Consensus of multiple autonomous underwater vehicles with double independent Markovian switching topologies and timevarying delays

A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles（multi-AUVs） with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated.This is accomplished by first dividing the communication topology into two different switching parts,i.e.,velocity and position,to reduce the data capacity per data package sent between the multi-AUVs in the ocean.Then,the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model.Consequently,coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies.Considering these factors,sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov-Krasovskii theorem.Finally,simulation results that validate the theoretical results are presented.

SYNCHRONIZATION OF MASTER-SLAVE MARKOVIAN SWITCHING COMPLEX DYNAMICAL NETWORKS WITH TIME-VARYING DELAYS IN NONLINEAR FUNCTION VIA SLIDING MODE CONTROL

In this article, a synchronization problem for master-slave Markovian switching complex dynamical networks with time-varying delays in nonlinear function via sliding mode control is investigated. On the basis of the appropriate Lyapunov-Krasovskii functional, introducing some free weighting matrices, new synchronization criteria are derived in terms of linear matrix inequalities （LMIs）. Then, an integral sliding surface is designed to guarantee synchronization of master-slave Markovian switching complex dynamical networks, and the suitable controller is synthesized to ensure that the trajectory of the closed-loop error system can be driven onto the prescribed sliding mode surface. By using Dynkin＇s formula, we established the stochastic stablity of master-slave system. Finally, numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.

Finite-time stability and stabilization of Markovian switching stochastic systems with impulsive effects

Many practical systems in physics, biology, engineer- ing and information science exhibit impulsive dynamical behaviors due to abrupt changes at certain instants during the dynami- cal processes. The problems of finite-time stab!lity analysis are investigated for a class of Markovian switching stochastic sys- tems, in which exist impulses at the switching instants. Multiple Lyapunov techniques are used to derive sufficient conditions for finite-time stochastic stability of the overall system. Furthermore, a state feedback controller, which stabilizes the closed loop sys- tems in the finite-time sense, is then addressed. Moreover, the controller appears not only in the shift part but also in the diffu- sion part of the underlying stochastic subsystem. The results are reduced to feasibility problems involving linear matrix inequalities （LMIs）. A numerical example is presented to illustrate the proposed methodology.

Lyapunov-Based Output Containment Control of Heterogeneous Multi-Agent Systems With Markovian Switching Topologies and Distributed Delays

This paper considers the mean square output containment control problem for heterogeneous multi-agent systems(MASs)with randomly switching topologies and nonuniform distributed delays.By modeling the switching topologies as a continuous-time Markov process and taking the distributed delays into consideration,a novel distributed containment observer is proposed to estimate the convex hull spanned by the leaders'states.A novel distributed output feedback containment controller is then designed without using the prior knowledge of distributed delays.By constructing a novel switching Lyapunov functional,the output containment control problem is then solved in the sense of mean square under an easily-verifiable sufficient condition.Finally,two numerical examples are given to show the effectiveness of the proposed controller.

Coupling for Markovian switching jump-diffusions

This work is concerned with coupling for a class of Markovian switching jump-diffusion processes.The processes under consideration can be regarded as a number of jump-diffusion processes modulated by a Markovian switching device.For this class of processes,we construct a successful coupling and an order-preserving coupling.

HARNACK TYPE INEQUALITIES FOR SDES DRIVEN BY FRACTIONAL BROWNIAN MOTION WITH MARKOVIAN SWITCHING

In this paper, by constructing a coupling equation, we establish the Harnack type inequalities for stochastic differential equations driven by fractional Brownian motion with Markovian switching. The Hurst parameter H is supposed to be in(1/2, 1). As a direct application, the strong Feller property is presented.

Delay-dependent robust stability of stochastic delay systems with Markovian switching

In recent years, the stability of hybrid stochastic delay systems, one of the important issues in the study of stochastic systems, has received considerable attention. However, the existing results do not deal with the structure of the diffusion but estimate its upper bound, which induces conservatism. This paper studies delay-dependent robust stability of hybrid stochastic delay systems. A delay-dependent criterion for robust exponential stability of hybrid stochastic delay systems is presented in terms of linear matrix inequalities （LMIs）, which exploits the structure of the diffusion. Numerical examples are given to verify the effectiveness and less conservativeness of the proposed method.

Mean square stability of recurrent neural networks with random delay and Markovian switching

To establish easily proved conditions under which the random delayed recurrent neural network with Markovian switching is mean-square stability,the evolution of the delay was modeled by a continuous-time homogeneous Markov process with a finite number of states.By employing Lyapunov-Krasovskii functionals and conducting stochastic analysis,a linear matrix inequality (LMI) approach was developed to derive the criteria for mean-square stability,which can be readily checked by some standard numerical packages such as the Matlab LMI Toolbox.A numerical example was exploited to show the usefulness of the derived LMI-based stability conditions.

Delay-Dependent Exponential Stability of Stochastic Delayed Recurrent Neural Networks with Markovian Switching

The exponential stability problem is investigated for a class of stochastic recurrent neural networks with time delay and Markovian switching. By using Ito＇s differential formula and the Lyapunov stability theory, sufficient condition for the solvability of this problem is derived in term of linear matrix inequalities, which can be easily checked by resorting to available software packages. A numerical example and the simulation are exploited to demonstrate the effectiveness of the proposed results.

Containment control of heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded delays

This paper addresses the problem of containment control for heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded communication delays.The objective is to design a distributed control strategy that ensures the output of each follower converges to the convex hull formed by the outputs of a group of leaders in mean square sense.A novel distributed observer is proposed by tackling both Markovian randomly switching topologies and unbounded delays.Then,a distributed state feedback controller and a distributed output feedback controller are developed based on the distributed observer,respectively.Finally,simulation results are provided to demonstrate the effectiveness of the proposed controllers.

Stability of Coupled Impulsive Markovian Jump Reaction-Diffusion Systems on Networks

This paper is devoted to the investigation of stability for a class of coupled impulsive Markovian jump reaction-diffusion systems on networks(CIMJRDSNs). By using graph theory, a systematic method is provided to construct global Lyapunov functions for the CIMJRDSNs. Based on Lyapunov functions and stochastic analysis method, some novel stability principles associated with the topology property of the networks are established.

Existence and Uniqueness of Stochastic Differential Equations with Random Impulses and Markovian Switching under Non-Lipschitz Conditions

In the paper, stochastic differential equations with random impulses and Markovian switching are brought forward, where the so-called random impulse means that impulse ranges are driven by a series of random variables and impulse times are a random sequence, so these equations extend stochastic differential equations with jumps and Markovian switching. Then the existence and uniqueness of solutions to such equations are investigated by employing the Bihari inequality under non-Lipschtiz conditions.

CONVERGENCE RATE OF THE TRUNCATED EULER-MARUYAMA METHOD FOR NEUTRAL STOCHA STIC DIFFERENTIAL DELAY EQUATIONS WITH MARKOVIAN SWITCHING

The key aim of this paper is to show the strong convergence of the truncated Euler-Maruyama method for neutral stochastic differential delay equations(NSDDEs)with Markovian switching(MS)without the linear growth condition.We present the truncated Euler-Maruyama method of NSDDEs-MS and consider its moment boundedness under the local Lipschitz condition plus Khasminskii-type condition.We also study its strong convergence rates at time T and over a finite interval[0,T].Some numerical examples are given to illustrate the theoretical results.

H_(2)/H_(∞) Control for Stochastic Jump-Diffusion Systems with Markovian Switching

In this paper, a stochastic H2/H∞ control problem is investigated for Poisson jumpdiffusion systems with Markovian switching, which are driven by a Brownian motion and a Poisson random measure with the system parameters modulated by a continuous-time finite-state Markov chain.A stochastic jump bounded real lemma is proved, which reveals that the norm of the perturbation operator below a given threshold is equivalent to the existence of a global solution to a parameterized system of Riccati type differential equations. This result enables the authors to obtain sufficient and necessary conditions for the existence of H2/H∞ control in terms of two sets of interconnected systems of Riccati type differential equations.

Cooperative output feedback consensus control of second-order nonlinear multi-agent systems under Markovian switching topologies

This paper deals with the leader-following consensus problem for a class of second-order nonlinear multi-agent systems by output feedback.The communication topology is characterized by a Markovian switching graph.Firstly,an input-driven observer is introduced to estimate the consensus error of each follower agent.Then,a cooperative nonlinear control law is constructed using the relative output information between neighboring agents by employing the backstepping methodology,which achievesleader-following consensusin mean square sense.Compared with the existing results,the nonlinear functions are required to satisfy polynomial growth condition rather than globally Lipschitz growth or Lipschitz-like growth condition.A numerical example is given to illustrate the theoretical results.

Exponential Stability of Impulsive Neutral Stochastic Functional Differential Equations with Markovian Switching

The aim of this paper is to the discussion of the exponential stability of a class of impulsive neutral stochastic functional differential equations with Markovian switching.Under the influence of impulsive disturbance,the solution for the system is discontinuous.By using the Razumikhin technique and stochastic analysis approaches,as well as combining the idea of mathematical induction and classification discussion,some sufficient conditions for the pth moment exponential stability and almost exponential stability of the systems are obtained.The stability conclusion is full time-delay.The results show that impulse,the point distance of impulse and Markovain switching affect the stability for the system.Finally,two examples are provided to illustrate the effectiveness of the results proposed.

Global synchronization of discrete-time coupled neural networks with Markovian switching and impulses

This paper is concerned with the problem of synchronization anMysis for discrete-time coupled neural networks. The networks under consideration are subject to： （1） the jump- ing parameters that are modeled as a continuous-time, discrete-state Markov process; （2） impulsive disturbances; and （3） time delays that include both the mode-dependent discrete and distributed delay. By constructing suitable Lyapuno-Krasovskii functional and combining with linear matrix inequality approach, several novel criteria are derived for verifying the global exponential synchronization in the mean square of such stochas- tic dynamical networks. The derived conditions are established in terms of linear matrix inequalities, which can be easily solved by some available software packages. A simu- lation example is presented to show the effectiveness and applicability of the obtained results,

Barrier Option Pricing in Regime Switching Models with Rebates

This paper is concerned with the valuation of single and double barrier knock-out call options in a Markovian regime switching model with specific rebates.The integral formulas of the rebates are derived via matrix Wiener-Hopf factorizations and Fourier transform techniques,also,the integral representations of the option prices are constructed.Moreover,the first-passage time density functions in two-state regime model are derived.As applications,several numerical algorithms and numerical examples are presented.

Bipartite quasi-synchronization of multiple neural networks with generalized cooperative-competitive topology

This study examines the bipartite quasi-synchronization(B-Q synchronization)issue of coupled networks with general cooperative-competitive topology and the event-triggered communications between nodes to curb the communication cost.In the existing literature concerning bipartite synchronization,the network topology is required to be structurally balanced,which necessitates that competitive interactions exist only between two distinct subgroups.In this study,we aim to lengthen the network’s topology to a more general signed network in which antagonistic interactions can exist in the same or different subgroups.According to signed graph theory and the markovian stochastic event-triggering mechanism,the dynamical model of multiple neural networks(MNNs)with structurally unbalanced and markovian event-triggered communication is established.By utilizing the stochastic Lyapunov stability analysis,some adequate criteria for B-Q synchronization of MNNs with the structurally unbalanced graph are obtained;also,a bound for the B-Q synchronization error is provided.As a special case,the bipartite synchronization criteria for MNNs with the structurally balanced graph are also obtained.Finally,two simulations are performed to verify the theoretical result.

Modeling a stochastic avian influenza model under regime switching and with human-to-human transmission

In this paper,we investigate the stochastic avian influenza model with human-to-human transmission,which is disturbed by both white and telegraph noises.First,we show that the solution of the stochastic system is positive and global.Furthermore,by using stochastic Lyapunov functions,we establish sufficient conditions for the existence of a unique ergodic stationary distribution.Then we obtain the conditions for extinction.Finally,numerical simulations are employed to demonstrate the analytical results.