Consensus of nonlinear multi-agent systems with fuzzy modelling uncertainties via state-constraint hybrid impulsive protocols

In this paper, the nonlinear multi-agent system which contains uncertainty and is controlled by state-constraint impulsive protocol is taken into consideration. For the uncertainty of the multi-agent system, it is replaced by fuzzy logic system approximately and a judgement strategy which only contains the relative information with neighbors is proposed in this paper. In order to do research in state-constraint impulsive protocol, three kinds of impulsive control protocols which conclude partial input saturation, double actuator saturation and single actuator saturation are discussed. Then, some sufficient conditions of the system are obtained to reach consensus. Finally, some numerical simulation examples are provided to prove the effectiveness of the theoretical analysis.

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

[2]  Zhi-Hong Guan,et al.  Chaotifying Stable Linear Complex Networks via Single Pinning Impulsive Strategy , 2019, Int. J. Bifurc. Chaos.

[3]  Wei Deng,et al.  Synchronization for a Class of Fractional-order Linear Complex Networks via Impulsive Control , 2018 .

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

[5]  Sulan Li,et al.  Bipartite Consensus in Networks of Agents With Antagonistic Interactions and Quantization , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

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

[7]  Jie Chen,et al.  Distributed Consensus of Second-Order Multi-Agent Systems With Heterogeneous Unknown Inertias and Control Gains Under a Directed Graph , 2016, IEEE Transactions on Automatic Control.

[8]  Xing He,et al.  Impulsive control and Hopf bifurcation of a three-dimensional chaotic system , 2014 .

[9]  Chuandong Li,et al.  Sandwich control systems with impulse time windows , 2017, Int. J. Mach. Learn. Cybern..

[10]  Zhi-Hong Guan,et al.  Optimal tracking performance and design of networked control systems with packet dropouts , 2013, J. Frankl. Inst..

[11]  Chuandong Li,et al.  Iterative learning control design of nonlinear multiple time-delay systems , 2011, Appl. Math. Comput..

[12]  Chuandong Li,et al.  Fixed-time consensus of complex dynamical networks with nonlinear coupling and fuzzy state-dependent uncertainties , 2019, Fuzzy Sets Syst..

[13]  Chuandong Li,et al.  Stability of nonlinear systems with variable-time impulses: B-equivalence method , 2017 .

[14]  Liangliang Li,et al.  An analysis and design for time-varying structures dynamical networks via state constraint impulsive control , 2019, Int. J. Control.

[15]  Zidong Wang,et al.  A note on chaotic synchronization of time-delay secure communication systems , 2008 .

[16]  Long Wang,et al.  Consensus of Hybrid Multi-Agent Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[17]  Tiedong Ma,et al.  Adaptive consensus of multi-agent systems via odd impulsive control , 2018, Neurocomputing.

[18]  Chuandong Li,et al.  Second-order consensus of discrete-time multi-agent systems in directed networks with nonlinear dynamics via impulsive protocols , 2018, Neurocomputing.

[19]  Guo-Xing Wen,et al.  Neural-network-based adaptive leader-following consensus control for second-order non-linear multi-agent systems , 2015 .

[20]  Florentina Nicolau,et al.  Multi-input control-affine systems static feedback equivalent to a triangular form and their flatness , 2014, Int. J. Control.

[21]  Maojiao Ye,et al.  Consensus analysis of hybrid multiagent systems: A game‐theoretic approach , 2019, International Journal of Robust and Nonlinear Control.

[22]  Chuandong Li,et al.  Leader-following fixed-time quantized consensus of multi-agent systems via impulsive control , 2019, J. Frankl. Inst..

[23]  Qunjiao Zhang,et al.  Projective and lag synchronization between general complex networks via impulsive control , 2012 .

[24]  Yu-Ping Tian,et al.  Formation control of multi-agent systems with heterogeneous communication delays , 2009, Int. J. Syst. Sci..

[25]  Jin Zhou,et al.  Synchronization in complex delayed dynamical networks with impulsive effects , 2007 .

[26]  C. L. Philip Chen,et al.  Adaptive Fuzzy Leader-Following Consensus Control for Stochastic Multiagent Systems with Heterogeneous Nonlinear Dynamics , 2017, IEEE Transactions on Fuzzy Systems.

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

[28]  Z. Guan,et al.  Performance limitations of networked control systems with quantization and packet dropouts. , 2017, ISA transactions.

[29]  Zhi-Hong Guan,et al.  Neimark-Sacker bifurcation analysis on a numerical discretization of Gause-type predator-prey model with delay , 2015, J. Frankl. Inst..

[30]  Z. Guan,et al.  Stabilization of complex network with hybrid impulsive and switching control , 2008 .

[31]  William A. Porter,et al.  On the Reduction of Sensitivity in Multivariate Systems , 1967 .

[32]  Yuangong Sun.  Average consensus in networks of dynamic agents with uncertain topologies and time-varying delays , 2012, J. Frankl. Inst..

[33]  Chuandong Li,et al.  Impulsive Consensus of Multiagent Systems With Limited Bandwidth Based on Encoding–Decoding , 2020, IEEE Transactions on Cybernetics.