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1.
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   

2.
The optimal widely linear state estimation problem for quaternion systems with multiple sensors and mixed uncertainties in the observations is solved in a unified framework. For that, we devise a unified model to describe the mixed uncertainties of sensor delays, packet dropouts and uncertain observations by using three Bernoulli distributed quaternion random processes. The proposed model is valid for linear discrete-time quaternion stochastic systems measured by multiple sensors and it allows us to provide filtering, prediction and smoothing algorithms for estimating the quaternion state through a widely linear processing. Simulation results are employed to show the superior performance of such algorithms in comparison to standard widely linear methods when mixed uncertainties are present in the observations.  相似文献   

3.
This article focuses on time delay switch (TDS) attacks on power networks subject to highly nonlinear and interconnection. T–S model is utilized to represent each nonlinear power subsystem in the network. In order to attenuate adverse impacts from TDS attacks, a novel control technique of estimation and compensation is proposed. Combined with the method of finite time boundedness (FTB), transient stability of power systems could be achieved. First, an augmented fuzzy observer is constructed to capacitate a synchronous estimation for system states and TDS attacks, which ensures that the estimation error is limited via the intersection operation of ellipsoids within a specified finite time interval. Then, a compensation technique is employed to attenuate the influence from TDS attacks. Finally, simulation results of a distributed power network show the efficacy of the proposed method against TDS attacks.  相似文献   

4.
The authors in [7] obtained the global asymptotical stability for static interval neural networks with S-type distributed delays by using the Razumikhin theorem. The aim of our paper is to investigate the global exponential robust stability by using the Lyapunov functional methods, and we will improve the proof methods more concise. A theorem and a corollary were obtained in which the boundedness, monotonicity and differentiability conditions on the activation functions are not required. So we generalize the results of related literature [7]. As an application, an example to demonstrate our results is given.  相似文献   

5.
Based on the conflict and crosstalk avoidance mechanism (CCAM), we propose a sleeping–awaking method for wireless sensor networks (WSNs) in which the maximal degree node (MDN) and all its neighbors run sleep or wake simultaneously while other nodes run the CCAM. This method is said to be the same sleeping–awaking method (SSAM). The SSAM is motivated by the congestion and collision problems of cliques, MDN and its neighbor set in the communicating graph of the WSN. In this communication way, the related protocol about the SSAM is provided accordingly. Under the designed protocol, we get a Markovian switching WSN with both white noise disturbance and multiple time-varying delays. Based on the theory of exponential stability in pth moment, we show that the protocol ensures the WSNs to keep in synchronization with the target function. A numerical example shows that the WSN can keep its target-synchronization even with large time delays.  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.
This paper is concerned with the adaptive control problem for a class of linear discrete-time systems with unknown parameters based on the distributed model predictive control (MPC) method. Instead of using the system state, the state estimate is employed to model the distributed state estimation system. In this way, the system state does not have to be measurable. Furthermore, in order to improve the system performance, both the output error and its estimation are considered. Moreover, a novel Lyapunov functional, comprised of a series of distributed traces of estimation errors and their transposes, has been presented. Then, sufficient conditions are obtained to guarantee the exponential ultimate boundedness of the system as well as the asymptotic stability of the error system by solving a nonlinear programming (NP) problem subject to input constraints. Finally, the simulation examples is given to illustrate the effectiveness and the validity of the proposed technique.  相似文献   

8.
In this paper, the event-triggered distributed multi-sensor data fusion algorithm is presented for wireless sensor networks (WSNs) based on a new event-triggered strategy. The threshold of the event is set according to the chi-square distribution that is constructed by the difference of the measurement of the current time and the measurement of the last sampled moment. When the event-triggered decision variable value is larger than the threshold, the event is triggered and the observation is sampled for state estimation. In designing the dynamic event-triggered strategy, we relate the threshold with the quantity in the chi-square distribution table. Therefore, compared to the existed event-triggered algorithms, this novel event-triggered strategy can give the specific sampling/communication rate directly and intuitively. In addition, for the presented distributed fusion in wireless sensor networks, only the measurements in the neighborhood (i.e., the neighbor nodes and the neighbor’s neighbor nodes) of the fusion center are fused so that it can obtain the optimal state estimation under limited energy consumption. A numerical example is used to illustrate the effectiveness of the presented algorithm.  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.
In large-scale complex dynamical networks, it is significant to estimate the states of target nodes with only a part of measured nodes. Meanwhile, multilayer complex dynamical networks exist widely in society and engineering. Therefore, it has important theoretic meaning and practical value to study the state estimation of target nodes in multilayer complex dynamical networks with limited node measurements. In this paper, with the measurable state information of a portion of nodes in one layer in the multilayer complex dynamical network, the state estimation of target nodes in other layers is studied. First, we build the model of the multilayer complex dynamical network which includes some target nodes and sensor nodes. Second, auxiliary nodes are selected by using the maximum matching principle in graph theory to construct the augmented node set. Third, we discuss the relationship between the minimum number of auxiliary nodes and interlayer connection probability in the multilayer complex dynamical network. Forth, an appropriate functional state observer is designed with limited number of measured nodes according to a typical model-based algorithm. Finally, numerical simulations are given to demonstrate the accuracy of the proposed method. The proposed method can achieve the accurate estimation with less placement of observers and fewer computational costs in the multilayer complex dynamical network.  相似文献   

11.
《Journal of The Franklin Institute》2021,358(18):10079-10094
This paper is focused on the distributed estimation issue in the form of set-membership (SM) for a class of discrete time-varying systems suffering mix-time-delays and state-saturations. The phenomena of time-delays and state-saturations are introduced to better describe insightful engineering. During local measurements transmission between sensors over a resource-limited sensor network, to prevent data collisions and resource-consumption, a newly dynamic event-triggering strategy (DETS) is designed to dispatch the local measurements transmission for each sensor to its neighbors. Compared with the most existing static ETSs, this DETs can mitigate the total number of triggering times and enlarge interval time between consecutive triggering instants. Then, some novel adequate criteria for designing the desired event-based SM estimators are derived such that the plant’s true state always resides in each sensor’s ellipsoidal region regardless of the simultaneous presence of bounded noises, mixed time delays and state-saturations. Subsequently, a recursive optimization algorithm is formulated such that the minimal ellipsoids, the estimators gains and event-triggering weighted matrices are acquired simultaneously. A verification simulation is presented to illustrate the advantages of the design approach of the developed state estimator.  相似文献   

12.
This paper tackles a distributed hybrid affine formation control (HAFC) problem for Euler–Lagrange multi-agent systems with modelling uncertainties using full-state feedback in both time-varying and constant formation cases. First, a novel two-layer framework is adopted to define the HAFC problem. Using the property of the affine transformation, we present the sufficient and necessary conditions of achieving the affine localizability. Because only parts of the leaders and followers can access to the desired formation information and states of the dynamic leaders, respectively, we design a distributed finite-time sliding-mode estimator to acquire the desired position, velocity, and acceleration of each agent. In the sequel, combined with the integral barrier Lyapunov functions, we propose a distributed formation control law for each leader in the first layer and a distributed affine formation control protocol for each follower in the second layer respectively with bounded velocities for all agents, meanwhile the adaptive neural networks are applied to compensate the model uncertainties. The uniform ultimate boundedness of all the tracking errors can be guaranteed by Lyapunov stability theory. Finally, corresponding simulations are carried out to verify the theoretical results and demonstrate that with the proposed control approach the agents can accurately and continuously track the given references.  相似文献   

13.
掌明 《科技广场》2007,(9):19-21
在分析了无线传感器网络应用和特性的基础上,论述了无线传感器网络中的网络体系结构、节点体系结构、与距离有关的节点能量计算模型、带有Flag标志和长期睡眠机制的状态转换模型,并给出了几种流行的无线传感器网络路由算法及其特点,对无线传感器网络的应用和研究有着深远的意义。  相似文献   

14.
《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   

15.
The consensus problem for networks of multiple agents consists in reaching an agreement between certain coordinates of interest using a distributed controller. It may be desirable that all the agents find a consensus at a given desired leader coordinate (Leader Follower Consensus Problem LFCP), or it may be only necessary that they agree at a certain coordinates value (Leaderless Consensus Problem LCP). Consensus has many practical applications in robot networks systems, where the interconnection of the agents may present variable time delays, hence rendering the stability analysis and control design more complex. Another problem that may arise is the possible lack of velocity measurements. In this work, a Proportional plus damping injection (P + d) controller together with a linear velocity observer is introduced. Our approach is able to solve both the LFCP and the LCP in networks of robots modeled as undirected weighted graphs with unknown asymmetric (bounded) variable time delays. Local (semi global) asymptotic stability is proven and simulation results are provided to test the performance of the proposed scheme.  相似文献   

16.
This paper is concerned with the event-based fusion estimation problem for a class of multi-rate systems (MRSs) subject to sensor degradations. The MRSs under consideration include several sensor nodes with different sampling rates. To facilitate the filter design, the MRSs are transformed into a single-rate system (SRS) by using an augmentation approach. A set of random variables obeying known probability distributions are used to characterize the phenomenon of the sensor degradations. For the purpose of saving the limited communication resources, the event-triggering mechanism (ETM) is adopted to regulate the transmission frequency of the measurements. For the addressed MRSs, we aim to design a set of event-based local filters for each sensor node such that the upper bound of each local filtering error covariance (FEC) is guaranteed and minimized by designing the filter parameter appropriately. Subsequently, the local estimates are fused with the aid of covariance intersection (CI) fusion approach. Finally, a numerical experiment is exploited to demonstrate the usefulness of the developed fusion estimation algorithm.  相似文献   

17.
In practice, it is almost impossible to directly add a controller on each node in a complex dynamical network due to the high control cost and the difficulty of practical implementation, especially for large-scale networks. In order to address this issue, a pinning control strategy is introduced as a feasible alternative. The objective of this paper is first to recall some recent advancements in global pinning synchronization of complex networks with general communication topologies. A systematic review is presented thoroughly from the following aspects, including modeling, network topologies, control methodologies, theoretical analysis methods, and pinned node selection and localization schemes (pinning strategies). Fully distributed adaptive laws are proposed subsequently for the coupling strength as well as pinning control gains, and sufficient conditions are obtained to synchronize and pin a general complex network to a preassigned trajectory. Moreover, some open problems and future works in the field are also discussed.  相似文献   

18.
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   

19.
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   

20.
This paper is concerned with the intermittent fault (IF) detection problem for a class of linear discrete-time stochastic systems over sensor networks with constant time delay. By utilizing the lifting method, the distributed decoupled observers are proposed based on the output information of neighbor nodes and the node itself. In order to detect the appearing time and disappearing time of the IF, the truncated residuals are designed by introducing a sliding-time window. Furthermore, the IF detection and location thresholds are determined based on the hypothesis testing technique and the detectability of the IF is analyzed in the framework of stochastic analysis. Finally, a simulation example is presented to illustrate the effectiveness of the derived results.  相似文献   

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