Dynamic consensus of nonlinear time-delay multi-agent systems with input saturation: an impulsive control algorithm

This paper aims to solve the dynamic consensus problem for a class of nonlinear multi-agent systems with input saturation and time delay. Due to the existing nonlinearity of the system, the low-gain feedback method widely used to handle saturation in multi-agent systems is no longer applicable. Moreover, to reduce both the communication and control energy consumption, an impulsive control algorithm is designed. Based on the stability theory of impulsive systems, as well as the property of the Laplacian matrix and convex hull, the set invariance conditions in the format of LMI are obtained. In addition, an optimization method is proposed for simultaneously designing the control parameters and assessing the attraction domain. Finally, the performance of the proposed consensus algorithms is demonstrated by two numerical experiments.

[1]  Wei Xing Zheng,et al.  On the Bipartite Consensus for Generic Linear Multiagent Systems With Input Saturation , 2017, IEEE Transactions on Cybernetics.

[2]  Yiguang Hong,et al.  Semi‐global output consensus of a group of linear systems in the presence of external disturbances and actuator saturation: An output regulation approach , 2016 .

[3]  Jun Hu,et al.  Non-fragile consensus control for nonlinear multi-agent systems with uniform quantizations and deception attacks via output feedback approach , 2019, Nonlinear Dynamics.

[4]  Yongguang Yu,et al.  Consensus of fractional multi-agent systems by distributed event-triggered strategy , 2018, Nonlinear Dynamics.

[5]  Guanrong Chen,et al.  Compressive-Sensing-Based Structure Identification for Multilayer Networks , 2018, IEEE Transactions on Cybernetics.

[6]  Kexue Zhang,et al.  Consensus seeking in multi-agent systems via hybrid protocols with impulse delays , 2017 .

[7]  James Lam,et al.  Semi-Global Leader-Following Consensus of Linear Multi-Agent Systems With Input Saturation via Low Gain Feedback , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Yan-Wu Wang,et al.  Impulsive Multisynchronization of Coupled Multistable Neural Networks With Time-Varying Delay , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[9]  Feng Qian,et al.  Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control , 2017, Inf. Sci..

[10]  Bo Zhou,et al.  Event‐Based Semiglobal Consensus of Homogenous Linear Multi‐Agent Systems Subject to Input Saturation , 2017 .

[11]  Guoqing Qi,et al.  Bounded consensus tracking of second-order multi-agent systems using rectangular impulsive control , 2019 .

[12]  Libing Wu,et al.  Cooperative adaptive fuzzy control for a class of uncertain non-linear multi-agent systems with time delays , 2017 .

[13]  W. Zhang,et al.  Observer-based adaptive consensus tracking for linear multi-agent systems with input saturation , 2015 .

[14]  Sophie Tarbouriech,et al.  Antiwindup design with guaranteed regions of stability: an LMI-based approach , 2005, IEEE Transactions on Automatic Control.

[15]  Javier Bajo,et al.  Multi-Agent Information Fusion System to manage data from a WSN in a residential home , 2015, Inf. Fusion.

[16]  Ahmad Afshar,et al.  Controller-based observer design for distributed consensus of multi-agent systems with fault and delay , 2019 .

[17]  Zhongjun Ma,et al.  Cluster-delay consensus in first-order multi-agent systems with nonlinear dynamics , 2016 .

[18]  Hamid Reza Karimi,et al.  Distributed $H_\infty$ Output-Feedback Control for Consensus of Heterogeneous Linear Multiagent Systems With Aperiodic Sampled-Data Communications , 2018, IEEE Transactions on Industrial Electronics.

[19]  Yan-Wu Wang,et al.  Optimal Persistent Monitoring Using Second-Order Agents With Physical Constraints , 2019, IEEE Transactions on Automatic Control.

[20]  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.

[21]  Zongli Lin,et al.  Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation , 2003, IEEE Trans. Fuzzy Syst..

[22]  Tingshu Hu,et al.  Control Systems with Actuator Saturation: Analysis and Design , 2001 .

[23]  Daoyi Xu,et al.  Stability Analysis and Design of Impulsive Control Systems With Time Delay , 2007, IEEE Transactions on Automatic Control.

[24]  Tingshu Hu,et al.  Control Systems with Actuator Saturation: Analysis and Design , 2001 .

[25]  Guanrong Chen,et al.  Fully Distributed Event-Triggered Semiglobal Consensus of Multi-agent Systems With Input Saturation , 2017, IEEE Transactions on Industrial Electronics.

[26]  Qing-Long Han,et al.  An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems , 2018, IEEE Transactions on Cybernetics.

[27]  X. Liao,et al.  Leader-following second-order consensus in multi-agent systems with sampled data via pinning control , 2014 .

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

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

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

[31]  Karl Henrik Johansson,et al.  Distributed event-triggered control for global consensus of multi-agent systems with input saturation , 2017, Autom..

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

[33]  M. Ceraolo,et al.  New dynamical models of lead-acid batteries , 2000 .

[34]  Junan Lu,et al.  Finite-time stabilization of complex dynamical networks via optimal control , 2016, Complex..

[35]  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.

[36]  Hyo-Sung Ahn,et al.  A survey of multi-agent formation control , 2015, Autom..

[37]  Clément Sire,et al.  Model of Collective Fish Behavior with Hydrodynamic Interactions. , 2017, Physical review letters.

[38]  Yan-Wu Wang,et al.  Output formation-containment of interacted heterogeneous linear systems by distributed hybrid active control , 2018, Autom..

[39]  Changchun Hua,et al.  Nonfragile Consensus of Multiagent Systems Based on Memory Sampled-Data Control , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[40]  Feiqi Deng,et al.  Sampled-Data Consensus for Multiagent Systems With Time Delays and Packet Losses , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[41]  Changchun Hua,et al.  Adaptive state feedback control for switched stochastic high‐order nonlinear systems under arbitrary switchings , 2018 .

[42]  Duxin Chen,et al.  Anisotropic interaction rules in circular motions of pigeon flocks: An empirical study based on sparse Bayesian learning. , 2017, Physical review. E.

[43]  V. Lakshmikantham,et al.  Theory of Impulsive Differential Equations , 1989, Series in Modern Applied Mathematics.

[44]  Guanrong Chen,et al.  Pinning Control of Lag-Consensus for Second-Order Nonlinear Multiagent Systems , 2017, IEEE Transactions on Cybernetics.