Neural Network-Based Adaptive Leader-Following Consensus Control for a Class of Nonlinear Multiagent State-Delay Systems

Compared with the existing neural network (NN) or fuzzy logic system (FLS) based adaptive consensus methods, the proposed approach can greatly alleviate the computation burden because it needs only to update a few adaptive parameters online. In the multiagent agreement control, the system uncertainties derive from the unknown nonlinear dynamics are counteracted by employing the adaptive NNs; the state delays are compensated by designing a Lyapunov–Krasovskii functional. Finally, based on Lyapunov stability theory, it is demonstrated that the proposed consensus scheme can steer a multiagent system synchronizing to the predefined reference signals. Two simulation examples, a numerical multiagent system and a practical multimanipulator system, are carried out to further verify and testify the effectiveness of the proposed agreement approach.

[1]  Long Wang,et al.  Consensus problems in networks of agents with double-integrator dynamics and time-varying delays , 2009, Int. J. Control.

[2]  Guo-Xing Wen,et al.  Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Zhongke Shi,et al.  Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form , 2014, IEEE Transactions on Cybernetics.

[4]  Zidong Wang,et al.  Distributed Filtering for Fuzzy Time-Delay Systems With Packet Dropouts and Redundant Channels , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[5]  Long Cheng,et al.  Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Dynamic Surface Control of Interconnected Nonlinear Pure-Feedback Systems , 2015, IEEE Transactions on Cybernetics.

[7]  Deliang Zeng,et al.  Consensus analysis of continuous‐time second‐order multi‐agent systems with nonuniform time‐delays and switching topologies , 2013 .

[8]  Jinde Cao,et al.  On Pinning Synchronization of Directed and Undirected Complex Dynamical Networks , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.

[9]  Yingmin Jia,et al.  Consensus of a Class of Second-Order Multi-Agent Systems With Time-Delay and Jointly-Connected Topologies , 2010, IEEE Transactions on Automatic Control.

[10]  Xin-Ping Guan,et al.  Adaptive Fuzzy Output-Feedback Controller Design for Nonlinear Time-Delay Systems With Unknown Control Direction , 2009, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Guo-Xing Wen,et al.  Direct adaptive NN control for a class of discrete-time nonlinear strict-feedback systems , 2010, Neurocomputing.

[12]  Zhongke Shi,et al.  Composite fuzzy control of a class of uncertain nonlinear systems with disturbance observer , 2015 .

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

[14]  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.

[15]  Junmin Li,et al.  Adaptive neural control for a class of nonlinearly parametric time-delay systems , 2005, IEEE Transactions on Neural Networks.

[16]  Shuzhi Sam Ge,et al.  Practical adaptive neural control of nonlinear systems with unknown time delays , 2005, Proceedings of the 2004 American Control Conference.

[17]  Jinde Cao,et al.  Second-order leader-following consensus of nonlinear multi-agent systems via pinning control , 2010, Syst. Control. Lett..

[18]  Randal W. Beard,et al.  Decentralized Scheme for Spacecraft Formation Flying via the Virtual Structure Approach , 2004 .

[19]  Shaocheng Tong,et al.  Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation , 2016, IEEE Transactions on Fuzzy Systems.

[20]  Peter N. Belhumeur,et al.  Closing ranks in vehicle formations based on rigidity , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[21]  Randal W. Beard,et al.  A decentralized scheme for spacecraft formation flying via the virtual structure approach , 2003, Proceedings of the 2003 American Control Conference, 2003..

[22]  Richard M. Murray,et al.  INFORMATION FLOW AND COOPERATIVE CONTROL OF VEHICLE FORMATIONS , 2002 .

[23]  Xiaobo Li,et al.  Adaptive Consensus of Multi-Agent Systems With Unknown Identical Control Directions Based on A Novel Nussbaum-Type Function , 2014, IEEE Transactions on Automatic Control.

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

[25]  Wei Ren,et al.  Distributed consensus of linear multi-agent systems with adaptive dynamic protocols , 2011, Autom..

[26]  Chenguang Yang,et al.  Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[27]  Zhongke Shi,et al.  Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[28]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

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

[30]  Guo-Xing Wen,et al.  Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems , 2016, IEEE Transactions on Cybernetics.

[31]  S. Ge,et al.  Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[32]  Bing Chen,et al.  Adaptive Neural Control for a Class of Perturbed Strict-Feedback Nonlinear Time-Delay Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[33]  Chai Wah Wu,et al.  Synchronization in Complex Networks of Nonlinear Dynamical Systems , 2008 .

[34]  C. L. Philip Chen,et al.  A rapid learning and dynamic stepwise updating algorithm for flat neural networks and the application to time-series prediction , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[35]  S. Shankar Sastry,et al.  Formation control of nonholonomic mobile robots with omnidirectional visual servoing and motion segmentation , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

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