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1.
A robust event-triggered distributed fusion algorithm is investigated in this paper for multi-sensor systems with unknown failure rates. A detection technique based on standard Gaussian distributed filtering innovation is designed and applied to judge whether the measurement is failed. This filtering innovation can also be used to construct the event-triggered condition. Specifically, the event condition is not triggered if the innovation is below the lower event-triggered threshold and the measurement is regarded as the failure measurement if the innovation exceeds the higher threshold. In the above two cases, the sensor measurement data is not transferred to the local estimator; otherwise, it will be transferred. Then, the sequential fast covariance intersection (SFCI) fusion algorithm is used for local estimation fusion. Besides, to analyze the estimation performance, sufficient conditions are given to demonstrate the boundness of the local estimation and fusion estimation covariance. Finally, a simulation example is given to show the usefulness of the presented algorithm.  相似文献   

2.
In this paper, we study a distributed state estimation problem for Markov jump systems (MJS) over sensor networks, in which each sensor node connects with each other through wireless networks with communication delays. We assume that each sensor node maintains a buffer to store delayed data transmitted from neighbor nodes. A distributed multiple model filter is designed by using the interacting multiple model methods (IMM) and a recursive delays compensation method. In order to ensure the stability, two stability conditions are derived for boundedness of estimation errors and boundedness of error covariance. Finally, the effectiveness of the proposed methods is illustrated by simulations and experiments of maneuvering target tracking.  相似文献   

3.
In this paper, the event-triggered distributed H∞ state estimation problem is investigated for a class of state-saturated systems with randomly occurring mixed delays over sensor networks. The mixed delays, which comprise both discrete and distributed delays, are allowed to occur in a random manner governed by two mutually independent Bernoulli distributed random variables. In order to alleviate the communication burden, an event-triggered mechanism is utilized for each sensor node to decide whether or not its current information should be broadcasted to its neighbors. The aim of this paper is to design event-triggered state estimators such that the error dynamics of state estimation is exponentially mean-square stable with a prescribed H∞ performance index. By resorting to intensive stochastic analysis, sufficient conditions are first derived to guarantee the existence of the desired estimators, and the parameters of the desired distributed estimators are then obtained in light of the feasibility of a certain set of matrix inequalities. A numerical example is employed to illustrate the usefulness of the proposed distributed estimation algorithm.  相似文献   

4.
This paper focus on the distributed fusion estimation problem for a multi-sensor nonlinear stochastic system by considering feedback fusion estimation with its variance. For any of the feedback channels, an event-triggered scheduling mechanism is developed to decide whether the fusion estimation is needed to broadcast to local sensors. Then event-triggered unscented Kalman filters are designed to provide local estimations for fusion. Further, a recursive distributed fusion estimation algorithm related with the trigger threshold is proposed, and sufficient conditions are builded for boundedness of the fusion estimation error covariance. Moreover, an ideal compromise between fusion center-to-sensors communication rate and estimation performance is achieved. Finally, validity of the proposed method is confirmed by a numerical simulation.  相似文献   

5.
Distributed target tracking is an important problem in sensor networks (SNs). In this paper, the problem of distributed target tracking is addressed under cyber-attacks for targets with discrete-time and continuous-time nonlinear dynamics. Two distributed filters are obtained for every node of the SN to estimate the states of a general class of nonlinear targets which can be seen in many practical applications. Compared with the existing results in the literature, the network topology of the SN is assumed to be subjected to the denial-of-service attack such that the communication links among sensor nodes are paralyzed or destroyed by this kind of attack. Moreover, the proposed algorithms are designed based on an event-triggered communication strategy that means the frequency of information transmission and unnecessary resource consumption are significantly reduced. The presented algorithms’ stability is also analyzed in the presence of noise to achieve secure event-triggered target tracking in mean-square. Two simulation examples are utilized to demonstrate the efficiency of the proposed event-triggered algorithms.  相似文献   

6.
This paper is concerned with the event-triggered H∞ state estimation problem for a class of discrete-time complex networks subject to state saturations, quantization effects as well as randomly occurring distributed delays. A series of Bernoulli distributed random variables is utilized to model the random occurrence of distributed delays. For the energy-saving purpose, an event-triggered mechanism is proposed to decide whether the current quantized measurement should be transmitted to the estimator or not. For the state-saturated complex networks, our aim is to design event-triggered state estimators that guarantee both the exponential mean-square stability of and the H∞ performance constraint on the error dynamics of the state estimation. Stochastic analysis is conducted, in combination with the Lyapunov functional approach, to derive sufficient conditions for the existence of the desired estimators whose gain matrices are obtained by solving a set of matrix inequalities. An illustrative example is exploited to show the usefulness of the estimator design algorithm proposed.  相似文献   

7.
《Journal of The Franklin Institute》2019,356(17):10335-10354
This paper is devoted to investigate the designs of the event-based distributed state estimation and fault detection of the nonlinear stochastic systems over wireless sensor networks (WSNs). The nonlinear stochastic systems as well as the filters corresponding to the multiple sensors are represented by interval type-2 Takagi–Sugeno (T–S) fuzzy models. (1) A new type of fuzzy distributed filters based on event-triggered mechanism is established corresponding to the nodes of the WSN. (2) The overall stability and performance, that is mean-square asymptotic stability in H∞ sense, of the event-driven fault detection system is analyzed based on Lyapunov stability theory. (3) New techniques are developed to cope with the problem of parametric matrix decoupling for solving the distributed filter gains. (4) Finally, the desired event-based distributed filter matrices are designed subject to the numbers of the fuzzy rules and a series of matrix inequalities. A simulation case is detailed to show the effectiveness of the presented event-based distributed fault detection filtering scheme.  相似文献   

8.
In this paper, a security consistent tracking control scheme with event-triggered strategy and sensor attacks is developed for a class of nonlinear multi-agent systems. For the sensor attacks on the system, a security measurement preselector and a state observer are introduced to combat the impact of the attacks and achieve secure state estimation. In addition, command filtering technology is introduced to overcome the “complexity explosion” caused by the use of the backstepping approach. Subsequently, a new dynamic event-triggered strategy is proposed, in which the triggering conditions are no longer constants but can be adjusted in real time according to the adaptive variables, so that the designed event-triggered mechanism has stronger online update ability. The measurement states are only transmitted through the network based on event-triggered conditions. The proposed adaptive backstepping algorithm not only ensures the security of the system under sensor attacks but also saves network resources and ensures the consistent tracking performance of multi-agent systems. The boundedness of all closed-loop signals is proved by Lyapunov stability analysis. Simulation examples show the effectiveness of the control scheme.  相似文献   

9.
This article aims at investigating the event-triggered (ET) distributed estimation problem for asynchronous sensor networks with randomly occurred unreliable measurements. We propose two ET mechanisms to schedule data transmissions in this paper. One ET mechanism based on dual-criterion is proposed to schedule the transmissions of measurements and avoid the interferences from unreliable measurements. The other ET mechanism is proposed to schedule the transmissions of local estimates. The connotative information in aforementioned ET mechanisms is exploited for taking full use of available information. Then, we provide the corresponding event-triggered asynchronous diffusion estimator based on the diffusion filtering scheme. In the proposed method, a sensor first generates a local estimate by utilizing available information of asynchronous measurements in each estimation period. Then it fuses available information of asynchronous local estimates to generate a fused estimate. Results of simulations in different cases and experiment in an optical-electronic detection network verify the validity and feasibility of the proposed method.  相似文献   

10.
Radio tomographic imaging (RTI) has wide applications in the detection and tracking of objects that do not require any sensor to be attached to the object. Consequently, it leads to device-free localization (DFL). RTI uses received signal strength (RSS) at different sensor nodes for imaging purposes. The attenuation maps, known as spatial loss fields (SLFs), measure the power loss at each pixel in the wireless sensor network (WSN) of interest. These SLFs help us to detect obstacles and aid in the imaging of objects. The centralized RTI system requires the information of all sensor nodes available at the fusion centre (FC), which in turn increases the communication overhead. Furthermore, the failure of links may lead to improper imaging in the RTI system. Hence, a distributed approach for the RTI system resolves such problems. In this paper, a consensus-based distributed strategy is used for distributed estimation of the SLF. The major contribution of this work is to propose a fully decentralized RTI system by using a consensus-based alternating direction method of multipliers (ADMM) algorithm to alleviate the practical issues with centralized and distributed incremental strategies. We proposed distributed consensus ADMM (DCADMM-RTI) and distributed sparse consensus ADMM (DSCADMM-RTI) for the RTI system to properly localize targets in a distributed fashion. Furthermore, the effect of quantization noise is verified by using the distributed consensus algorithms while sharing the quantized data among the neighbourhoods.  相似文献   

11.
在无线传感器网络中,由于传感器节点的电池不能更换.因此要想办法节省节点的能量以延长无线传感器网络的寿命.高效率的数据融合方式将来自多传感器节点的数据进行综合处理,得出更为准确完整的信息,从而有效地节省了网络资源.  相似文献   

12.
将UWB精确定位功能和TOA/AOA混和定位技术相结合,应用于无线传感器网络簇内节点定位中,为无线传感器网络分簇路由协议提供可靠的位置服务。仿真结果表明,其UWB定位精确度较高,适合簇内节点的相对定位。  相似文献   

13.
This paper studies the distributed Kalman consensus filtering problem based on the event-triggered (ET) protocol for linear discrete time-varying systems with multiple sensors. The ET strategy of the send-on-delta rule is employed to adjust the communication rate during data transmission. Two series of Bernoulli random variables are introduced to represent the ET schedules between a sensor and an estimator, and between an estimator and its neighbor estimators. An optimal distributed filter with a given recursive structure in the linear unbiased minimum variance criterion is derived, where solution of cross-covariance matrix (CCM) between any two estimators increases the complexity of the algorithm. In order to avert CCM, a suboptimal ET Kalman consensus filter is also presented, where the filter gain and the consensus gain are solved by minimizing an upper bound of filtering error covariance. Boundedness of the proposed suboptimal filter is analyzed based on a Lyapunov function. A numerical simulation verifies the effectiveness of the proposed algorithms.  相似文献   

14.
This paper focuses on the filtering problem for nonlinear networked systems with event-triggered data transmission and correlated noises. An event-triggered data transmission mechanism is introduced to reduce excessive measurements transmitted over a bandwidth-constrained network. Considering that process noise and measurement noise are one-step cross-correlated, an UKF-based filtering algorithm which depends on correlation parameter and trigger threshold is presented. Then sufficient conditions are established to ensure stability of the designed filter, where a critical value of the correlation parameter exists. Finally, the effectiveness of the proposed filtering algorithm is demonstrated by comparative simulations.  相似文献   

15.
This paper investigates the consensus of fractional-order multiagent systems via sampled-data event-triggered control. Firstly, an event-triggered algorithm is defined using sampled states. Thus, Zeno behaviors can be naturally avoided. Then, a distributed control protocol is proposed to ensure the consensus of fractional-order multiagent systems, where each agent updates its current state based on its neighbors’ states at event-triggered instants. Furthermore, the pinning control technology is taken into account to ensure all agents in multiagent systems reach the specified reference state. With the aid of linear matrix inequalities (LMI), some sufficient conditions are obtained to guarantee the consensus of fractional-order multiagent system. Finally, numerical simulations are presented to demonstrate the theoretical analysis.  相似文献   

16.
The consensus problem for a multi-agent system (MAS) is investigated in this paper via a sliding mode control mechanism subject to stochastic DoS attack, which may occur on each transmission channel independently and randomly according to the Bernoulli distribution. A distributed dynamic event-triggered strategy is implemented on the communication path among agents, where dynamic parameters are introduced to adjust the threshold of event-triggered condition. After that, a distributed sliding mode controller is proposed for ensuring the stochastic consensus of the MAS. Meantime, a minimization problem is solved to obtain the correct controller gain matrix. At last, a numerical example is shown to demonstrate the presented results.  相似文献   

17.
The consensus problem for a multi-agent system (MAS) is investigated in this paper via a sliding mode control mechanism subject to stochastic DoS attack, which may occur on each transmission channel independently and randomly according to the Bernoulli distribution. A distributed dynamic event-triggered strategy is implemented on the communication path among agents, where dynamic parameters are introduced to adjust the threshold of event-triggered condition. After that, a distributed sliding mode controller is proposed for ensuring the stochastic consensus of the MAS. Meantime, a minimization problem is solved to obtain the correct controller gain matrix. At last, a numerical example is shown to demonstrate the presented results.  相似文献   

18.
本文在研究传统的DV-Hop3D算法基础上提出了一种新无线传感器网络定位算法。新算法在算法的第一阶段设置了跳数阈值参数以减小通信开销,并且在算法的第二阶段用可选择的平均跳距代替固定的平均跳距来计算未知节点到锚节点的距离,最后用Matlab7.1进行了仿真。仿真结果表明,该改进算法可明显提高节点定位精度,并且能有效降低网络通信量。  相似文献   

19.
《Journal of The Franklin Institute》2019,356(17):10260-10276
This paper is concerned with the problem of distributed event-triggered controller design for networked control systems (NCSs) with stochastic cyber-attacks. A decentralized event-triggered scheme is introduced to save the energy consumption and alleviate the transmission load of the network. Each sensor can make its own decision to determine whether the sampled data is delivered to the network or not. By taking two kinds of random cyber-attacks into consideration, a novel mathematical model is constructed for distributed event-triggered NCSs. Sufficient conditions which can guarantee the stability of the control system are obtained by applying Lyapunov stability theory, and the design method of the controller gain is presented in an exact expression. Finally, an example is given to demonstrate the effectiveness of the proposed method.  相似文献   

20.
This paper deals with the distributed estimation problem for networked sensing system with event-triggered communication schedules on both sensor-to-estimator channel and estimator-to-estimator channel. Firstly, an optimal event-triggered Kalman consensus filter (KCF) is derived by minimizing the mean squared error of each estimator based on the send-on-delta triggered protocol. Then, the suboptimal event-triggered KCF is proposed in order to reduce the computational complexity in covariance propagation. Moreover, the formal stability analysis of the estimation error is provided by using the Lyapunov-based approach. Finally, simulation results are presented to demonstrate the effectiveness of the proposed filter.  相似文献   

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