Consensus protocol design for discrete-time networks of multiagent with time-varying delay via logarithmic quantizer

This article considers the problem of consensus for discrete-time networks of multiagent with time-varying delays and quantization. It is assumed that the logarithmic quantizer is utilized between the information flow through the sensor of each agent, and its quantization error is included in the proposed method. By constructing a suitable Lyapunov-Krasovskii functional and utilizing matrix theory, a new consensus criterion for the concerned systems is established in terms of linear matrix inequalities LMIs which can be easily solved by various effective optimization algorithms. Based on the consensus criterion, a designing method of consensus protocol is introduced. One numerical example is given to illustrate the effectiveness of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity 21: 163-176, 2015

[1]  Renquan Lu,et al.  Networked Control With State Reset and Quantized Measurements: Observer-Based Case , 2013, IEEE Transactions on Industrial Electronics.

[2]  Huijun Gao,et al.  A New Model Transformation of Discrete-Time Systems With Time-Varying Delay and Its Application to Stability Analysis , 2011, IEEE Transactions on Automatic Control.

[3]  Gordon F. Royle,et al.  Algebraic Graph Theory , 2001, Graduate texts in mathematics.

[4]  Hui Li,et al.  Quantized H∞ Filtering for Singular Time-varying Delay Systems with Unreliable Communication Channel , 2012, Circuits Syst. Signal Process..

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

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

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

[8]  Fang Wu,et al.  Networked Control With Reset Quantized State Based on Bernoulli Processing , 2014, IEEE Transactions on Industrial Electronics.

[9]  Ju H. Park,et al.  Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer , 2014, Complex..

[10]  Guang-Hong Yang,et al.  Jensen inequality approach to stability analysis of discrete-time systems with time-varying delay , 2008, 2008 American Control Conference.

[11]  Jin-Hoon Kim,et al.  Note on stability of linear systems with time-varying delay , 2011, Autom..

[12]  Shengyuan Xu,et al.  A survey of linear matrix inequality techniques in stability analysis of delay systems , 2008, Int. J. Syst. Sci..

[13]  Robert E. Skelton,et al.  Stability tests for constrained linear systems , 2001 .

[14]  Roozbeh Daneshvar,et al.  The effect of gossip on social networks , 2011, Complex..

[15]  Lihua Xie,et al.  The sector bound approach to quantized feedback control , 2005, IEEE Transactions on Automatic Control.

[16]  Dongjun Lee,et al.  Stable Flocking of Multiple Inertial Agents on Balanced Graphs , 2007, IEEE Transactions on Automatic Control.

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

[18]  Huijun Gao,et al.  ${\cal H}_{\infty}$ Estimation for Uncertain Systems With Limited Communication Capacity , 2007, IEEE Transactions on Automatic Control.

[19]  Rathinasamy Sakthivel,et al.  State estimation for switched discrete-time stochastic BAM neural networks with time varying delay , 2013 .

[20]  Rathinasamy Sakthivel,et al.  Robust state estimation for discrete-time genetic regulatory networks with randomly occurring uncertainties , 2013 .

[21]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[22]  Hyungbo Shim,et al.  Output Consensus of Heterogeneous Uncertain Linear Multi-Agent Systems , 2011, IEEE Transactions on Automatic Control.

[23]  Ju H. Park,et al.  Dynamic output feedback consensus of continuous-time networked multiagent systems , 2015, Complex..

[24]  Cecilia E. Garcia Cena,et al.  Design and modeling of the multi-agent robotic system: SMART , 2012, Robotics Auton. Syst..

[25]  Tao Fan,et al.  Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties , 2014, Complex..

[26]  Daizhan Cheng,et al.  Leader-following consensus of multi-agent systems under fixed and switching topologies , 2010, Syst. Control. Lett..

[27]  S. M. Lee,et al.  Improved robust stability criteria for uncertain discrete-time systems with interval time-varying delays via new zero equalities [Brief Paper] , 2012 .

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

[29]  PooGyeon Park,et al.  Reciprocally convex approach to stability of systems with time-varying delays , 2011, Autom..

[30]  Wei Ren,et al.  Consensus strategies for cooperative control of vehicle formations , 2007 .

[31]  Mario di Bernardo,et al.  Analysis and stability of consensus in networked control systems , 2010, Appl. Math. Comput..

[32]  Renquan Lu,et al.  H∞ filtering for singular systems with communication delays , 2010, Signal Process..

[33]  Rathinasamy Sakthivel,et al.  Robust h ∞ control for uncertain discrete-time stochastic neural networks with time-varying delays , 2012 .

[34]  Sung Hyun Kim,et al.  Improved Approach to Robust H∞ Stabilization of Discrete-Time T-S Fuzzy Systems With Time-Varying Delays , 2010, IEEE Trans. Fuzzy Syst..

[35]  James Lam,et al.  A delay-partitioning approach to the stability analysis of discrete-time systems , 2010, Autom..