H∞H∞ consensus control for multi-agent systems with missing measurements: The finite-horizon case

Abstract This paper deals with the H ∞ consensus control problem for a class of discrete time-varying multi-agent systems with both missing measurements and parameter uncertainties. A directed graph is used to represent the communication topology of the multi-agent network, and a binary switching sequence satisfying a conditional probability distribution is employed to describe the missing measurements. The purpose of the addressed problem is to design a time-varying controller such that, for all probabilistic missing observations and admissible parameter uncertainties, the H ∞ consensus performance is guaranteed over a given finite horizon for the closed-loop networked multi-agent systems. According to the given topology, the measurement output available for the controller is not only from the individual agent but also from its neighboring agents. By using the completing squares method and stochastic analysis techniques, necessary and sufficient conditions are derived for the H ∞ consensus to be ensured, and then the time-varying controller parameters are designed by solving coupled backward recursive Riccati difference equations (RDEs). A simulation example is utilized to illustrate the usefulness of the proposed control protocol.

[1]  Yiguang Hong,et al.  Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version) , 2017, 1801.00258.

[2]  Z. Guan,et al.  Consensus of second-order and high-order discrete-time multi-agent systems with random networks☆ , 2012 .

[3]  Zhisheng Duan,et al.  On H∞ and H2 performance regions of multi-agent systems , 2011, Autom..

[4]  Soummya Kar,et al.  Distributed Consensus Algorithms in Sensor Networks: Quantized Data and Random Link Failures , 2007, IEEE Transactions on Signal Processing.

[5]  Lihua Xie,et al.  Network Topology and Communication Data Rate for Consensusability of Discrete-Time Multi-Agent Systems , 2011, IEEE Transactions on Automatic Control.

[6]  Wei Xing Zheng,et al.  Consensus of multiple second-order vehicles with a time-varying reference signal under directed topology , 2011, Autom..

[7]  Lihua Xie,et al.  Distributed Consensus With Limited Communication Data Rate , 2011, IEEE Transactions on Automatic Control.

[8]  M. Benrejeb,et al.  New delay-dependent stability conditions for linear systems with delay , 2011, 2011 International Conference on Communications, Computing and Control Applications (CCCA).

[9]  Fuwen Yang,et al.  Robust H ∞ filtering for discrete time-varying uncertain systems with a known deterministic input , 2002 .

[10]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[11]  Mario di Bernardo,et al.  Synchronizability and Synchronization Dynamics of Weighed and Unweighed Scale Free Networks with Degree Mixing , 2007, Int. J. Bifurc. Chaos.

[12]  Khashayar Khorasani,et al.  A Decentralized Markovian Jump ${\cal H}_{\infty}$ Control Routing Strategy for Mobile Multi-Agent Networked Systems , 2011, IEEE Transactions on Control Systems Technology.

[13]  Yang Liu,et al.  Consensus problem of high‐order multi‐agent systems with external disturbances: An H∞ analysis approach , 2010 .

[14]  Wenwu Yu,et al.  Distributed Consensus Filtering in Sensor Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[15]  Hong-Bin Ma Decentralized adaptive synchronization of a stochastic discrete-time multiagent dynamic model , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[16]  Yeung Sam Hung,et al.  Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case , 2010, Autom..

[17]  YangQuan Chen,et al.  High-Order Consensus Algorithms in Cooperative Vehicle Systems , 2006, 2006 IEEE International Conference on Networking, Sensing and Control.

[18]  Xiao Fan Wang,et al.  Flocking of Multi-Agents With a Virtual Leader , 2009, IEEE Trans. Autom. Control..

[19]  Karlene A. Hoo,et al.  Stability analysis for closed-loop management of a reservoir based on identification of reduced-order nonlinear model , 2013 .

[20]  Khashayar Khorasani,et al.  Multi-agent team cooperation: A game theory approach , 2009, Autom..

[21]  Dongbing Gu,et al.  A Game Theory Approach to Target Tracking in Sensor Networks , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

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

[23]  Long Wang,et al.  Finite-time formation control for multi-agent systems , 2009, Autom..

[24]  Zidong Wang,et al.  Bounded $H_{\infty}$ Synchronization and State Estimation for Discrete Time-Varying Stochastic Complex Networks Over a Finite Horizon , 2011, IEEE Transactions on Neural Networks.

[25]  Peng Shi,et al.  Joint state filtering and parameter estimation for linear stochastic time-delay systems , 2011, Signal Process..

[26]  Yingmin Jia,et al.  Consensus of second-order discrete-time multi-agent systems with nonuniform time-delays and dynamically changing topologies , 2009, Autom..

[27]  Wei Ren On Consensus Algorithms for Double-Integrator Dynamics , 2008, IEEE Trans. Autom. Control..

[28]  Ji-Feng Zhang,et al.  Necessary and Sufficient Conditions for Consensusability of Linear Multi-Agent Systems , 2010, IEEE Transactions on Automatic Control.

[29]  Amr El Abbadi,et al.  Convergence Rates of Distributed Average Consensus With Stochastic Link Failures , 2010, IEEE Transactions on Automatic Control.

[30]  Zidong Wang,et al.  Distributed H∞ state estimation with stochastic parameters and nonlinearities through sensor networks: The finite-horizon case , 2012, Autom..

[31]  Randy A. Freeman,et al.  Multi-Agent Coordination by Decentralized Estimation and Control , 2008, IEEE Transactions on Automatic Control.

[32]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

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

[34]  Aurora Hermoso-Carazo,et al.  Recursive smoothing algorithms for the estimation of signals from uncertain observations via mixture approximations , 2010, Int. J. Syst. Sci..

[35]  Jonathan H. Manton,et al.  Stochastic Consensus Seeking With Noisy and Directed Inter-Agent Communication: Fixed and Randomly Varying Topologies , 2010, IEEE Transactions on Automatic Control.

[36]  Dirk Aeyels,et al.  Cluster formation in a time-varying multi-agent system , 2011, Autom..

[37]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.