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1.
A finite-time non-fragile state estimation algorithm is discussed in this article for discrete delayed neural networks with sensor failures and randomly occurring sensor nonlinearity. First, by using augmented technology, such system is modeled as a kind of nonlinear stochastic singular delayed system. Then, a finite-time state estimator algorithm is provided to ensure that the singular error dynamic is regular, causal and stochastic finite-time stable. Moreover, the states and sensor failures can be estimated simultaneously. Next, in order to avoid the affection of estimator’s parameter perturbation, a finite-time non-fragile state estimation algorithm is given, and a simulation result demonstrates the usefulness of the proposed approach.  相似文献   

2.
This paper is devoted to solving the recursive state estimation (RSE) issue for a class of complex networks (CNs) with Round-Robin (RR) protocol and switching nonlinearities (SNs). A random variable obeying the Bernoulli distribution with known statistical properties is introduced to describe the switching phenomenon between two nonlinear functions. A Gaussian noise and time-varying outer coupling strength are adopted to show the changeable network topology (CNT). The RR protocol is applied to regulate signal transmissions, which determines that the element in measurement output has access to the communication networks at each step. The purpose of this paper is to construct a recursive state estimator such that, for all SNs, time-varying topology and RR protocol, the expected state estimation performance is guaranteed. Specifically, based on two recursive matrix equations, the covariance upper bound (CUB) of state estimation error is obtained firstly and then minimized via designing estimator gain in a proper way. Moreover, a feasible criterion is given to guarantee that the trace of obtained CUB is bounded and a monotonicity relationship is established between state estimation error and time-varying outer coupling strength. Lastly, a simulation experiment is illustrated to verify the feasibility of the addressed estimation method.  相似文献   

3.
4.
In this paper, the state estimation problem is studied for a class of discrete-time stochastic complex networks with switched topology. In the network under consideration, we assume that measurement outputs can be got from only partial nodes, besides, the switching rule of this network is characterized by a sequence of Bernoulli random variables. The aim of the presented estimation problem is to develop a recursive estimator based on the framework of extended Kalman filter (EKF), such that the upper bound for the filtering error convariance is optimized. In order to address the nonlinear functions, the Taylor series expansion is utilized and the high-order terms of linearization errors are expressed in an exact way. Furthermore, by solving two Ricatti-like difference equations, the gain matrix can be acquired at each time instant. It is shown that the filtering error is bounded in mean square under some conditions with the aid of stochastic analysis techniques. A numerical example is given to demonstrate the validity of the proposed estimator.  相似文献   

5.
This paper is devoted to the non-fragile exponential synchronization problem of complex dynamical networks with time-varying coupling delays via sampled-data static output-feedback controller involving a constant signal transmission delay. The dynamics of the nodes contain s quadratically restricted nonlinearities, and the feedback gain is allowed to have norm-bounded time-varying uncertainty. The control design is based on a Lyapunov–Krasovskii functional, which consists of the sum of terms assigned to the individual nodes, i.e., it is constructed without merging the complex dynamical network’s nodes into a single large-scale system. In this way, the proposed design method has substantially reduced computational complexity and improved conservativeness, and guaranties non-fragile exponential stability of the error system. The sufficient stability condition is expressed in terms of linear matrix inequalities that are solvable by standard tools. The efficiency of the proposed method is illustrated by numerical examples.  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.
In this paper a new integrated observer-based fault estimation and accommodation strategy for discrete-time piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and the states, a fault tolerant controller using a PWL state feedback is designed. The observer-based fault-tolerant controller is obtained by the interconnection of the estimator and the state feedback controller. We show that separate design of the state feedback and the estimator results in the stability of the overall closed-loop system. In addition, the input-to-state stability (ISS) gain for the closed-loop system is obtained and a procedure for minimizing it is given. All of the design conditions are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example.  相似文献   

8.
The issue of non-fragile controller’s designed with reachable set estimation and time-delay for multi-agent systems(MASs) is investigated in this paper. The information interaction among agents is governed by a set of switching sequence, which can be described by continue-time discrete state semi-Markov process. By tree-transformation, the MASs firstly converted into reduced-order system, and properly considered the instability of the parameters with the dynamic behavior of the controller, a non-fragile controller is designed to describe the system’s performance cope with the perturbation from the controller. The sufficient conditions are established in forms of a series of linear matrix inequalities which are based on Lyapunov-Krasovskii method, and the agent’s state of error systems is bounded by a finite closed set will be guaranteed. Finally, the availability of the derived theoretical results are verified by two numerical simulations.  相似文献   

9.
The paper proposes a decentralized state estimation method for the control of network systems, where a cooperative objective has to be achieved. The nodes of the network are partitioned into independent nodes, providing the control inputs, and dependent nodes, controlled by local interaction laws. The proposed state estimation algorithm allows the independent nodes to estimate the state of the dependent nodes in a completely decentralized way. To do that, it is necessary for each independent node of the network to estimate the control input components computed by the other independent nodes, without requiring communication among the independent nodes. The decentralized state estimator, including an input estimator, is developed and the convergence properties are studied. Simulation results show the effectiveness of the proposed approach.  相似文献   

10.
《Journal of The Franklin Institute》2022,359(18):11155-11185
Nowadays, cyber-physical systems (CPSs) have been widely used in various fields due to their powerful performance and low cost. The cyber attacks will cause security risks and even huge losses according to the universality and vulnerability of CPSs. As a typical network attack, deception attacks have the features of high concealment and strong destructiveness. Compared with the traditional deception attack models with a constant value, a deception attack with random characteristics is introduced in this paper, which is difficult to identify. In order to defend against such deception attacks and overcome energy constraints in CPSs, the secure state estimation and the event-triggered communication mechanism without feedback information are co-considered to reconcile accuracy of estimation and energy consumption. Firstly, an event-triggered augmented state estimator is proposed for secure state estimation and attack identification. Then, under the ideology of equivalence, the augmented state estimator is derived as a concise two-stage estimator with reduced order. The two-stage estimator can perform the secure state estimation and attack identification respectively. The estimators ensure the accuracy of attack identification well since not treating attack information as the trigger event. Afterward, the comparison of the computational complexity of these two algorithms is analyzed. Finally, an example of a target tracking system is supplied to prove the effectiveness and efficiency of the proposed algorithm.  相似文献   

11.
This paper is concerned with the robust state estimation problem for semi-Markovian switching complex-valued neural networks with quantization effects (QEs). The uncertain parameters are described by the linear fractional uncertainties (LFUs). To enhance the channel utilization and save the communication resources, the measured output is quantized before transmission by a logarithmic quantizer. The purpose of the problem under consideration is to design a full-order state estimator to estimate the complex-valued neuron states. Based on the Lyapunov stability theory, stochastic analysis method, and some improved integral inequalities, sufficient conditions are first derived to guarantee the estimation error system to be globally asymptotically stable in the mean square. Then, the desired state estimator can be directly designed after solving a set of matrix inequalities, which is robust against the LFUs and the QEs. In the end of the paper, one numerical example is provided to illustrate the feasibility and effectiveness of the proposed estimation design scheme.  相似文献   

12.
The consensus tacking problem for multi-agent systems with a leader of none control input and unknown control input is studied in this paper. By virtue of the relative state information of neighboring agents, state estimator and disturbance estimator are designed for each follower to estimate the system states and exogenous disturbance, respectively. Meanwhile, a novel control protocol based on two estimators is designed to make tracking error eventually converge to zero. Furthermore, the obtained results are further extended to the leader with unknown control input. A novel state estimator with adaptive time-varying gain is proposed such that consensus tracking condition is independent of the Laplacian matrix with regard to the communication topology. Finally, two examples are presented to verify the feasibility of the proposed control protocol.  相似文献   

13.
This paper proposes a novel robust non-fragile proportional plus derivative state feedback (PDSF) control scheme for a class of uncertain nonlinear singular systems. The Takagi–Sugeno (T–S) fuzzy model is employed to represent the nonlinear singular system with parameter uncertainties appearing not only in distinct state matrices, but also in distinct derivative matrices. By using the free-weighting matrix technique, some sufficient conditions, which guarantee the resulting closed-loop system to be normal and stable (NS), are presented. With these conditions, the problems of non-fragile PDSF controllers design with additive and multiplicative uncertainties are respectively solved in terms of linear matrix inequalities (LMIs), which can be conveniently solved via the convex optimization technique. Finally, two examples are provided to illustrate the validity of the presented results.  相似文献   

14.
In this paper, the secure synchronization control problem of a class of complex time-delay dynamic networks (CTDDNs) under denial of service (DoS) attacks is studied. Based on the pinning control strategy, a non-fragile sampling controller is designed for a small number of nodes in the complex network. It can effectively solve the problem of limited communication resources and has good anti-interference performance. In order to resist the influence of DoS attacks, an improved comparator algorithm is designed to obtain the specific information of DoS attacks, including the upper and lower bounds of the DoS attacks duration, the DoS attacks frequency and the specific active/sleeping interval of DoS attacks. Based on Lyapunov stability theory and by designing the pinning non-fragile sampling controller, new security synchronization criteria are established for CTDDNs. Finally, two numerical examples are given to verify the validity of the theories.  相似文献   

15.
This paper investigates the state estimation problem for networked systems with colored noises and communication constraints. The colored noises are considered to be correlated to itself at other time steps, and communication constraints include two parts: (1) the information is quantized by a logarithmic quantizer before transmission, (2) only one node can access the network channel at each instant based on a specified media access protocol. A robust recursive estimator is designed under the condition of colored noises, quantization error and partially available measurements. The upper bound of the covariance of the estimation error is then derived and minimized by properly designing estimator gains. An illustrative example is finally given to demonstrate the effectiveness of the developed estimator.  相似文献   

16.
This paper deals with the problems of non-fragile robust stochastic stabilization and robust H control for uncertain stochastic nonlinear time-delay systems. The parameter uncertainties are assumed to be time-varying norm-bounded appearing in both state and input matrices. The time-delay is unknown and time-varying with known bounds. The non-fragile robust stochastic stabilization problem is to design a memoryless non-fragile state feedback controller such that the closed-loop system is robustly stochastically stable for all admissible parameter uncertainties. The purpose of robust H control problem, in addition to robust stochastical stability requirement, is to reduce the effect of the disturbance input on the controlled output to a prescribed level. Using the Lyapunov functional method and free-weighting matrices, delay-dependent sufficient conditions for the solvability of these problems are established in terms of linear matrix inequality (LMI). Numerical example is provided to show the effectiveness of the proposed theoretical results.  相似文献   

17.
In this work, we probes the stability results of H state estimation for discrete-time stochastic genetic regulatory networks with leakage, distributed delays, Markovian jumping parameters and impulsive effects. Here, we focus to evaluate the true absorption of mRNAs and proteins by calculating the H estimator in such a way that the estimation error dynamics is stochastically stable during the completion of the prescribed H disturbance attenuation level. In favor of decreasing the data communion in trouble, the H system accept and evaluate the outputs that are only transferred to the estimator when a certain case is acroses. Further, few sufficient conditions are formulated, by utilizing the Lyapunov–Krasovskii functional under which the estimation error system is stochastically stable and also satisfied the H attainment constraint. The estimator is obtained in terms of linear matrix inequalities (LMIs) and these LMIs are attainable, only if the estimator gains can be absolutely given. In addition to that, two numerical examples are exposed to establish the efficiency of our obtained results.  相似文献   

18.
The robust fault estimation problem for linear discrete time-varying (LDTV) systems subject to multiplicative noise is investigated by means of finite impulse response (FIR) filter. A novel analytical redundancy, expressed via all states of the previous time window, is originally established to construct the fault estimator. To ensure the satisfactory fault estimation accuracy in stochastic sense under the interference of random uncertainty, a new performance index in forms of matrix trace function is proposed. An easy-to-check necessary and sufficient condition is presented to obtain the optimal filter gain via minimizing the performance index at each time instant. It is analytically demonstrated that, the newly proposed fault estimation algorithm enjoys obvious computational advantages in updating the filter gain, especially as the length of the time window increases for time-varying systems. Simulation results are finally provided to verify its feasibility and superiority.  相似文献   

19.
In this paper, the problem of finite-horizon H state estimation is investigated for a class of discrete time-varying complex networks with multiplicative noises and random coupling strengths. The network nodes and estimators are connected via a constrained communication network which allows only one node to send measurement data at each transmission instant. The Round-Robin protocol is introduced to determine which node obtains the access to the network at certain transmission instant. The aim of the addressed problem is to design a set of time-varying estimator parameters such that the prescribed H performance is guaranteed over a finite horizon. By using the stochastic analysis approach and completing-the-square method, sufficient conditions are derived for the existence of the desired estimators in terms of the solution to backward recursive Riccati difference equations. Finally, a numerical example is provided to validate the feasibility and effectiveness of the proposed results.  相似文献   

20.
In cyber-physical systems (CPS), cyber threats emerge in many ways which can cause significant destruction to the system operation. In wireless CPS, adversaries can block the communications of useful information by channel jamming, incurring the so-called denial of service (DoS) attacks. In this paper, we investigate the problem of optimal jamming attack scheduling against remote state estimation wireless network. Specifically, we consider that two wireless sensors report data to a remote estimator through two wireless communication channels lying in two unoverlapping frequency bands, respectively. Meanwhile, an adversary can select one and only one channel at a time to execute jamming attack. We prove that the optimal attack schedule is continuously launching attack on one channel determined based on the system dynamics matrix. The theoretical results are validated by numerical simulations.  相似文献   

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