End to end communication rate-based adaptive fault tolerant control of multi-agent systems under unreliable interconnections

Abstract The active fault tolerant control (FTC) problem for nonidentical high-order multi-agent systems (MASs) with network disconnections and actuator faults is studied in this paper. To address the challenges incurred by network disconnections, a novel FTC method based on the end-to-end communication rates is proposed, where the MAS is considered as a cyber-physical system (CPS). In the cyber components, the pre-specified minimum values of the end-to-end communication rates are used to determine the status of network connection, then a logic-based switching control approach is designed to deal with the network disconnections. In the physical components, a cooperative controller and a high-gain observer-like protocol are presented to compensate the actuator faults and the nonidentical nonlinearities. Compared with the previous turning mechanisms based on the output errors method, the end-to-end communication rates method is a more direct way to determine status of network connection. Finally, a simulation is given to validate the effectiveness of the proposed method.

[1]  Ping Wang,et al.  Preserving privacy for free: Efficient and provably secure two-factor authentication scheme with user anonymity , 2015, Inf. Sci..

[2]  Pagavathigounder Balasubramaniam,et al.  Design of state estimator for BAM fuzzy cellular neural networks with leakage and unbounded distributed delays , 2017, Inf. Sci..

[3]  Tao Zhang,et al.  Stable Adaptive Neural Network Control , 2001, The Springer International Series on Asian Studies in Computer and Information Science.

[4]  Daizhan Cheng,et al.  Leader-following consensus of second-order agents with multiple time-varying delays , 2010, Autom..

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

[6]  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.

[7]  Ju H. Park,et al.  Adaptive sliding-mode insensitive control of a class of non-ideal complex networked systems , 2014, Inf. Sci..

[8]  Zhong-Ping Jiang,et al.  Distributed formation control of nonholonomic mobile robots without global position measurements , 2013, Autom..

[9]  Guang-Hong Yang,et al.  Decentralized fault-tolerant control for a class of nonlinear large-scale systems with actuator faults , 2017, Inf. Sci..

[10]  Guang-Hong Yang,et al.  Adaptive Fault Tolerant Control of Cooperative Heterogeneous Systems With Actuator Faults and Unreliable Interconnections , 2016, IEEE Transactions on Automatic Control.

[11]  Seung-Hwan Choi,et al.  Context Generator and Behavior Translator in a Multilayer Architecture for a Modular Development Process of Cyber-Physical Robot Systems , 2014, IEEE Transactions on Industrial Electronics.

[12]  Rajeev Shorey,et al.  Mobile, Wireless and Sensor Networks: Technology, Applications and Future Directions , 2005 .

[13]  Guang-Hong Yang,et al.  A New Sensor Fault Isolation Method for T–S Fuzzy Systems , 2017, IEEE Transactions on Cybernetics.

[14]  Khashayar Khorasani,et al.  Team Consensus for a Network of Unmanned Vehicles in Presence of Actuator Faults , 2010, IEEE Transactions on Control Systems Technology.

[15]  Xin Huang,et al.  Reliable Control Policy of Cyber-Physical Systems Against a Class of Frequency-Constrained Sensor and Actuator Attacks , 2018, IEEE Transactions on Cybernetics.

[16]  Vijay Kumar,et al.  Robust Control for Mobility and Wireless Communication in Cyber–Physical Systems With Application to Robot Teams , 2012, Proceedings of the IEEE.

[17]  Ping Wang,et al.  Two Birds with One Stone: Two-Factor Authentication with Security Beyond Conventional Bound , 2018, IEEE Transactions on Dependable and Secure Computing.

[18]  Cong Wang,et al.  Learning from neural control , 2006, IEEE Transactions on Neural Networks.

[19]  Xiao-Zheng Jin,et al.  Finite-time robust fault-tolerant control against actuator faults and saturations , 2017 .

[20]  Qing-Long Han,et al.  A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems , 2014, Autom..

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

[22]  Dan Ye,et al.  A cooperative detection and compensation mechanism against Denial-of-Service attack for cyber-physical systems , 2018, Inf. Sci..

[23]  Ayan Banerjee,et al.  Ensuring Safety, Security, and Sustainability of Mission-Critical Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[24]  Guanghui Wen,et al.  Containment of Higher-Order Multi-Leader Multi-Agent Systems: A Dynamic Output Approach , 2016, IEEE Transactions on Automatic Control.

[25]  Keng Peng Tee,et al.  Adaptive Neural Network Control for Helicopters in Vertical Flight , 2008, IEEE Transactions on Control Systems Technology.

[26]  Guang-Hong Yang,et al.  Robust Adaptive Fault-Tolerant Control for a Class of Unknown Nonlinear Systems , 2017, IEEE Transactions on Industrial Electronics.

[27]  Marcel Staroswiecki,et al.  Fault tolerant cooperative control for a class of nonlinear multi-agent systems , 2011, Syst. Control. Lett..

[28]  David J. Hill,et al.  Power systems as dynamic networks , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[29]  Guang-Hong Yang,et al.  Adaptive sliding mode fault tolerant control for nonlinearly chaotic systems against DoS attack and network faults , 2017, J. Frankl. Inst..

[30]  Guang-Hong Yang,et al.  Distributed Adaptive Fuzzy Control For Nonlinear Multiagent Systems Under Directed Graphs , 2018, IEEE Transactions on Fuzzy Systems.

[31]  Shixi Wen,et al.  Control and resource allocation of cyber-physical systems , 2016 .

[32]  Jun Zhao,et al.  Cooperative Adaptive Fuzzy Tracking Control for Networked Unknown Nonlinear Multiagent Systems With Time-Varying Actuator Faults , 2014, IEEE Transactions on Fuzzy Systems.

[33]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[34]  Wei Xing Zheng,et al.  Network-based practical set consensus of multi-agent systems subject to input saturation , 2018, Autom..

[35]  P. Kundur,et al.  Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions , 2004, IEEE Transactions on Power Systems.

[36]  Mohammad Haeri,et al.  Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure. , 2017, ISA transactions.

[37]  Frank L. Lewis,et al.  Coordination of multi-agent systems on interacting physical and communication topologies , 2017, Syst. Control. Lett..

[38]  Xin Wang,et al.  Distributed fault-tolerant control for a class of cooperative uncertain systems with actuator failures and switching topologies , 2016, Inf. Sci..

[39]  Ping Wang,et al.  Anonymous Two-Factor Authentication in Distributed Systems: Certain Goals Are Beyond Attainment , 2015, IEEE Transactions on Dependable and Secure Computing.