Stabilization of multi-group models with multiple dispersal and stochastic perturbation via feedback control based on discrete-time state observations

Abstract This paper focuses on the multi-group models with multiple dispersal and stochastic perturbation (MGMDS). The effect of both multiple dispersal among groups and stochastic perturbation are taken into consideration. The stabilization of MGMDS is investigated via feedback control based on the discrete-time state observations. In addition, a systematic method is given to construct a global Lyapunov function for MGMDS. By means of graph theory and Lyapunov method, some sufficient conditions are obtained to ensure the stabilization in the sense of mean-square asymptotical stability. An upper bound of the duration between two consecutive state observations is estimated. Moreover, to show the applicability of our results, the main theory is employed to a stochastic coupled oscillators. Finally, a numerical example is given to illustrate the effectiveness and feasibility of the theoretical results.

[1]  Jinde Cao,et al.  Stability Analysis of Markovian Jump Stochastic BAM Neural Networks With Impulse Control and Mixed Time Delays , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[2]  Xiaodong Liu,et al.  Stability analysis for neural networks with time-varying delay , 2008, 2008 47th IEEE Conference on Decision and Control.

[3]  Huijun Gao,et al.  Network-based feedback control for systems with mixed delays based on quantization and dropout compensation , 2011, Autom..

[4]  Jinde Cao,et al.  Adaptive cluster synchronization in directed networks with nonidentical nonlinear dynamics , 2016, Complex..

[5]  Wei Liu,et al.  Stabilisation of stochastic differential equations with Markovian switching by feedback control based on discrete-time state observation with a time delay , 2015 .

[6]  Jinde Cao,et al.  Distributed control of cluster synchronisation in networks with randomly occurring non-linearities , 2016, Int. J. Syst. Sci..

[7]  Ke Wang,et al.  Graph-theoretic approach to stability of multi-group models with dispersal , 2014 .

[8]  Toshikazu Kuniya,et al.  Global stability of a multi-group SVIR epidemic model , 2013 .

[9]  Liping Chen,et al.  Robust stability and stabilization of fractional-order linear systems with polytopic uncertainties , 2015, Appl. Math. Comput..

[10]  Xiaohua Ding,et al.  Stochastic stability for pantograph multi-group models with dispersal and stochastic perturbation , 2016, J. Frankl. Inst..

[11]  Zhidong Teng,et al.  n Species impulsive migration model with Markovian switching. , 2012, Journal of theoretical biology.

[12]  Toshikazu Kuniya,et al.  GLOBAL STABILITY OF EXTENDED MULTI-GROUP SIR EPIDEMIC MODELS WITH PATCHES THROUGH MIGRATION AND CROSS PATCH INFECTION , 2013 .

[13]  Ruoyan Sun,et al.  Computers and Mathematics with Applications Global Stability of the Endemic Equilibrium of Multigroup Sir Models with Nonlinear Incidence , 2022 .

[14]  Huaguang Zhang,et al.  Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay , 2010, IEEE Transactions on Neural Networks.

[15]  Xiaoming Fan,et al.  Global stability of deterministic and stochastic multigroup SEIQR models in computer network , 2013 .

[16]  Iftikhar Ahmad,et al.  Stochastic approach for the solution of multi-pantograph differential equation arising in cell-growth model , 2015, Appl. Math. Comput..

[17]  Huaguang Zhang,et al.  A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[18]  Xuerong Mao,et al.  Extinction and recurrence of multi-group SEIR epidemic , 2013 .

[19]  Wensheng Yin,et al.  Asymptotical boundedness for stochastic coupled systems on networks driven by G-Brownian motion , 2018, Journal of Mathematical Analysis and Applications.

[20]  Junjie Wei,et al.  Global stability of multi-group SEIR epidemic models with distributed delays and nonlinear transmission , 2012 .

[21]  Bing Chen,et al.  Synchronization of stochastic coupled systems via feedback control based on discrete-time state observations , 2017 .

[22]  Gnaneswaran Nagamani,et al.  Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term , 2016, Appl. Math. Comput..

[23]  Xuerong Mao,et al.  Stabilization of continuous-time hybrid stochastic differential equations by discrete-time feedback control , 2013, Autom..

[24]  Chunyu Yang,et al.  Stabilization of stochastic delay systems via a disordered controller , 2017, Appl. Math. Comput..

[25]  Jinde Cao,et al.  Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism , 2016, Neural Networks.

[26]  Michael Y. Li,et al.  Global stability of multi-group epidemic models with distributed delays , 2010 .

[27]  Wei Liu,et al.  Stabilization of hybrid stochastic differential equations by feedback control based on discrete-time state observations , 2014, Syst. Control. Lett..

[28]  Xuerong Mao,et al.  Stochastic differential equations and their applications , 1997 .

[29]  Meng Liu,et al.  Dynamical behavior of a one-prey two-predator model with random perturbations , 2015, Commun. Nonlinear Sci. Numer. Simul..

[30]  Pengfei Wang,et al.  Stability analysis for discrete-time coupled systems with multi-diffusion by graph-theoretic approach and its application , 2015 .

[31]  Yan Liu,et al.  The Stability of Stochastic Coupled Systems With Time-Varying Coupling and General Topology Structure , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Xiaoming Fan Global Stability of Multigroup SIRS Epidemic Model with Varying Population Sizes and Stochastic Perturbation around Equilibrium , 2014 .

[33]  Michael Y. Li,et al.  Impacts of migration and immigration on disease transmission dynamics in heterogeneous populations , 2012 .

[34]  John R. Jungck,et al.  Mathematics and evolutionary biology make bioinformatics education comprehensible , 2013, Briefings Bioinform..

[35]  S. R. Lopes,et al.  Rhythm synchronization and chaotic modulation of coupled Van der Pol oscillators in a model for the heartbeat , 2004 .

[36]  Jun-Guo Lu,et al.  Global asymptotical synchronization of chaotic neural networks by output feedback impulsive control: An LMI approach , 2009 .

[37]  Pengfei Wang,et al.  Synchronization of coupled stochastic complex-valued dynamical networks with time-varying delays via aperiodically intermittent adaptive control. , 2018, Chaos.

[38]  Wenxue Li,et al.  Novel aperiodically intermittent stability criteria for Markovian switching stochastic delayed coupled systems. , 2018, Chaos.

[39]  Gong-You Tang,et al.  Optimal vibration control for stochastic discrete-time systems , 2008, 2008 Chinese Control and Decision Conference.

[40]  Assessing environmental correlates of fish movement on a coral reef , 2015, Coral Reefs.

[41]  Wei Liu,et al.  Stabilization of Hybrid Systems by Feedback Control Based on Discrete-Time State Observations , 2015, SIAM J. Control. Optim..

[42]  Yongduan Song,et al.  A novel approach to output feedback control of fuzzy stochastic systems , 2014, Autom..

[43]  Michael Y. Li,et al.  Global-stability problem for coupled systems of differential equations on networks , 2010 .

[44]  Daniel W. C. Ho,et al.  Robust $H_{\infty }$ Fuzzy Output-Feedback Control With Multiple Probabilistic Delays and Multiple Missing Measurements , 2010, IEEE Transactions on Fuzzy Systems.

[45]  Xiaoqing Zhang,et al.  Exponential stability of delayed multi-group model with reaction-diffusion and multiple dispersal based on Razumikhin technique and graph theory , 2015, Commun. Nonlinear Sci. Numer. Simul..

[46]  James Lam,et al.  Stabilisation of hybrid stochastic differential equations by delay feedback control , 2008, Syst. Control. Lett..

[47]  Jinde Cao,et al.  Guaranteed cost boundary control for cluster synchronization of complex spatio-temporal dynamical networks with community structure , 2016, Science China Information Sciences.

[48]  Wenxue Li,et al.  Exponential synchronization for coupled complex networks with time-varying delays and stochastic perturbations via impulsive control , 2019, J. Frankl. Inst..

[49]  Yang Cao,et al.  Observer-Based Consensus Tracking of Nonlinear Agents in Hybrid Varying Directed Topology , 2017, IEEE Transactions on Cybernetics.