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1.
This paper introduces the Lebesgue sampling approach to the robust stabilization of Boolean control networks (BCNs) with external disturbances. Given a Lebesgue sampling region and a feedback control, a time aggregated system is obtained via the semi-tensor product method. Then, a new criterion is presented for the robust stabilization of time aggregated system. Furthermore, given a signal of Lebesgue sampling, a sequence of the Lebesgue type robust reachable sets is constructed. Based on these reachable sets, several algorithms are presented to design both Lebesgue sampling region and sampled-data state feedback control for the robust stabilization of BCNs.  相似文献   

2.
This paper investigates the stability and stabilizability of complex-valued memristive neural networks (CVMNNs) with random time-varying delays via non-fragile sampled-data control. Taking the influence of gain fluctuations into account, a non-fragile sampled-data controller is designed for CVMNNs. Compared with the existing control schemes, the one here is more applicable and can effectively save the communication resources. The assumption on activation functions of CVMNNs is relaxed by only needing the complex-valued activation functions satisfying the Lipschitz condition. By constructing a suitable Lyapunov–Krasovskii functional (LKF), new stability and stabilizability criteria are derived for CVMNNs. Different from the existing results with the maximum absolute values of memristive connection weights, our ones are based on the average values of the maximum and minimum of the memristive connection weights. Finally, numerical simulations are given to validate the effectiveness of the theoretical results.  相似文献   

3.
Set stabilization of probabilistic Boolean control networks (PBCNs) is investigated in this paper and some interesting results are derived. The main results consist of three parts. (1) A definition of set stabilizability with probability one by closed-loop control is proposed for PBCNs, which is not a natural extension from deterministic Boolean control networks to PBCNs due to the random feature of PBCNs. (2) A necessary and sufficient set stabilizability condition is provided for PBCNs. (3) An algorithm for designing a state feedback controller is developed. It is guaranteed that all designed controllers can stabilize a PBCN to a given subset with probability one. The design method is constructive, so it is convenient to use this method in practical application. The results derived above are fundamental and important, since based on them many problems about PBCNs can be solved, for example partial stabilization, synchronization, and so on. Finally, a practical example is employed to show the effectiveness of our results.  相似文献   

4.
This paper investigates secure bipartite consensus tracking of linear multi-agent systems under denial-of-service(DoS) attacks by using event-triggered control mechanism with data sampling. Both bipartite leader-following and containment tracking consensus are considered in this paper. The event-triggered control protocol using sampled-data information is designed to save limited resources. The communication channels are interrupted by intermittent DoS attacks. Sufficient conditions on the sampling periods, attack frequency and attack duration are obtained to ensure secure bipartite tracking consensus of the multi-agent systems. Finally, simulation example is provided to illustrate the effectiveness of the theoretical results.  相似文献   

5.
《Journal of The Franklin Institute》2022,359(18):11108-11134
This paper focuses on the stochastic passivity problem of stochastic memristor-based complex valued neural networks with two different types of time-delays and reaction-diffusion terms by sampled-data control strategy. Different from the existing sampled-data strategies, this paper develops spatial and temporal point sampling, namely, only a finite number of points in space or time are sampled. By introducing two different Lyapunov functional and employing techniques such as Wirtinger’s integral inequality, Jensen’s inequality and Young’s inequality, etc., two different sufficient conditions for the stochastic passivity of the system are established. Prominently, the condition quantitatively reveals the relationship between the upper and lower bounds of the sampling interval at spatial and temporal points. Finally, a numerical example is given to verify the rationality of the proposed method. Notice, compared with a large number of results of real-valued reaction-diffusion neural networks, the research results of sampled-data controlled complex-valued reaction-diffusion neural networks have not appeared so far, and this work is the first attempt to fill in the gaps in this topic.  相似文献   

6.
This paper investigates the problem of stabilization for fuzzy sampled-data systems with variable sampling. A novel Lyapunov–Krasovskii functional (LKF) is introduced to the fuzzy systems. The benefit of the new approach is that the LKF develops more information about actual sampling pattern of the fuzzy sampled-data systems. In addition, some symmetric matrices involved in the LKF are not required to be positive definite. Based on a recently introduced Wirtinger-based integral inequality that has been shown to be less conservative than Jensen’s inequality, much less conservative stabilization conditions are obtained. Then, the corresponding sampled-data controller can be synthesized by solving a set of linear matrix inequalities (LMIs). Finally, an illustrative example is given to show the feasibility and effectiveness of the proposed method.  相似文献   

7.
In this paper, the exponential stability of delayed neural networks (DNNs) with delayed sampled-data inputs is investigated via extended bilateral looped functional approach. Firstly, a new extended bilateral looped functional is constructed, which is differentiable at sampling intervals and can relax the constraints on positive definiteness when compared to traditional functionals. Then, less conservative criteria for exponential stability of DNNs with delayed sampled-data inputs expressed through linear matrix inequalities (LMIs) are obtained. Furthermore, the results are extended to T–S fuzzy DNNs with delayed sampled-data inputs, where corresponding stability conditions are likewise derived. Finally, two simulation examples are given to illustrate the validity of the main results.  相似文献   

8.
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9.
In this work, a sampled-data control problem for neural-network-based systems with an optimal guaranteed cost is investigated. By constructing suitable time-dependent functionals and utilizing an improved free-matrix-based integral inequality, a sampled-data stability criterion for neural-network-based systems is derived. Based on a first result, a sampled-data controller design method for neural-network-based systems that meets the maximum sampling period and minimum guaranteed cost performance is proposed. The superiority and validity of the results will be verified by comparing with the existing results in a numerical example.  相似文献   

10.
《Journal of The Franklin Institute》2023,360(13):10365-10385
This paper investigates a spatiotemporal sampled-data fuzzy control strategy for switched singularly perturbed partial differential equation (PDE) systems, where the systems’ operation modes obey average dwell-time switching mechanism. To efficiently deal with nonlinear terms and guarantee the system stability for the considered systems, a spatiotemporal sampled-data fuzzy control scheme is developed. Furthermore, based on the fact that mode mismatch phenomena during switching and sampling, through formulating novel Lyapunov functionals (LFs) with the discontinuous terms and mode-dependent two-sided looped-functionals, which can fully utilize the state information of the sampling period, a new exponential stability criterion is provided for the target systems. Finally, an example is provided to prove the validity of the proposed control approach.  相似文献   

11.
This paper studies the extended dissipativity (ED) issue for T-S fuzzy systems (TSFSs) via reliable memory control scheme and aperiodic sampled-data (ASD) method. First, considering the random variation of sampling interval and the time delays (TDs) of sampling signal transmission in the communication network, a reliable aperiodic memory sampled-data control (RAMSDC) strategy is proposed. Then, the developed delay-dependent Lyapunov-Krasovskii functional (LKF) with some two-sided looped-functional (TSLF) terms is constructed to fully utilize sampled state information. The introduced free matrices in the TSLF need not to be positive definite, which reduces the conservativeness of the obtained results. Next, a sufficient condition is given to ensure the ED, and the controller gain matrix is obtained by means of linear matrix inequality (LMI) technique. At last, the effectiveness of theoretical results in practical application is verified by the use of a truck-trailer model.  相似文献   

12.
The synchronization for a class of switched uncertain neural networks (NNs) with mixed delays and sampled-data control is researched in this paper. When a switching signal occurs in a sampling interval, the controller cannot switch until the next sampling instant. There is a mismatch between the system and the controller. Thus, we devise the control strategy to guarantee that the switched NNs can be synchronized. The proposed Lyapunov-Krasovskii functional (LKF) can make full use of system information. By use of an improved integral inequality, some sufficient stability conditions formed by linear matrix inequalities (LMIs) are derived for the synchronization of switched NNs. Average dwell time (ADT) is obtained as a form of inequality that includes the sampling interval. At last, the feasibility of the proposed method is proved by some numerical examples.  相似文献   

13.
This paper is concerned with master-slave synchronization for chaotic Lur'e systems subject to aperiodic sampled-data. To reduce the communication burden, an aperiodic event-triggered (APET) transmission scheme is introduced to determine the transmission of the latest sampling synchronization data. In order to reduce the design conservatism, a novel time-dependent Lyapunov functional (TDLF) is constructed to fully use the characteristics about sampling behavior, triggering error, and nonlinear part of the system, simultaneously. A more relaxed constraint criterion is then presented to ensure the positivity of the whole functional between two sampling instants. By partially resorting to the TDLF, the APET-based synchronization criterion depending on the upper and lower bounds of the uncertain sampling period is presented. The synchronization criterion based on aperiodic-sampling mechanism is also provided. Finally, a typical example about neural networks is offered to illustrate the benefit and validity of obtained synchronization methodologies.  相似文献   

14.
This article investigates the defense control problem for sampled-data Takagi-Sugeno (T-S) fuzzy systems with multiple transmission channels against asynchronous denial-of-service (DoS) attacks. Firstly, a new switching security control method is proposed to tolerate the asynchronous DoS attacks that act independently on each channel. Then, based on switching strategy, the resulting augmented sampled-data system can be converted into new switched systems including several stable subsystems and one open-loop subsystem. Besides, by applying the piecewise Lyapunov-Krasovskii (L-K) function method, membership functions (MFs) dependent sufficient conditions are derived to ensure the exponential stability of newly constructed switching systems. Moreover, quantitative relations among the sampling period, the exponential decay rate, and the rate of all channels being fully attacked and not being completely attacked are established. Finally, simulation examples show the effectiveness of the developed defense control approach.  相似文献   

15.
This paper studies the global sampled-data output feedback stabilization problem for a class of stochastic nonlinear systems. The considered system is in non-strict feedback form with unknown time-varying delay. A state observer is introduced to estimate the unmeasured states. With the help of the backstepping method, a linear sampled-data output feedback controller is constructed. By choosing an appropriate Lyapunov–Krasoviskii functional and an allowable sampling period, it is shown that the stochastic system can be globally asymptotically stabilized in the mean square sense under the developed control scheme. Finally, two examples are presented to verify the effectiveness of the designed control scheme.  相似文献   

16.
This paper studies the leader–follower consensus problem of second-order multi-agent dynamical systems with fixed and stochastic switching topologies in a sampled-data setting. A distributed linear consensus protocol is designed to track an active leader, where the current position information of neighbor agents and self-velocity data are utilized. A necessary and sufficient condition is established under fixed and directed topology for reaching consensus, which depends on the sampling period and control gain parameters. A sufficient condition is obtained under the Markov switching topology case. Finally, some numerical simulations are provided to verify the effectiveness of the theoretical results.  相似文献   

17.
This paper addresses the design of a sampled-data model predictive control (MPC) strategy for linear parameter-varying (LPV) systems. A continuous-time prediction model, which takes into account that the samples are not necessarily periodic and that plant parameters vary continuously with time, is considered. Moreover, it is explicitly assumed that the value of the parameters used to compute the optimal control sequence is measured only at the sampling instants. The MPC approach proposed by Kothare et al. [1], where the basic idea consists in solving an infinite horizon guaranteed cost control problem at each sampling time using linear matrix inequalities (LMI) based formulations, is adopted. In this context, conditions for computing a sampled-data stabilizing LPV control law that provides a guaranteed cost for a quadratic performance criterion under input saturation are derived. These conditions are obtained from a parameter-dependent looped-functional and a parameter-dependent generalized sector condition. A strategy that consists in solving convex optimization problems in a receding horizon policy is therefore proposed. It is shown that the proposed strategy guarantees the feasibility of the optimization problem at each step and leads to the asymptotic stability of the origin. The conservatism reduction provided by the proposed results, with respect to similar ones in the literature, is illustrated through numerical examples.  相似文献   

18.
Sampled-data control for time-delay systems   总被引：1，自引：0，他引：1  
The sampled-data systems are hybrid ones involving continuous time and discrete time signals, which makes the traditional analysis and synthesis methodologies of time-delay systems unable to be directly used in the cases of hybrid systems with time-delay. The primary disadvantages of current design techniques of sampled-data control are their inabilities to deal effectively with time-delay and the model uncertainty. In this paper, we generalized the analysis methodology of time-delay systems to that of the hybrid systems with time-delay and uncertainty, which developed a design procedure of sampled-data control for time-delay systems. Asymptotic stability of the time-delay hybrid systems was developed. The time-delay dependent robust sampled-data control for the time-varying delay of an uncertain linear system was then discussed. The results were described as linear matrix inequalities, which can be solved using newly released LMITool.  相似文献   

19.
Sampled-data control as an effective mean of digital control has shown its prominent superiority in most practical industries and a zero-order holder (ZOH) is often introduced to maintain continuity of control in the field of sampled-data control system. However, it decreases the control accuracy in a certain extent since the state will be held invariably within each sampling interval. In order to improve the control accuracy, this paper proposes a dynamic model-based control strategy instead of ZOH for a class of switched sampled-data control systems. The model, which is built by abstracting the plant knowledge, is located at the controller side. The controller is set up based on the model state and it provides control input to the switched system. A fixed sampling period is adopted, under which a hybrid-dwell time switching condition is revealed by taking into account asynchronous switching. With reasonable design of switching condition, exponential stability of the closed-loop system can be guaranteed. Finally, advantages of our proposed method are presented through a numerical example by comparing with the result of ZOH-based control.  相似文献   

20.
In this paper, several resultful control schemes based on data quantization are proposed for complex-valued memristive neural networks (CVMNNs). Firstly, considering the finite communication resources and the interference of failures to the system, a state quantized sampled-data controller (SQSDC) is designed for CVMNNs. Next, taking the interference of gain fluctuations into account, a non-fragile sampled-data control (SDC) law is proposed for CVMNNs in the framework of data quantification. In order to full capture more inner sampling information, a newly Lyapunov-Krasovskii function (LKF) is constructed on the basis of the proposed triple integral inequality. After that, in the framework of taking full advantage of the property of Bessel-Legendre inequality, a time-dependent discontinuous LKF (TDDLKF) is proposed for CVMNNs with SQSDC. Based on the useful LKF, several stability criteria are established. Finally, the numerical simulations are provided to substantiate the validity and less conservatism of the proposed schemes.  相似文献   

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