likelihood Inference under Generalized Hybrid Censoring Scheme with Comp eting Risks

Statistical inference is developed for the analysis of generalized type-Ⅱ hybrid censoring data under exponential competing risks model. In order to solve the problem that approximate methods make unsatisfactory performances in the case of small sample size,we establish the exact conditional distributions of estimators for parameters by conditional moment generating function(CMGF). Furthermore, confidence intervals(CIs) are constructed by exact distributions, approximate distributions as well as bootstrap method respectively,and their performances are evaluated by Monte Carlo simulations. And finally, a real data set is analyzed to illustrate all the methods developed here.

A TVD-WAF-based hybrid finite volume and finite difference scheme for nonlinearly dispersive wave equations

A total variation diminishing-weighted average flux （TVD-WAF）-based hybrid numerical scheme for the enhanced version of nonlinearly dispersive Boussinesq-type equations was developed. The one-dimensional governing equations were rewritten in the conservative form and then discretized on a uniform grid. The finite volume method was used to discretize the flux term while the remaining terms were approximated with the finite difference method. The second-order TVD-WAF method was employed in conjunction with the Harten-Lax-van Leer （HLL） Riemann solver to calculate the numerical flux, and the variables at the cell interface for the local Riemann problem were reconstructed via the fourth- order monotone upstream-centered scheme for conservation laws （MUSCL）. The time marching scheme based on the third-order TVD Runge- Kutta method was used to obtain numerical solutions. The model was validated through a series of numerical tests, in which wave breaking and a moving shoreline were treated. The good agreement between the computed results, documented analytical solutions, and experimental data demonstrates the correct discretization of the governing equations and high accuracy of the proposed scheme, and also conforms the advantages of the proposed shock-capturing scheme for the enhanced version of the Boussinesq model, including the convenience in the treatment of wave breaking and moving shorelines and without the need for a numerical filter.

HHR:Hierarchical Hybrid Routing Scheme for Information-Centric Network

Publish/subscribe(pub/sub) paradigm is the main communication model for Information-Centric Network(ICN) proposals.A key issue for pub/sub system is how to route the content objects to the correct subscribers,and ICN is no exception.ICN network would be divided into core domain and many edge domains as today's internet does.HHR(Hierarchy Hybrid Routing scheme) is presented for ICN:A Chord-like routing scheme is used in core domain,while edge domains routing structure can be classified into three categories,Local Routing(LR),Delivery of Local Publication to Core domain(DLPC),and Remote Publication Routing into edge domain(RPR).LR can be decided by each edge domain,which determined by many factors,such as locality characteristic for pub/sub information and local policies.A hierarchical routing algorithm is proposed to solve DLPC and RPR simultaneously.Simulation results demonstrate that HHR can be fast deployed,and can be applied in large scale network or dynamic subscription environment.

Event-Triggered Finite-Time <i>H</i>_∞Control for Switched Stochastic Systems

This paper investigates the problem of event-triggered finite-time H∞ control for a class of switched stochastic systems. The main objective of this study is to design an event-triggered state feedback H∞ controller such that the resulting closed-loop system is finite-time bounded and satisfies a prescribed H∞ level in some given finite-time interval. Based on stochastic differential equations theory and average dwell time approach, sufficient conditions are derived to ensure the finite-time stochastic stability with the prescribed H∞ performance for the relevant closed-loop system by employing the linear matrix inequality technique. Finally, the desired state feedback H∞ controller gain matrices can be expressed in an explicit form.

A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems With A Hybrid Event-Triggered Mechanism

This paper is concerned with the double sensitive fault detection filter for positive Markovian jump systems. A new hybrid adaptive event-triggered mechanism is proposed by introducing a non-monotonic adaptive law. A linear adaptive event-triggered threshold is established by virtue of 1-norm inequality.Under such a triggering strategy, the original system can be transformed into an interval uncertain system. By using a stochastic copositive Lyapunov function, an asynchronous fault detection filter is designed for positive Markovian jump systems(PMJSs) in terms of linear programming. The presented filter satisfies both L_-gain(?_-gain) fault sensitivity and L_1(?_1)internal differential privacy sensitivity. The proposed approach is also extended to the discrete-time case. Finally, two examples are provided to illustrate the effectiveness of the proposed design.

基于FSC和TCSC混合复用的交直流混联线路潜供电弧特性

为提高系统运行稳定性,高补偿度串补装置广泛投入使用,但线路故障后潜供电流存在高幅值的低频分量,潜供电弧难以自熄。针对此问题,基于交直流混联输电线路,研究了不同布置方式下串补度对潜供电流与恢复电压幅值影响,提出了一种固定串补(fixed series compensation,FSC)和可控串补(thyristor controlled series compensation,TCSC)混合复用抑制潜供电弧的方法。此外,为满足线路对高补偿度的需求,设计FSC和TCSC混合复用串补度最佳配置方案。结果表明,交直流混联线路采用串补度40%的双平台分散布置方式,潜供电流与恢复电压幅值达到最小,燃弧时间最短。高补偿度串补线路TCSC采用串补度10%、20%的配置方案更利于熄弧,提高重合闸成功率。

带有预验证机制的区块链动态共识算法

委员会共识和混合共识通过选举委员会来代替全网节点完成区块验证,可有效加快共识速度,提高吞吐量,但恶意攻击和收买易导致委员会发生腐败问题,严重时将影响共识结果甚至造成系统瘫痪.现有工作虽引入信誉机制降低委员会节点腐败的可能性,但开销大、可信度低且无法降低腐败问题对系统的影响.提出一种带有预验证机制的区块链动态共识算法(DBCP),通过预验证机制在较小开销的前提下对委员会进行可靠的信誉评估,及时淘汰委员会中的恶意节点.若腐败问题已影响到共识结果,DBCP会通过动态共识将区块验证权转移到全网节点,并淘汰给出错误意见的委员会节点,避免系统瘫痪.若委员会通过迭代达到高可信状态,则DBCP会将区块验证权交由委员会,全网节点将认同委员会的共识结果,并不再对区块进行验证,进而加快共识速度.经实验验证,DBCP的吞吐量与比特币相比提升了两个数量级,且与Byzcoin相近,可在一个出块周期内快速应对委员会腐败问题,安全性优于Byzcoin.