Cooperative Adaptive Fuzzy Output Feedback Control for Synchronization of Nonlinear Multi‐Agent Systems in the Presence of Input Saturation

This paper considers the leader‐following synchronization problem of nonlinear multi‐agent systems with unmeasurable states in the presence of input saturation. Each follower is governed by a class of strict‐feedback systems with unknown nonlinearities and the information of the leader can be accessed by only a small fraction of followers. An auxiliary system is introduced and its states are used to design the cooperative controllers for counteracting the effect of input saturation. By using fuzzy logic systems to approximate the unknown nonlinearities, local adaptive fuzzy observers are designed to estimate the unmeasurable states. Dynamic surface control (DSC) is employed to design distributed adaptive fuzzy output feedback controllers. The developed controllers guarantee that the outputs of all followers synchronize to that of the leader under directed communication graphs. Based on Lyapunov stability theory, it is proved that all signals in the closed‐loop systems are semiglobally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. An example is provided to show the effectiveness of the proposed control approach.

[1]  Dan Wang,et al.  Cooperative fuzzy adaptive output feedback control for synchronisation of nonlinear multi-agent systems under directed graphs , 2015, Int. J. Syst. Sci..

[2]  Gang Sun,et al.  Distributed Neural Network Control for Adaptive Synchronization of Uncertain Dynamical Multiagent Systems , 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]  Guanghui Wen,et al.  Consensus Tracking of Multi-Agent Systems With Lipschitz-Type Node Dynamics and Switching Topologies , 2014, IEEE Transactions on Circuits and Systems I: Regular Papers.

[5]  Huiping Li,et al.  Distributed model predictive control of constrained nonlinear systems with communication delays , 2013, Syst. Control. Lett..

[6]  Dan Wang,et al.  Distributed model reference adaptive control for cooperative tracking of uncertain dynamical multi‐agent systems , 2013, IET Control Theory & Applications.

[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]  Ziyang Meng,et al.  On global leader-following consensus of identical linear dynamic systems subject to actuator saturation , 2013, Syst. Control. Lett..

[9]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Control of MIMO Nonlinear Systems With Unknown Dead-Zone Inputs , 2013, IEEE Transactions on Fuzzy Systems.

[10]  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.

[11]  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.

[12]  Weisheng Yan,et al.  Mutual Synchronization of Multiple Robot Manipulators with Unknown Dynamics , 2012, J. Intell. Robotic Syst..

[13]  Yingmin Jia,et al.  Adaptive consensus protocol for networks of multiple agents with nonlinear dynamics using neural networks , 2012 .

[14]  Frank Allgöwer,et al.  Cooperative control of dynamically decoupled systems via distributed model predictive control , 2012 .

[15]  Frank L. Lewis,et al.  Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics , 2012, Autom..

[16]  X. Liu,et al.  Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  Shaocheng Tong,et al.  Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Frank L. Lewis,et al.  Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities , 2011 .

[19]  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).

[20]  Guanghui Wen,et al.  A new observer-type consensus protocol for linear multi-agent dynamical systems , 2011, Proceedings of the 30th Chinese Control Conference.

[21]  Tieshan Li,et al.  Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown time delays and input saturation , 2011, Neurocomputing.

[22]  Wei Wei,et al.  Consensus problems for linear time-invariant multi-agent systems with saturation constraints , 2011 .

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

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

[25]  Shuzhi Sam Ge,et al.  Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints , 2011, Autom..

[26]  Lin Huang,et al.  Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint , 2016, IEEE Transactions on Circuits and Systems I: Regular Papers.

[27]  Frank L. Lewis,et al.  Distributed adaptive control for synchronization of unknown nonlinear networked systems , 2010, Autom..

[28]  Shaocheng Tong,et al.  Fuzzy-Adaptive Decentralized Output-Feedback Control for Large-Scale Nonlinear Systems With Dynamical Uncertainties , 2010, IEEE Transactions on Fuzzy Systems.

[29]  Long Cheng,et al.  Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems With Uncertainties , 2010, IEEE Transactions on Neural Networks.

[30]  Licheng Jiao,et al.  Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[31]  Shuzhi Sam Ge,et al.  Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities , 2010, IEEE Transactions on Neural Networks.

[32]  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).

[33]  Guoqiang Hu Robust consensus tracking of a class of second-order multi-agent dynamic systems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[34]  Shaocheng Tong,et al.  A Combined Backstepping and Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control , 2009, IEEE Transactions on Fuzzy Systems.

[35]  Shaocheng Tong,et al.  Observer-based fuzzy adaptive control for strict-feedback nonlinear systems , 2009, Fuzzy Sets Syst..

[36]  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).

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

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

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

[40]  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.

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

[42]  P. P. Yip,et al.  Adaptive dynamic surface control : a simplified algorithm for adaptive backstepping control of nonlinear systems , 1998 .

[43]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.