Stochastic synchronization of delayed multiagent networks with intermittent communications: An impulsive framework

This paper studies the consensus problem of first-order and second-order multi-agent systems with nonlinear dynamics and quantised interactions. Continuous-time and impulsive control inputs are designed for the multi-agent systems on the logarithmic quantised relative state measurements of agents, respectively. By using nonsmooth analysis tools, we get some sufficient conditions for the consensus of multi-agent systems under the continuous-time inputs. Compared with continuous-time control inputs, impulsive distributed control inputs just use the state variables of the systems at discrete-time instances. Based on impulsive control theory, we prove that the multi-agent systems can reach consensus by choosing proper control gains and impulsive intervals. The simulation results are given to verify the effectiveness of the theoretical results.

This paper considers thep-moment boundedness of nonlinear impulsive stochastic delay differential systems (ISDDSs). Using the Lyapunov-Razumikhin method and stochastic analysis techniques, we obtain sufficient conditions which guarantee thep-moment boundedness of ISDDSs. Two cases are considered, one is that the stochastic delay differential system (SDDS) may not be bounded, and how an impulsive strategy should be taken to make the SDDS be bounded. The other is that the SDDS is bounded, and an impulsive disturbance appears in this SDDS, then what restrictions on the impulsive disturbance should be adopted to maintain the boundedness of the SDDS. Our results provide sufficient criteria for these two cases. At last, two examples are given to illustrate the correctness of our results.

In this paper, a class of large-scale systems with impulsive effect, input disturbance, and both variable and unbounded delays were investigated. On the assumption that all subsystems of the large-scale system can be exponentially stabilized, and the stabilizing feedbacks and corresponding Lyapunov functions (LFs) for the closed-loop systems are available, using the idea of vector Lyapunov method and M-matrix property, the intero-differential inequalities with variable and unbounded delays were constructed. By the stability analysis of the intero-differential inequalities, the sufficient conditions to ensure the robust exponential stability of the large-scale system were obtained. Finally, the correctness and validity of the methods was verified by two numerical examples.

In this paper we analyze stochastic synchronization of coupled chaotic maps over blinking networks composed of a pristine static network and stochastic on-off couplings between any pair of nodes. We focus on mean square linear stability of the synchronized state by analyzing the time evolution of the second moment of the variation transverse to the synchronization manifold. By projecting the variational equations on the eigenvectors of a higher order state matrix describing this variational dynamics, we establish a necessary and sufficient condition for stochastic synchronization based on the largest Lyapunov exponent of the map and the spectral radius of such matrix. This condition is further simplified by computing closed-form results for the spectral properties of the moments of the graph Laplacian associated to the intermittent coupling and using classical eigenvalue bounds. We illustrate the main results through simulations on synchronization of chaotic Henon maps.

In this paper, the issue on impulsive control and synchronization of nonlinear system with impulse time window are investigated. The considered impulsive effects can be stochastically occurred at a determined time window. Hence, the impulses here can be more general and more applicable than the fixed impulses. Some novel and easy-to-check criteria with impulse time window are obtained to guarantee the impulsive control and synchronization global asymptotical stable. Especially, on the basis of the our analysis, we only choose an efficient impulse time window instead of choosing fixed-impulse sequences. Finally, the simulation results further demonstrate the effectiveness of our theoretical results.

In this paper, the finite-time stochastic outer synchronization between two different complex dynamical networks with noise perturbation is investigated. By using suitable controllers, sufficient conditions for finite-time stochastic outer synchronization are derived based on the finite-time stability theory of stochastic differential equations. It is noticed that the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results. The effect of control parameters on the settling time is also numerically demonstrated.

The effect of impulse on stability of neural network is evident not only in performance, that is, impulsive control and impulsive interference. The amount of impulse has a certain impact on stability of neural network. Unlike traditional average impulsive interval, a new strategy is applied in this paper, namely, impulsive density. Based on this strategy, by constructing Lyapunov function, we establish sufficient conditions for mean square asymptotical stability of impulsive stochastic time-varying neural network without time delay. As well as, under this strategy and uniformly asymptotically stable function, by combining trajectory based approach and improved Razumikhin method, mean square exponential stability criterion of impulsive stochastic time-varying neural network with time delay is established. Finally, to demonstrate the viability of our theoretical findings, some instances are provided.

This article addresses the issue of drive–response synchronization in fractional-order multi-link memristive neural networks (FMMNN) with multiple delays, under hybrid impulsive feedback control. To address the impact of multiple delays on system synchronization, an extended fractional-order delayed comparison principle incorporating impulses is established. By leveraging Laplace transform, Mittag–Leffler functions, the generalized comparison principle, and hybrid impulsive feedback control schemes, several new sufficient conditions are derived to ensure synchronization in the addressed FMMNN. Unlike existing studies on fractional-order single-link memristor-based systems, our response network is a multi-link model that considers impulsive effects. Notably, the impulsive gains αi are not limited to a small interval, thus expanding the application range of our approach (αi∈(−2,0)∪(−∞,−2)∪(0,+∞)). This feature allows one to choose impulsive gains and corresponding impulsive intervals that are appropriate for the system environment and control requirements. The theoretical results obtained in this study contribute to expanding the relevant theoretical achievements of fractional-order neural networks incorporating memristive characteristics.

Large umbrella space antennas are essential for communication, monitoring and observation of Earth and space objects. Despite investigations devoted to space antenna dynamics, the disturbance impulse shape effect on the root mean square error of spacecraft antenna reflecting surface has not been studied. This paper overcomes this gap describing disturbance impulse impact on root mean square error of spacecraft antenna reflecting surface relative to paraboloid via nonlinear finite element method. Based on numerical results root mean square dependency on disturbance time for rectangular and sine impulses was calculated. This approach could be applied in studying antenna reflecting surface response on disturbance impulse for different types of perspective large space antennas.

Impulsive control for T–S fuzzy model-based chaotic systems

In this paper, we consider the coordination problem of double integrator dynamics under the assumption of intermittent communication between agents in the presence of time-varying communication delays. More precisely, we consider the containment control problem with multiple dynamic leaders under a directed interconnection graph topology. We present distributed control algorithms, in the full and partial state feedback cases, where the communication between agents is performed only at some discrete instants of time in the presence of irregular communication delays and packet dropouts. It is shown that the proposed approach leads to our control objectives under sufficient conditions that relate the characteristics of the communication process and the control gains. The effectiveness of the proposed control schemes is illustrated through numerical examples.

Dynamic analysis of pest control model with population dispersal in two patches and impulsive effect

In this paper, synchronization of coupled neural networks is investigated via distributed delayed impulsive control, and system delays, coupling delays and impulsive delays are simultaneously considered. Firstly, the concept of average delayed impulsive weight is proposed, which allows impulsive weights and impulsive delays to be integrated into just one expression, and afterward hybrid impulses can be augmented. Then, this paper extends the comparison principle by taking delayed impulses into account, where the limitation that system delays exist between two consecutive impulsive instants is released. Without any restriction on time delays, sufficient conditions of global exponential synchronization for coupled neural networks are obtained. Additionally, the corresponding convergence rate is estimated. It indicates that the networks can still achieve synchronization even if the impulses work negatively, or may destroy synchronization. Finally, three typical networks are investigated to verify the availability of the control schemes.

This article investigates the set stabilization of impulsive Boolean control networks (IBCNs) by sampled-data state feedback control based on a hybrid index model. It is worth mentioning that the 2-D index model has the ability to characterize the instantaneousness of ideal impulses and describe complicated impulsive behaviors. To avoid Zeno phenomenon, the judging conditions for forward completeness are derived. Subsequently, an algorithm is designed to obtain the largest sampled point control invariant set (SPCIS) of a given set in the hybrid domain, and its validity is further authenticated. Accordingly, a necessary and sufficient condition is derived for the set stabilization of IBCNs in the hybrid domain, and all time-optimal sampled-data state feedback controllers are designed. The similar results are also obtained for IBCNs in the time domain. Compared with set stabilization in the time domain, set stabilization in the hybrid domain not only focuses on the dynamics at each time instant but also concerns every jumping state. It results in that every SPCIS in the hybrid domain is a subset of a certain SPCIS in the time domain. Eventually, the λ switch with impulsive disturbances is modeled as a reduced IBCN, which is presented to demonstrate the obtained results.

It is a need of time to use hybrid approach (biological and chemical) to control agriculture pests effectively, economically and safely. Most of the pests and natural enemies in their life history goes through two stages namely immature larva and mature adult. From this biological point of view, we purpose a pest control model with stage structuring in pests and natural enemies in the presence of impulsively released natural enemy and chemical pesticides. Using Floquet theory and small ampli- tude perturbation technique, the local stability of periodic solutions are discussed. The suffcient conditions for the global attractively of pest- extinction periodic solution and permanence of the system are obtained by using comparison technique of differential equations with impulsive effect. At last an extensive simulation is done to verify the theoretical ndings and to see the rich dynamical behavior of the system.