Observer-based fault detection for high-order nonlinear multi-agent systems

Abstract This paper focuses on the problem of fault detection (FD) for high-order heterogeneous nonlinear multi-agent systems. The nonlinear part of the multi-agent systems comprises a known Lipschitz nonlinear function and an unknown nonlinear function. Fault in one agent can be detected by the unknown input observers, which are constructed in its neighbor nodes. In the observers, the unknown nonlinear functions are treated as unknown input, and do not appear in the observer residual dynamic, so the residual is robust to all types of unknown nonlinear functions, which may contain additive disturbance as well as nonlinear, uncertain, time-varying terms, and so on. Simulations are given to demonstrate the effectiveness of the proposed methods.

[1]  Hieu Minh Trinh,et al.  State and input simultaneous estimation for a class of nonlinear systems , 2004, Autom..

[2]  Changchun Hua,et al.  Nonlinear protocols for distributed consensus in directed networks of dynamic agents , 2015, J. Frankl. Inst..

[3]  Zhong-Ping Jiang,et al.  Distributed Output-Feedback Control of Nonlinear Multi-Agent Systems , 2013, IEEE Transactions on Automatic Control.

[4]  Christopher Edwards,et al.  Robust Fault Estimation Using Relative Information in Linear Multi-Agent Networks , 2014, IEEE Transactions on Automatic Control.

[5]  R. Rajamani,et al.  Existence and design of observers for nonlinear systems: Relation to distance to unobservability , 1998 .

[6]  Zhiwei Gao,et al.  Reliable Observer-Based Control Against Sensor Failures for Systems With Time Delays in Both State and Input , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[7]  Cunwu Han,et al.  Robust fault detection for uncertain discrete-time systems subject to signal-to-noise ratio constrained channels , 2015, J. Frankl. Inst..

[8]  Nan Yang,et al.  Fault Isolation of Nonlinear Processes Based on Fault Directions and Features , 2014, IEEE Transactions on Control Systems Technology.

[9]  Chen Gan.  Observer-based consensus control and fault detection for multi-agent systems , 2014 .

[10]  Zhiguo Liu,et al.  Distributed consensus of a class of networked heterogeneous multi-agent systems , 2014, J. Frankl. Inst..

[11]  Antonio Bicchi,et al.  Consensus Computation in Unreliable Networks: A System Theoretic Approach , 2010, IEEE Transactions on Automatic Control.

[12]  Zidong Wang,et al.  Distributed fault detection for a class of second-order multi-agent systems: an optimal robust observer approach , 2014 .

[13]  Chi Ma,et al.  Fault Detection of Non-Gaussian Processes Based on Model Migration , 2013, IEEE Transactions on Control Systems Technology.

[14]  André Teixeira,et al.  Networked control systems under cyber attacks with applications to power networks , 2010, Proceedings of the 2010 American Control Conference.

[15]  H. Trinh,et al.  Functional Observers for Dynamical Systems , 2011 .

[16]  Zhong-Ping Jiang,et al.  Distributed nonlinear control of mobile autonomous multi-agents , 2014, Autom..

[17]  Wei Wang,et al.  Cooperative control for consensus of multi-agent systems with actuator faults , 2014, Comput. Electr. Eng..

[18]  Karl Henrik Johansson,et al.  Distributed fault detection for interconnected second-order systems , 2011, Autom..

[19]  Huaguang Zhang,et al.  Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming , 2015, IEEE Transactions on Fuzzy Systems.

[20]  Khashayar Khorasani,et al.  Fault Detection and Isolation of discrete-time Markovian jump linear systems with application to a network of multi-agent systems having imperfect communication channels , 2009, Autom..

[21]  Shreyas Sundaram,et al.  Distributed Function Calculation via Linear Iterative Strategies in the Presence of Malicious Agents , 2011, IEEE Transactions on Automatic Control.

[22]  Khashayar Khorasani,et al.  Actuator Fault Detection and Isolation for a Network of Unmanned Vehicles , 2009, IEEE Transactions on Automatic Control.

[23]  Jianchang Liu,et al.  A consensus-based multi-agent approach for estimation in robust fault detection. , 2014, ISA transactions.

[24]  Zhong-Ping Jiang,et al.  Event-based consensus of multi-agent systems with general linear models , 2014, Autom..

[25]  Lei Liu,et al.  Distributed formation control of networked Euler-Lagrange systems with fault diagnosis , 2015, J. Frankl. Inst..

[26]  Mohammad Haeri,et al.  Adaptive flocking control of nonlinear multi-agent systems with directed switching topologies and saturation constraints , 2013, J. Frankl. Inst..

[27]  José Aguilar-Castro,et al.  Agents-based design for fault management systems in industrial processes , 2007, Comput. Ind..

[28]  Huaguang Zhang,et al.  Output regulation of state-coupled linear multi-agent systems with globally reachable topologies , 2014, Neurocomputing.

[29]  Lihua Xie,et al.  Global $H_\infty$ Consensus of Multi-Agent Systems with Lipschitz Nonlinear Dynamics , 2012 .

[30]  Lei Guo,et al.  Observer-Based Optimal Fault Detection and Diagnosis Using Conditional Probability Distributions , 2006, IEEE Transactions on Signal Processing.

[31]  Navid Sahebjamnia,et al.  IMAQCS: Design and implementation of an intelligent multi-agent system for monitoring and controlling quality of cement production processes , 2013, Comput. Ind..

[32]  Mark E. Campbell,et al.  Multiple agent-based autonomy for satellite constellations , 2000, Artif. Intell..

[33]  Lijun Zhu,et al.  Robust homogenization and consensus of nonlinear multi-agent systems , 2014, Syst. Control. Lett..

[34]  P. Frank,et al.  Survey of robust residual generation and evaluation methods in observer-based fault detection systems , 1997 .

[35]  Huijun Gao,et al.  Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems , 2014, Autom..