Impulsive consensus of multi-agent nonlinear systems with control gain error

In this paper, the consensus problem of multi-agent nonlinear systems with control gain error is studied. Based on the theory of impulsive differential equations, Lyapunov stability theory and algebraic graph theory, some impulsive consensus conditions are given to realize the consensus of a class of multi-agent nonlinear systems. Compared with the existing investigations of impulsive consensus of multi-agent systems, the proposed impulsive control protocol with control gain error is more rigorous and effective in practical systems. Two numerical simulations are verified to confirm the effectiveness of the proposed methods.

[1]  Jinde Cao,et al.  A unified synchronization criterion for impulsive dynamical networks , 2010, Autom..

[2]  Bing Chen,et al.  Synchronization for Coupled Neural Networks With Interval Delay: A Novel Augmented Lyapunov–Krasovskii Functional Method , 2013, IEEE Transactions on Neural Networks and Learning Systems.

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

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

[5]  Huaguang Zhang,et al.  Controlling Chaos: Suppression, Synchronization and Chaotification , 2009 .

[6]  Haibo Jiang,et al.  Consensus of multi-agent linear dynamic systems via impulsive control protocols , 2011, Int. J. Syst. Sci..

[7]  Josep M. Guerrero,et al.  Hybrid Three-Phase/Single-Phase Microgrid Architecture With Power Management Capabilities , 2015, IEEE Transactions on Power Electronics.

[8]  Huaguang Zhang,et al.  Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[9]  Bo Liu,et al.  Pinning Consensus in Networks of Multiagents via a Single Impulsive Controller , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Josep M. Guerrero,et al.  A Multiagent-Based Consensus Algorithm for Distributed Coordinated Control of Distributed Generators in the Energy Internet , 2015, IEEE Transactions on Smart Grid.

[11]  Zhi-Hong Guan,et al.  Guaranteed performance consensus in second-order multi-agent systems with hybrid impulsive control , 2014, Autom..

[12]  Mengyin Fu,et al.  Consensus of Multi-Agent Systems With General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols , 2011, IEEE Transactions on Automatic Control.

[13]  Guanghui Wen,et al.  Consensus in multi‐agent systems with communication constraints , 2012 .

[14]  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.

[15]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[16]  Haibo Jiang,et al.  Impulsive synchronization of networked nonlinear dynamical systems , 2010 .

[17]  Gang Feng,et al.  Consensus Analysis Based on Impulsive Systems in Multiagent Networks , 2012, IEEE Transactions on Circuits and Systems I: Regular Papers.

[18]  Junan Lu,et al.  Second-order consensus of multi-agent systems with nonlinear dynamics via impulsive control , 2014, Neurocomputing.

[19]  Huaguang Zhang,et al.  Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming , 2015, IEEE Transactions on Fuzzy Systems.

[20]  Gang Feng,et al.  Consensus of Multi-Agent Networks With Aperiodic Sampled Communication Via Impulsive Algorithms Using Position-Only Measurements , 2012, IEEE Transactions on Automatic Control.

[21]  Huaguang Zhang,et al.  Adaptive Synchronization Between Two Different Chaotic Neural Networks With Time Delay , 2007, IEEE Transactions on Neural Networks.

[22]  Ma Tie-Dong,et al.  Impulsive stabilization of a class of nonlinear system with bounded gain error , 2014 .

[23]  L. Shilnikov CHUA’S CIRCUIT: RIGOROUS RESULTS AND FUTURE PROBLEMS , 1994 .

[24]  Z. Guan,et al.  Consensus and performance optimisation of multi-agent systems with position-only information via impulsive control , 2013 .

[25]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

[26]  Shinji Hara,et al.  Biochemical oscillations in delayed negative cyclic feedback: Existence and profiles , 2013, Autom..

[27]  Zhihong Man,et al.  Robust Finite-Time Consensus Tracking Algorithm for Multirobot Systems , 2009, IEEE/ASME Transactions on Mechatronics.

[28]  Zhiwei Liu,et al.  Containment control for multi-agent systems via impulsive algorithms without velocity measurements , 2014 .

[29]  Yu Zhao,et al.  Robust consensus tracking of multi-agent systems with uncertain lur'e-type non-linear dynamics , 2013 .

[30]  T. Chai,et al.  Adaptive synchronization between two different chaotic systems with unknown parameters , 2006 .

[31]  Gang Feng,et al.  Consensus of second-order multi-agent systems via impulsive control using sampled hetero-information , 2013, Autom..

[32]  Tiedong Ma,et al.  On the exponential synchronization of stochastic impulsive chaotic delayed neural networks , 2011, Neurocomputing.

[33]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[34]  Jinde Cao,et al.  Synchronization criteria of Lur’e systems with time-delay feedback control , 2005 .

[35]  Shihua Chen,et al.  Impulsive consensus problem of second-order multi-agent systems with switching topologies , 2012 .

[36]  Jiangping Hu,et al.  Tracking control for multi-agent consensus with an active leader and variable topology , 2006, Autom..

[37]  Junwei Sun,et al.  Transmission projective synchronization of multi-systems with non-delayed and delayed coupling via impulsive control. , 2012, Chaos.

[38]  Tiedong Ma,et al.  Synchronization of multi-agent stochastic impulsive perturbed chaotic delayed neural networks with switching topology , 2015, Neurocomputing.

[39]  Ma Tie-Dong,et al.  An improved impulsive control approach to robust lag synchronization between two different chaotic systems , 2010 .

[40]  Daniel W. C. Ho,et al.  Impulsive consensus of multi‐agent directed networks with nonlinear perturbations , 2012 .

[41]  Yan‐Wu Wang,et al.  Consensus in second-order multi-agent systems via impulsive control using position-only information with heterogeneous delays , 2015 .

[42]  Frank L. Lewis,et al.  Optimal Design for Synchronization of Cooperative Systems: State Feedback, Observer and Output Feedback , 2011, IEEE Transactions on Automatic Control.

[43]  Huaguang Zhang,et al.  Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach , 2015, IEEE Transactions on Cybernetics.

[44]  Yu-Ping Tian,et al.  Consensus of Multi-Agent Systems With Diverse Input and Communication Delays , 2008, IEEE Transactions on Automatic Control.