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1.
Finite-time control for periodic systems with sensor nonlinearities and random input gains is addressed in this work. The variation of sensor nonlinearities is modeled by a Markov chain, and a stochastic variable is used to describe the influence of the actuator. A mode- and sensor nonlinearity-dependent non-fragile controller is designed to improve the performance and the non-fragility of the controller. The finite-time boundedness of the closed-loop system is ensured by a sufficient condition, the corresponding controller is then designed. Finally, the effectiveness of the developed results is illustrated by a numerical example.  相似文献   

2.
《Journal of The Franklin Institute》2021,358(18):10193-10212
In this paper, the non-fragile state estimation problem is investigated for a class of continuous-time delayed complex networks. In the addressed complex network model, the outputs only from partial network nodes are used to fulfill the state estimation task. For improving the efficiency of resource utilization, a dynamic event-triggering mechanism is applied in the design of estimator, where an auxiliary time-varying parameter is introduced to dynamically modulate the triggering condition. Our intention is to obtain the gain parameters of the desired non-fragile state estimator, which can tolerate the norm-bounded gain perturbation. In virtue of a novel Lyapunov functional and matrix inequality technique, sufficient conditions are provided to ensure robustly exponential boundedness for estimation error dynamics, and gain matrices of the estimator are computed based on certain matrix inequalities. An illustrative simulation is presented to show the validity of the non-fragile estimator proposed.  相似文献   

3.
This paper studies the asynchronous state fusion estimation problem for multi-sensor networked systems subject to stochastic data packet dropouts. A set of Bernoulli sequences are adopted to describe the random packet losses with different arriving probabilities for different sensor communication channels. The asynchronous sensors considered in this paper can have arbitrary sampling rates and arbitrary initial sampling instants, and may even sample the system non-uniformly. Asynchronous measurements collected within the fusion interval are transformed to the fusion time instant as a combined equivalent measurement. An optimal asynchronous estimation fusion algorithm is then derived based on the transformed equivalent measurement using the recursive form of linear minimum mean squared error (LMMSE) estimator. Cross-correlations between involved random variables are carefully calculated with the stochastic data packet dropouts taken into account. A numerical target tracking example is provided to illustrate the feasibility and effectiveness of the proposed algorithm.  相似文献   

4.
《Journal of The Franklin Institute》2022,359(18):10726-10740
In this paper, the secure transmission issue of a remote estimation sensor network against eavesdropping is studied. A powerful eavesdropper overhears the measurement data sent through the communication channels between the sensors and the remote estimator, and estimates system state illegally, which threatens the system information security. Different from the existing anti-eavesdropping design approaches, a stealthy artificial noise (AN) strategy is proposed to prevent eavesdroppers from deciphering encryption policy by hiding the encryption process from eavesdroppers. It has the same dynamical process with each sensor’s measurement to guarantee that the estimation error of the eavesdropper is unbounded while its observation residual variance keeps in certain bound and converges to 0, and further ensure system security without alerting the eavesdropper. It is proved that the strategy is feasible whenever the eavesdropper starts to wiretap. The selection of sensors that needs to be encrypted is further given by solving an optimization problem. The effectiveness of the proposed algorithm is verified by two simulation examples.  相似文献   

5.
This paper explores the finite-time bounded issue for discrete-time singular time-varying delay system via sliding mode control method. A suitable discrete-time sliding mode control law is constructed to drive the state trajectories onto the specified sliding surface in a given finite time interval. Meanwhile, sufficient conditions for finite-time bounded to the closed-loop delayed system are provided in both reaching phase and sliding motion phase. In addition, the finite-time sliding mode controller gain matrix can be solved by using the linear matrix inequalities approach. Finally, three numerical examples are illustrated to demonstrate the superiority and practicability of presented results.  相似文献   

6.
This study considers state and fault estimation for a switched system with a dual noise term. A zonotopic and Gaussian Kalman filter for state estimation is designed to obtain state estimation interval in the presence of both stochastic and unknown but bounded (UBB) uncertainties. The switching state and fault state of the system are distinguished by detecting whether the system measurement date is within the bounds of its predicted output. Once the switched time is detected in the system, the filter zonotopic and Gaussian Kalman functions are initialized. Once the fault time is detected, a zonotopic and Gaussian Kalman filter-based fault estimator is constructed to estimate the corresponding faults. Finally, a numerical simulation is presented to demonstrate the accuracy and effectiveness of the proposed algorithm.  相似文献   

7.
This paper investigates the distributed state estimation problem for a linear time-invariant system characterized by fading measurements and random link failures. We assume that the fading effect of the measurements occurs slowly. Additionally, communication failures between sensors can affect the state estimation performance. To this end, we propose a Kalman filtering algorithm composed of a structural data fusion stage and a signal date fusion stage. The number of communications can be decreased by executing signal data fusion when a global estimate is required. Then, we investigate the stability conditions for the proposed distributed approach. Furthermore, we analyze the mismatch between the estimation generated by the proposed distributed algorithm and that obtained by the centralized Kalman filter. Lastly, numerical results verify the feasibility of the proposed distributed method.  相似文献   

8.
This paper proposes a design framework of sensor communication by using the stochastic event triggers, which aims at best saving the communication resources. The system to be considered is as follows: a sensor takes measurements of the states of a dynamic process and sends the information to a remote estimator, and the estimator computes the state estimates for the dynamic process. To save communication resources, a set of stochastic event triggers on the measurements are assigned to the sensor. At each sampled time, when no trigger is triggered, the sensor sends nothing to the estimator; when one of them is triggered, the sensor sends the identity code of the corresponding trigger. It is shown that once the estimator receives the identity of the trigger, it is equivalent for the estimator to receiving a measurement from a certain virtual sensor. Based on it, the system performance under the proposed communication is analyzed, and the design of specific models is considered. Examples are presented to demonstrate the proposed communication design.  相似文献   

9.
This paper investigates the finite-time control problems for a class of discrete-time nonlinear singular systems via state undecomposed method. Firstly, the finite-time stabilization problem is discussed for the system under state feedback, and a finite-time stabilization controller is obtained. Then, based on which, the finite-time H boundedness problem is studied for the system with exogenous disturbances. Finally, an example of population distribution model is presented to illustrate the validity of the proposed controller. Because there is no any constraint for singular matrix E in the paper, controllers can be designed for more discrete-time nonlinear singular systems.  相似文献   

10.
In a multimodal, system, the growth in the number of possible modal paths makes state estimation difficult. Practical algorithms bound complexity by merging estimates that are conditioned on different modal path fragments. Commonly, the weight given to these local estimates is inversely related to the normalized magnitude of the residuals generated by each local filter. This paper presents a novel dual-sensor estimator that uses a merging formula that is based upon a different function of the residuals. Its performance is contrasted with an estimator using a single sensor and with another dual-sensor algorithm that requires fewer on-line calculations.  相似文献   

11.
This paper considers the sliding mode control (SMC) problem of a class of uncertain Markovian jump systems, in which there exist randomly occurring parameter uncertainties and random gain variations in the controller. By introducing two independent random variables obeying Bernoulli distribution, the random characteristics of parameter uncertainties and controller gain variations are described. A mode-dependent sliding surface is constructed, and then, the non-fragile SMC scheme is synthesized such that the specified sliding surface is reached in finite time. Furthermore, the stochastic finite-time boundedness over both the reaching and sliding stages are ensured simultaneously under some sufficient conditions. Finally, the developed non-fragile SMC approach is verified by a practical example.  相似文献   

12.
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   

13.
A new solution of networked control systems with bandwidth constraints is proposed in this paper. First, at the smart sensor side, a new stochastic communication logic scheduling strategy is designed based on a Poisson Process with time-dependent intensity. Under this strategy, the system only needs a finite-time state update. Hence the quantity of transmission of message is reduced. With the proof that the stochastic communication logic is essentially a Markov chain, the NCS is modeled as a jump system and the necessary and sufficient condition of stability for the state feedback system is presented as well. With the proposed stochastic communication logic, based on the update time, the controller is given in terms of a LMI. The simulation result shows that the scheduling strategy can decrease the network traffic, while the controller can guarantee certain good system performance.  相似文献   

14.
15.
《Journal of The Franklin Institute》2021,358(18):10095-10120
This paper addresses the H finite-time asynchronous state estimation issue for Markov jump systems with partial transition probabilities. A hidden-Markov-chain-based redundant channel model (HMCb-RCM) is established to reflect a more practical situation. Based on the output of the HMCb-RCM, firstly an asynchronous full-order state estimator is devised for the jump system with partial transition probabilities. Then, new sufficient criteria are derived such that the state estimation error is H stochastically finite-time bounded. The relationship between the partial transition probabilities and asynchronous modes is revealed as few attempts. The conditional transition probability matrix (CTPM) for the HMCb-RCM is not fixed but designable accordingly; a co-design strategy is newly developed to synthesize the CTPM and the state estimator simultaneously, which produces less conservatism than that with fixed CTPM. Finally, the theoretical results are applied to a one-link robotic manipulator to validate the proposed results.  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.
This paper studies the finite-time stability and stabilization of linear discrete time-varying stochastic systems with multiplicative noise. Firstly, necessary and sufficient conditions for the finite-time stability are presented via a state transition matrix approach. Secondly, this paper also develops the Lyapunov function method to study the finite-time stability and stabilization of discrete time-varying stochastic systems based on matrix inequalities and linear matrix inequalities (LMIs) so as to Matlab LMI Toolbox can be used.The state transition matrix-based approach to study the finite-time stability of linear discrete time-varying stochastic systems is novel, and its advantage is that the state transition matrix can make full use of the system parameter informations, which can lead to less conservative results. We also use the Lyapunov function method to discuss the finite-time stability and stabilization, which is convenient to be used in practical computations. Finally, three numerical examples are given to illustrate the effectiveness of the proposed results.  相似文献   

18.
Unpredictable packet loss that occurs in the channel connecting a local sensor and a remote estimator will deteriorate the performance of state estimation. To relieve this detrimental impact, an online linear temporal coding scheme is studied in this paper. If the packet of the last step is lost, a linear combination of the current and the last measurements with proper weights is transmitted; otherwise, only the current data is sent. By virtue of the innovation sequence approach, a linear minimum mean-squared error estimation algorithm is designed. To optimize performance, a novel estimator is also proposed which provides a recursive expression of the error covariances. The proposed two algorithms are proved to be equivalent via a set of transformations. With the aid of some optimization techniques, a recursive algorithm is presented to obtain the optimal coding weight in terms of minimizing the average estimation error covariance.  相似文献   

19.
We consider a remote state estimation process under an active eavesdropper for cyber-physical system. A smart sensor transmits its local state estimates to a remote estimator over an unreliable network, which is eavesdropped by an adversary. The intelligent adversary can work in passive eavesdropping mode and active jamming mode. An active jamming mode enables the adversary to interfere the data transmission from sensor to estimator, and meanwhile improve the data reception of itself. To protect the transmission data from being wiretapped, the sensor with two antennas injects noise to the eavesdropping link with different power levels. Aiming at minimizing the estimation error covariance and power cost of themselves while maximizing the estimation error covariance of their opponents, a two-player nonzero-sum game is constructed for sensor and active eavesdropper. For an open-loop case, the mixed Nash equilibrium is obtained by solving an one-stage nonzero-sum game. For a long term consideration, a Markov stochastic game is introduced and a Nash Q-learning method is given to find the Nash equilibrium strategies for two players. Numerical results are provided to show the effectiveness of our theoretical conclusions.  相似文献   

20.
This article proposes a sliding mode control strategy for hyperbolic PDE systems under the requirement of finite-time boundedness. First, the singular perturbation theory is introduced to model multi-time scales phenomena, and a quantized measurement method is employed to save the communication resources in network. In addition, by considering the effect of the singular perturbation phenomenon in PDE systems, a sliding surface dependent on spatial position and singular perturbation parameter is constructed, then a sliding mode control law is developed to drive state trajectories to the designed sliding surface in finite time. Moreover, a partitioning strategy is introduced to ensure that the system is finite-time bounded in the reaching phase and the sliding motion phase, respectively. Finally, some sufficient conditions are given to ensure that the system is finite-time bounded in both reaching phase and sliding motion phase, and a simulation example of the chemical tubular reactor demonstrates the effectiveness of the proposed method.  相似文献   

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