Energy-to-peak consensus for multi-agent systems with stochastic disturbances and Markovian switching topologies

This paper is concerned with the problem of energy-to-peak consensus for a class of multi-agent systems with both stochastic disturbances and Markovian switching topologies. The objective is to design a control protocol in the form of dynamic output feedback, such that the multi-agent system reaches mean square consensus and has a prescribed energy-to-peak disturbance attenuation level. By using linear transformations, the problem is transformed into a standard energy-to-peak control problem. Then a new bounded real lemma is established. On the basis of this, an approach for the design of the control protocol is developed, by which the desired gain can be obtained via solving a number of linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the proposed approach.

[1]  Frank L. Lewis,et al.  Distributed Control Systems for Small-Scale Power Networks: Using Multiagent Cooperative Control Theory , 2014, IEEE Control Systems.

[2]  D. Elworthy ASYMPTOTIC METHODS IN THE THEORY OF STOCHASTIC DIFFERENTIAL EQUATIONS , 1992 .

[3]  Janset Dasdemir,et al.  Output feedback synchronization of multiple robot systems under parametric uncertainties , 2017 .

[4]  Jinde Cao,et al.  Exponential H∞ filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities , 2016, Science China Technological Sciences.

[5]  Ju H. Park,et al.  Robust resilient L2-L∞ control for uncertain stochastic systems with multiple time delays via dynamic output feedback , 2016, J. Frankl. Inst..

[6]  Yu-Ping Tian,et al.  Consentability and protocol design of multi-agent systems with stochastic switching topology , 2009, Autom..

[7]  Jinde Cao,et al.  Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching , 2016, IEEE Transactions on Cybernetics.

[8]  Ana L. C. Bazzan,et al.  Multi-Agent Systems for Traffic and Transportation Engineering , 2009 .

[9]  Zhen Wang,et al.  Reduced-order observer design for the synchronization of the generalized Lorenz chaotic systems , 2012, Appl. Math. Comput..

[10]  Hui Zhang,et al.  Robust gain-scheduling energy-to-peak control of vehicle lateral dynamics stabilisation , 2014 .

[11]  Xiaowu Mu,et al.  L 2, 2014 .

[12]  Hao Shen,et al.  Finite-time l2-l∞ tracking control for Markov jump repeated scalar nonlinear systems with partly usable model information , 2016, Inf. Sci..

[13]  J. Ben Atkinson,et al.  Modeling and Analysis of Stochastic Systems , 1996 .

[14]  Yuqiang Wu,et al.  Observer-based finite-time exponential l2 − l∞ control for discrete-time switched delay systems with uncertainties , 2013 .

[15]  Guang-Hong Yang,et al.  New Results on Output Feedback $H_{\infty} $ Control for Linear Discrete-Time Systems , 2014, IEEE Transactions on Automatic Control.

[16]  Zhen Wang,et al.  Consensus for Nonlinear Stochastic Multi-agent Systems with Time Delay , 2018, Appl. Math. Comput..

[17]  Yiguang Hong,et al.  On Convergence Rate of Distributed Stochastic Gradient Algorithm for Convex Optimization with Inequality Constraints , 2016, SIAM J. Control. Optim..

[18]  Tao Li,et al.  Consensus Conditions of Multi-Agent Systems With Time-Varying Topologies and Stochastic Communication Noises , 2010, IEEE Transactions on Automatic Control.

[19]  Yilun Shang,et al.  Group consensus of multi-agent systems in directed networks with noises and time delays , 2015, Int. J. Syst. Sci..

[20]  X. Mao Stability of stochastic differential equations with Markovian switching , 1999 .

[21]  Jinde Cao,et al.  Consensus of multi-agent systems via intermittent event-triggered control , 2017, Int. J. Syst. Sci..

[22]  Jinde Cao,et al.  Event-Triggered Schemes on Leader-Following Consensus of General Linear Multiagent Systems Under Different Topologies , 2017, IEEE Transactions on Cybernetics.

[23]  Qian Ma,et al.  Non-fragile observer-based H∞ control for stochastic time-delay systems , 2016, Appl. Math. Comput..

[24]  Long Wang,et al.  Finite-time consensus for stochastic multi-agent systems , 2011, Int. J. Control.

[25]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[26]  John S. Baras,et al.  Almost sure convergence to consensus in Markovian random graphs , 2008, 2008 47th IEEE Conference on Decision and Control.

[27]  R. Beard,et al.  Consensus of information under dynamically changing interaction topologies , 2004, Proceedings of the 2004 American Control Conference.

[28]  Bor-Sen Chen,et al.  H∞ Control for a Class of Nonlinear Stochastic Time-Delay Systems , 2004 .

[29]  Jinde Cao,et al.  Finite-time consensus of second-order multi-agent systems via auxiliary system approach , 2016, J. Frankl. Inst..

[30]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[31]  Rathinasamy Sakthivel,et al.  Robust reliable L2 - L∞ control for continuous-time systems with nonlinear actuator failures , 2016, Complex..

[32]  Jing Wang,et al.  synchronization for singularly perturbed complex networks with semi-Markov jump topology , 2018, Appl. Math. Comput..

[33]  Yan Cui,et al.  L2 − L∞ Consensus Control for High‐Order Multi‐Agent Systems with Nonuniform Time‐Varying Delays , 2014 .

[34]  Yingmin Jia,et al.  Distributed robust Hinfinity consensus control in directed networks of agents with time-delay , 2008, Syst. Control. Lett..

[35]  Jinde Cao,et al.  Stochastic Synchronization of Complex Networks With Nonidentical Nodes Via Hybrid Adaptive and Impulsive Control , 2012, IEEE Transactions on Circuits and Systems I: Regular Papers.

[36]  Hong Zhu,et al.  Finite-time H∞ estimation for discrete-time Markov jump systems with time-varying transition probabilities subject to average dwell time switching , 2015, Commun. Nonlinear Sci. Numer. Simul..

[37]  Jinde Cao,et al.  Exponential stability of stochastic functional differential equations with Markovian switching and delayed impulses via Razumikhin method , 2012, Advances in Difference Equations.

[38]  Huijun Gao,et al.  Leader-following consensus of a class of stochastic delayed multi-agent systems with partial mixed impulses , 2015, Autom..

[39]  Yang Liu,et al.  H ∞ consensus control of multi-agent systems with switching topology: a dynamic output feedback protocol , 2010, Int. J. Control.

[40]  D. Wilson Convolution and Hankel operator norms for linear systems , 1989 .

[41]  Shengyuan Xu,et al.  Regularized Primal–Dual Subgradient Method for Distributed Constrained Optimization , 2016, IEEE Transactions on Cybernetics.

[42]  Hao Shen,et al.  Non-fragile mixed ℋ∞/l 2 − l ∞ synchronisation control for complex networks with Markov jumping-switching topology under unreliable communication links , 2014 .

[43]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.