Distributed adaptive output consensus control of a class of uncertain nonlinear multiagents systems

This paper addresses the leader‐follower output consensus problem for a class of uncertain nonlinear multiagent systems in a directed communication topology. By employing the backstepping method, the dynamic surface control technique, neutral networks, and the graph theory, a distributed adaptive control scheme is developed recursively for each follower using its own and neighbors' information. The key features of this strategy are that it reduces the computational burden by introducing the dynamic surface control approach and there is no requirement for a priori knowledge about uncertain dynamics of the system. Moreover, in theory, it is proved that the designed control approach can steer the output signals of followers in a directed graph to track the desired trajectory of the leader and guarantee all signals in the closed‐loop system cooperatively semiglobally uniformly ultimately bounded. Furthermore, two examples are included, and the simulation results demonstrate the effectiveness of the proposed strategy.

[1]  Robert M. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.

[2]  Marios M. Polycarpou,et al.  Stable adaptive neural control scheme for nonlinear systems , 1996, IEEE Trans. Autom. Control..

[3]  Swaroop Darbha,et al.  Dynamic surface control for a class of nonlinear systems , 2000, IEEE Trans. Autom. Control..

[4]  Tao Zhang,et al.  Stable adaptive control for nonlinear multivariable systems with a triangular control structure , 2000, IEEE Trans. Autom. Control..

[5]  Shuzhi Sam Ge,et al.  Adaptive neural control of uncertain MIMO nonlinear systems , 2004, IEEE Transactions on Neural Networks.

[6]  Dan Wang,et al.  Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form , 2005, IEEE Transactions on Neural Networks.

[7]  Li Tieshan,et al.  DSC-backstepping Based Robust Adaptive NN Control for Nonlinear Systems , 2008 .

[8]  Shuzhi Sam Ge,et al.  Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form , 2008, Autom..

[9]  Zhihua Qu,et al.  Cooperative Control of Dynamical Systems With Application to Autonomous Vehicles , 2008, IEEE Transactions on Automatic Control.

[10]  Mark W. Spong,et al.  Output Synchronization of Nonlinear Systems with Relative Degree One , 2008, Recent Advances in Learning and Control.

[11]  Zao-Jian Zou,et al.  DSC-backstepping Based Robust Adaptive NN Control for Nonlinear Systems: DSC-backstepping Based Robust Adaptive NN Control for Nonlinear Systems , 2009 .

[12]  Z. Qu,et al.  Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles , 2009 .

[13]  Shaocheng Tong,et al.  A DSC Approach to Robust Adaptive NN Tracking Control for Strict-Feedback Nonlinear Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Yongming Li,et al.  Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[15]  Dan Wang,et al.  Neural network‐based adaptive dynamic surface control of uncertain nonlinear pure‐feedback systems , 2011 .

[16]  Frank L. Lewis,et al.  Lyapunov, Adaptive, and Optimal Design Techniques for Cooperative Systems on Directed Communication Graphs , 2012, IEEE Transactions on Industrial Electronics.

[17]  Hao Wang,et al.  Robust adaptive neural control of uncertain pure-feedback nonlinear systems , 2012, 2012 Third International Conference on Intelligent Control and Information Processing.

[18]  Sung Jin Yoo,et al.  Distributed Consensus Tracking for Multiple Uncertain Nonlinear Strict-Feedback Systems Under a Directed Graph , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Wenwu Yu,et al.  An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination , 2012, IEEE Transactions on Industrial Informatics.

[20]  Zhengtao Ding,et al.  Consensus Output Regulation of a Class of Heterogeneous Nonlinear Systems , 2013, IEEE Transactions on Automatic Control.

[21]  Wei Wang,et al.  Hierarchical decomposition based distributed adaptive control for output consensus tracking of uncertain nonlinear systems , 2013, 2013 American Control Conference.

[22]  Jie Huang,et al.  Cooperative global output regulation of heterogeneous second-order nonlinear uncertain multi-agent systems , 2013, Autom..

[23]  Frank L. Lewis,et al.  Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems , 2014, Autom..

[24]  Fuad E. Alsaadi,et al.  An overview of consensus problems in constrained multi-agent coordination , 2014 .

[25]  Yi Dong,et al.  Cooperative Global Output Regulation for a Class of Nonlinear Multi-Agent Systems , 2014, IEEE Transactions on Automatic Control.

[26]  Haibo Ji,et al.  Leader-following consensus of multi-agent systems under directed communication topology via distributed adaptive nonlinear protocol , 2014, Syst. Control. Lett..

[27]  Antoine Girard,et al.  Multiagent Flocking Under General Communication Rule , 2014, IEEE Transactions on Control of Network Systems.

[28]  Jie Huang,et al.  Cooperative robust output regulation of a class of heterogeneous linear uncertain multi‐agent systems , 2014 .

[29]  Yisheng Zhong,et al.  Formation Control for High-Order Linear Time-Invariant Multiagent Systems With Time Delays , 2014, IEEE Transactions on Control of Network Systems.

[30]  Xudong Ye,et al.  Distributed adaptive controller for the output-synchronization of networked systems in semi-strict feedback form , 2014, J. Frankl. Inst..

[31]  Wei Wang,et al.  Distributed adaptive control for consensus tracking with application to formation control of nonholonomic mobile robots , 2014, Autom..

[32]  Tianping Chen,et al.  Achieving Cluster Consensus in Continuous-Time Networks of Multi-Agents With Inter-Cluster Non-Identical Inputs , 2014, IEEE Transactions on Automatic Control.

[33]  Valery A. Ugrinovskii,et al.  Gain‐scheduled leader‐follower tracking control for interconnected parameter varying systems , 2015, ArXiv.

[34]  Gang Feng,et al.  Leader-follower consensus of time-varying nonlinear multi-agent systems , 2015, Autom..

[35]  Peter Kuster,et al.  Nonlinear And Adaptive Control Design , 2016 .

[36]  Qing-Long Han,et al.  Distributed networked control systems: A brief overview , 2017, Inf. Sci..

[37]  Jinde Cao,et al.  Leader-Following Consensus of Nonlinear Multiagent Systems With Stochastic Sampling , 2017, IEEE Transactions on Cybernetics.