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Distributed Fault Tolerant Control for Multi-agent Systems with Complex-weighted Directed Communication Topology subject to Actuator Faults

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  • Control Theory and Applications
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Abstract

In this paper, under the complex-weighted directed communication topology, the problem of distributed fault tolerant control (FTC) for a class of second-order multi-agent systems (MAS) in the presence of actuator faults is studied. The faults can simultaneously occur in more than one agent. First, a real representation of the secondorder dynamic agent with the complex weighted graph is proposed. Second, based on the proposed representation, distributed finite-time convergent observer is proposed for each agent to estimate the state and fault in a finite time. Then, using the fault information obtained online, an adaptive FTC protocol is proposed to compensate for the failure effects and to enable all the agents to achieve the control goal. Also, we show that the closed-loop system can be guaranteed to be asymptotically stable in the presence of faults. Finally, an illustration example is given to demonstrate the effectiveness of the proposed scheme.

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References

  1. R. Olfati–Saber and M. Murray, “Consensus problems in networks of agents with switching topology and timedelays,” IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1520–1533, 2004.

    Article  MathSciNet  MATH  Google Scholar 

  2. R. Olfati–Saber, “Flocking for multi–agent dynamic systems: algorithms and theory,” IEEE Transactions on Automatic Control, vol. 51, no. 3, pp. 401–420, 2006.

    Article  MathSciNet  MATH  Google Scholar 

  3. S. Nosrati, M. Shafiee, and M. B. Menhaj, “Dynamic average consensus via nonlinear protocols,” Automatica, vol. 48, no. 9, pp. 2262–2270, 2012.

    Article  MathSciNet  MATH  Google Scholar 

  4. B. Ranjbar–sahraei, M. Roopaei, and S. Khosravi, “Adaptive fuzzy formation control for a swarm of nonholonomic differentially driven vehicles,” Nonlinear Dynamics, vol. 67, no. 4, pp. 2747–2757, 2012.

    Article  MathSciNet  MATH  Google Scholar 

  5. B. S. Park and S. J. Yoo, “Adaptive leader–follower formation control of mobile robots with unknown skidding and slipping effects,” International Journal of Control, Automation and Systems, vol. 13, no. 3, pp. 587–594, 2015.

    Article  Google Scholar 

  6. A. Bidram, A. Davoudi, F. L. Lewis, and J. M. Guerrero, “Distributed cooperative secondary control of micro grids using feedback linearization,” IEEE Transactions on Power System, vol. 28, no. 3, pp. 3462–3470, 2013.

    Article  Google Scholar 

  7. Z. Lin, W. Ding, G. Yan, C. Yu, and A. Giua, “Leader–Follower Formation via Complex Laplacian,” Automatica, vol. 49. no. 6, pp.1900–1906, 2013.

    Article  MathSciNet  MATH  Google Scholar 

  8. B. D. O. Anderson, C. Yu, B. Fidan, and J. M. Hendrickx, “Rigid graph control architectures for autonomous formations,” IEEE Control Systems, vol. 28, no. 6, pp. 48–63, 2008.

    Article  MathSciNet  MATH  Google Scholar 

  9. M. Cao, C. Yu, and B. D. O. Anderson, “Formation control using range only measurements,” Automatica, vol. 47. no. 4, pp.776–781, 2011.

    Google Scholar 

  10. F. Dorfler and B. Francis, “Geometric analysis of the formation problem for autonomous robots,” IEEE Transactions on Automatic Control, vol. 55, no. 10, pp. 2379–2384, 2010.

    Article  MathSciNet  MATH  Google Scholar 

  11. Z. Lin, B. Francis, and M. Maggiore, “Necessary and sufficient graphical conditions for formation control of unicycles,” IEEE Transactions on Automatic Control, vol. 50, no. 1, pp. 121–127, 2005.

    Article  MathSciNet  MATH  Google Scholar 

  12. K. K. Oh and H. S. Ahn, “Formation control of mobile agents based on distributed position estimation,” IEEE Transactions on Automatic Control, vol. 58, no. 3, pp. 737–742, 2013.

    Article  MathSciNet  MATH  Google Scholar 

  13. L. Sabattini, C. Secchi, and C. Fantuzzi, “Arbitrarily shaped formations of mobile robots: artificial potential fields and coordinate transformation,” Autonomous Robots, vol. 30, no. 4, pp. 385–397, 2011.

    Article  Google Scholar 

  14. Z. Han, L. Wang, Z. Lin, and R. Zheng, “Formation control with size scaling via a complex Laplacian–based approach,” IEEE Transactions on Cybernetics, vol. 46, no. 10, pp. 1–12, 2015.

    Google Scholar 

  15. H. Ferdowsi and S. Jagannathan, “Decentralized Fault Tolerant Control of a Class of Nonlinear Interconnected Systems,” International Journal of Control, Automation and Systems, vol. 15, no. 2, pp. 527–536, 2017.

    Article  Google Scholar 

  16. Y. X. Li and G. H. Yang, “Fuzzy adaptive output feedback fault–tolerant tracking control of a class of uncertain nonlinear systems with non–affine nonlinear faults,” IEEE Transactions on Fuzzy Systems, vol. 24, no. 1, pp. 223–234, 2016.

    Article  Google Scholar 

  17. X. Wang and G. H. Yang, “Cooperative adaptive faulttolerant tracking control for a class of multi–agent systems with actuator failures and mismatched parameter uncertainties,” IET Control Theory & Applications, vol. 9, no. 8, pp. 1274–1284, 2015.

    Article  MathSciNet  Google Scholar 

  18. Z. Zuo, J. Zhang, and Y. Wang, “Adaptive fault–tolerant tracking control for linear and Lipschitz nonlinear multiagent systems,” IEEE Transactions on Industrial Electronics, vol. 62, no. 6, pp. 3923–3931, 2015.

    Google Scholar 

  19. C. Deng and G. H. Yang, “Distributed adaptive faulttolerant containment control for a class of multi agent systems with non–identical matching non–linear functions,” IET Control Theory & Applications, vol. 10, no. 3, pp. 273–281, 2015.

    Article  Google Scholar 

  20. D. Ye, X. Zhao, and B. Cao, “Distributed adaptive faulttolerant consensus tracking of multi–agent systems against time–varying actuator faults,” IET Control Theory & Applications, vol. 10. no. 5, pp.554–563, 2016.

    Google Scholar 

  21. Y. Wang, Y. Song, M. Krstic, and C. Wen, “Fault–tolerant finite time consensus for multiple uncertain nonlinear mechanical systems under single–way directed communication interactions and actuation failures,” Automatica, vol. 63, pp. 374–383, 2016.

    Article  MathSciNet  MATH  Google Scholar 

  22. S. Bhat and D. S. Bernstein, “Finite–time stability of continuous autonomous systems,” SIAM Journal on Control and Optimization, vol. 38, no. 3, pp. 751766, 2000.

    Article  MathSciNet  Google Scholar 

  23. G. Chen, F. L. Lewis, and L. Xie, “Finite–time distributed consensus via binary control protocols,” Automatica, vol. 47, no. 9, pp. 1962–1968, 2011.

    Article  MathSciNet  MATH  Google Scholar 

  24. Y. Zhao, Z. Duan, G. Wen, and G. Chen, “Distributed finite–time tracking for multiple non–identical second–order nonlinear systems with settling time estimation,” Automatica, vol. 64, pp. 86–93, 2016.

    Article  MathSciNet  MATH  Google Scholar 

  25. K. Zhang, B. Jiang, and V. Cocquempot, “Adaptive technique–based distributed fault estimation observer design for multi–agent systems with directed graphs,” IET Control Theory & Applications, vol. 9. no. 18, pp.2619–2625, 2015.

    Google Scholar 

  26. B. Jiang, M. Staroswiecki, and V. Cocquempot, “Fault accommodation for nonlinear dynamic systems,” IEEE Transactions on Automatic Control, vol. 51, no. 9, pp. 1578–1583, 2006.

    Article  MathSciNet  MATH  Google Scholar 

  27. A. Ghasemi, J. Askari, and M. B. Menhaj, “Fault detection and isolation of multi–agent systems via complex Laplacian,” AUT Journal of Modeling and Simulation, vol. 49, no. 1, pp. 95–102, 2017.

    Google Scholar 

  28. A. Ghasemi, J. Askari, and M. B. Menhaj, “Distributed fault detection and isolation of actuator faults in multiagent systems with complex–weights directed communication topology,” Journal of Control, Automation and Electrical Systems, vol. 29, no. 6, pp. 692–702, 2018.

    Article  Google Scholar 

  29. M. D. Ercegovac and J.–M. Muller, “Solving Systems of Linear Equations in Complex Domain: Complex EMethod,” LIP, 2007.

    Google Scholar 

  30. Y. Wang, L. Xie, and C. E. de Souza, “Robust control of a class of uncertain nonlinear systems,” Systems & Control Letters, vol. 19. no. 2, pp.139–149, 1992.

    Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran

    Ali Ghasemi & Javad Askari

  2. Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

    Mohammad Bagher Menhaj

Authors
  1. Ali Ghasemi
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  2. Javad Askari
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  3. Mohammad Bagher Menhaj
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Corresponding author

Correspondence to Ali Ghasemi.

Additional information

Recommended by Associate Editor Ho Jae Lee under the direction of Editor PooGyeon Park.

Ali Ghasemi is currently a Ph.D. candidate in the Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran. From 2016 to 2017, he worked as a research assistant with Prof. Menhaj at the computational intelligence and large scale systems research laboratory, Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran. He is author and co-author of about 20 technical papers and two books: Engineering Circuit Analysis, 2011, and Spacecraft Dynamics and Control, 2012, all in Persian. His current research interests include multi-agent systems, fault-tolerant control, adaptive control, and unmanned vehicles.

Javad Askari received the B.Sc. and M. Sc. degrees in electrical engineering from Isfahan University of Technology, Isfahan, Iran, in 1987 and from University of Tehran, Tehran, Iran, in 1993, respectively. He received the Ph.D. degree in electrical engineering from the University of Tehran in 2001. From 1999 to 2001, he received a grant from the German Academic Exchange Service (DAAD) and joined the Control Engineering Department, Technical University Hamburg, Hamburg, Germany. He is currently an Associate Professor in the Department of Control Engineering, Isfahan University of Technology (IUT). His current research interests include control theory, particularly in the field of hybrid dynamical systems and fault-tolerant control, adaptive control of time delay systems, identification, and electrical engineering curriculum.

Mohammad Bagher Menhaj received his Ph.D. degree from School of Electrical and Computer Engineering at OSU in 1992. After completing one year with OSU as a postdoctoral fellow, in 1993, he joined Amirkabir University of Technology, Tehran, Iran, where he is currently a Full Professor. December 2000 to Aug. 2003, he was with school of Electrical and Computer Engineering and Department of Computer Science at OSU as a visiting faculty member and research scholar. He is author and co-author of more than 400 technical papers, and six books: Fundamentals of Neural Networks, 1998, Application of Computational Intelligence in Control, 1998, Neural Networks, 2000, Fuzzy Computations, 2007, Fuzzy Control, 2016, and Adaptive Control Systems, 2016, all in Persian. He has also been project director for many industrial projects in the areas such as crisis control management, communication traffic control, real time simulator design, flight control and navigation systems, and satellite attitude determination and control systems, sponsored by private and government institutions. He is also currently head of electrical and biomedical and mechatronic engineering department at the Qazvin Islamic Azad University (QIAU). His main research interests are: theory of computational intelligence, learning automata, adaptive filtering and their applications in control, power systems, image processing, pattern recognition, and communications, and other areas of interests are: theory of rough set and knowledge discovery.

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Ghasemi, A., Askari, J. & Menhaj, M.B. Distributed Fault Tolerant Control for Multi-agent Systems with Complex-weighted Directed Communication Topology subject to Actuator Faults. Int. J. Control Autom. Syst. 17, 415–424 (2019). https://doi.org/10.1007/s12555-017-0458-7

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  • DOI: https://doi.org/10.1007/s12555-017-0458-7

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