Skip to main content

Abstract

In this chapter, we first introduce some underlying concepts of cooperative control. Then, we briefly review how fixed-time cooperative control is motivated and promoted in the control community. Moreover, we present some related work of distributed optimization and network connectivity. Furthermore, we summarize future research topics. Finally, we give a brief outline of the monograph.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. B. Blanknov, Friday smorgasbord: school is out version, available at https://reefbuilders.com/2016/11/11/friday-smorgasbord-58/. Accessed 19 Mar 2019

  2. Lee’s Birdwatching adventures plus, mixed flock of birds flying in a V formation, available at https://leesbird.com/2013/07/05/. Accessed 19 Mar 2019

  3. Renaisscience, Mill of humanity: swarms, emergence and us, available at https://medium.com/@renaisscience/mill-of-humanity-swarms-emergence-and-us-b8f9ef50a11e/. Accessed 19 Mar 2019

  4. L. Felzmann, How the science of swarms can help us fight cancer and predict the future, available at https://www.wired.com/2013/03/powers-of-swarms/. Accessed 19 Mar 2019

  5. M.M. Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos (Simon & Schuster, New York, 1992)

    Google Scholar 

  6. W.B. Arthur, Complexity and the economy. Science 284(5411), 107–109 (1999)

    Article  Google Scholar 

  7. T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, O. Shochet, Novel type of phase transitions in a system of self-driven particles. Phys. Rev. Lett. 75(6), 1226–1229 (1995)

    Article  MathSciNet  Google Scholar 

  8. A. Jadbabaie, J. Lin, A.S. Morse, Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Trans. Autom. Control 48(6), 988–1001 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  9. W. Ren, R.W. Beard, E.M. Atkins, Information consensus in multivehicle cooperative control. IEEE Control Syst. Mag. 27(2), 71–82 (2007)

    Article  Google Scholar 

  10. Q. Lu, Q.-L. Han, X. Xie, S. Liu, A finite-time motion control strategy for odor source localization. IEEE Trans. Ind. Electron. 61(10), 5419–5430 (2014)

    Article  Google Scholar 

  11. Q. Lu, Q.-L. Han, S. Liu, A finite-time particle swarm optimization algorithm for odor source localization. Inf. Sci. 277, 111–140 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  12. Y. Cao, W. Yu, W. Ren, G. Chen, An overview of recent progress in the study of distributed multi-agent coordination. IEEE Trans. Ind. Inf. 9(1), 427–438 (2013)

    Article  Google Scholar 

  13. L. Ding, Q.-L. Han, G. Guo, Network-based leader-following consensus for distributed multi-agent systems. Automatica 49(7), 2281–2286 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  14. X. Ge, Q.-L. Han, Consensus of multiagent systems subject to partially accessible and overlapping Markovian network topologies. IEEE Trans. Cybern. 47(8), 1807–1819 (2017)

    Article  Google Scholar 

  15. X. Ge, Q.-L. Han, F. Yang, Event-based set-membership leader-following consensus of networked multi-agent systems subject to limited communication resources and unknown-but-bounded noise. IEEE Trans. Ind. Electron. 64(6), 5045–5054 (2017)

    Article  Google Scholar 

  16. Y. Cao, W. Ren, Z. Meng, Decentralized finite-time sliding mode estimators and their applications in decentralized finite-time formation tracking. Syst. Control Lett. 59(9), 522–529 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  17. X. Ge, Q.-L. Han, Distributed formation control of networked multi-agent systems using a dynamic event-triggered communication mechanism. IEEE Trans. Ind. Electron. 64(10), 8118–8127 (2017)

    Article  Google Scholar 

  18. C. Wang, Z. Zuo, Z. Lin, Z. Ding, Consensus control of a class of Lipschitz nonlinear systems with input delay. IEEE Trans. Circuits Syst. I: Regul. Papers 62(11), 2730–2738 (2015)

    Article  MathSciNet  Google Scholar 

  19. X. Ge, Q.-L. Han, D. Ding, X.-M. Zhang, B. Ning, A survey on recent advances in distributed sampled-data cooperative control of multi-agent systems. Neurocomputing 275, 1684–1701 (2018)

    Article  Google Scholar 

  20. W. He, C. Xu, Q.-L. Han, F. Qian, Z. Lang, Finite-time \(L_2\) leader-follower consensus of networked Euler-Lagrange systems with external disturbances. IEEE Trans. Syst. Man Cybern.: Syst. 48(11), 1920–1928 (2018)

    Article  Google Scholar 

  21. X.-M. Zhang, Q.-L. Han, X. Yu, Survey on recent advances in networked control systems. IEEE Trans. Ind. Inf. 12(5), 1740–1752 (2016)

    Article  Google Scholar 

  22. C. Wang, Z. Zuo, Z. Lin, Z. Ding, A truncated prediction approach to consensus control of Lipschitz nonlinear multiagent systems with input delay. IEEE Trans. Control Netw. Syst. 4(4), 716–724 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  23. Q. Lu, Q.-L. Han, S. Liu, A cooperative control framework for collective decision on movement behaviors of particles. IEEE Trans. Evol. Comput. 20(6), 859–873 (2016)

    Article  Google Scholar 

  24. Q. Lu, Q.-L. Han, Mobile robot networks for environmental monitoring: a cooperative receding horizon temporal logic control approach. IEEE Trans. Cybern. 49(2), 698–711 (2019)

    Article  Google Scholar 

  25. F.L. Lewis, H. Zhang, K. Hengster-Movric, A. Das, Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches (Springer, London, 2014)

    Google Scholar 

  26. Z. Li, Z. Duan, Cooperative Control of Multi-Agent Systems: A Consensus Region Approach (Taylor & Francis Inc, United States, 2014)

    Google Scholar 

  27. Y. Song, Y. Wang, Cooperative Control of Nonlinear Networked Systems: Infinite-time and Finite-time Design Methods (Springer International Publishing, 2019)

    Google Scholar 

  28. L. Ding, Q.-L. Han, L.Y. Wang, E. Sindi, Distributed cooperative optimal control of DC microgrids with communication delays. IEEE Trans. Ind. Inf. 14(9), 3924–3935 (2018)

    Article  Google Scholar 

  29. X. Ge, F. Yang, Q.-L. Han, Distributed networked control systems: a brief overview. Inf. Sci. 380, 117–131 (2017)

    Article  Google Scholar 

  30. W. He, G. Chen, Q.-L. Han, W. Du, J. Cao, F. Qian, Multiagent systems on multilayer networks: synchronization analysis and network design. IEEE Trans. Syst. Man Cybern. Syst. 47(7), 1655–1667 (2017)

    Article  Google Scholar 

  31. B. Tian, L. Yin, H. Wang, Finite-time reentry attitude control based on adaptive multivariable disturbance compensation. IEEE Trans. Ind. Electron. 62(9), 5889–5898 (2015)

    Article  Google Scholar 

  32. T. Zhao, Z. Ding, Distributed finite-time optimal resource management for microgrids based on multi-agent framework. IEEE Trans. Ind. Electron. 65(8), 6571–6580 (2018)

    Article  Google Scholar 

  33. X.-M. Zhang, Q.-L. Han, B.-L. Zhang, An overview and deep investigation on sampled-data-based event-triggered control and filtering for networked systems. IEEE Trans. Ind. Inf. 13(1), 4–16 (2017)

    Article  MathSciNet  Google Scholar 

  34. W. Ren, Consensus based formation control strategies for multi-vehicle systems, In Proceedings of the American Control Conference (ACC) (Minnesota, USA, Minneapolis, 2006), pp. 4237–4242

    Google Scholar 

  35. W. He, B. Zhang, Q.-L. Han, F. Qian, J. Kurths, J. Cao, Leader-following consensus of nonlinear multiagent systems with stochastic sampling. IEEE Trans. Cybern. 47(2), 327–338 (2017)

    Google Scholar 

  36. X. Ge, Q.-L. Han, X.-M. Zhang, Achieving cluster formation of multi-agent systems under aperiodic sampling and communication delays. IEEE Trans. Ind. Electron. 65(4), 3417–3426 (2018)

    Article  Google Scholar 

  37. Y.-L. Wang, Q.-L. Han, Network-based fault detection filter and controller coordinated design for unmanned surface vehicles in network environments. IEEE Trans. Ind. Inf. 12(5), 1753–1765 (2016)

    Article  MathSciNet  Google Scholar 

  38. L. Ding, Q.-L. Han, X. Ge, X.-M. Zhang, An overview of recent advances in event-triggered consensus of multiagent systems. IEEE Trans. Cybern. 48(4), 1110–1123 (2018)

    Article  Google Scholar 

  39. R. Olfati-Saber, Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Trans. Autom. Control 51(3), 401–420 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  40. C.W. Reynolds, Flocks, herds, and schools: a distributed behavioral model. Comput. Gr. 21(4), 25–34 (1987)

    Article  Google Scholar 

  41. H.G. Tanner, A. Jadbabaie, G.J. Pappas, Flocking in fixed and switching networks. IEEE Trans. Autom. Control 52(5), 863–868 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  42. V. Gazi, K.M. Passino, Stability analysis of swarms. IEEE Trans. Autom. Control 48(4), 692–697 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  43. G. Beni, P. Liang, Pattern reconfiguration in swarms—convergence of a distributed asynchronous and bounded iterative algorithm. IEEE Trans. Robot. Autom. 12(3), 485–490 (1996)

    Article  Google Scholar 

  44. A. Tiwari, J. Fung, J.M. Carson, A framework for Lyapunov certificates for multi-vehicle rendezvous problem, In Proceedings of the American Control Conference (ACC) (Massachusetts, USA, Boston, 2004), pp. 5582–5587

    Google Scholar 

  45. J. Lin, A.S. Morse, B.D.O. Anderson, The multi-agent rendezvous problem—part 1: the synchronous case. SIAM J. Control Optim. 46(6), 2096–2119 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  46. R. Olfati-Saber, R.M. Murray, Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Autom. Control 49(9), 1520–1533 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  47. Y. Kim, M. Mesbahi, On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian. IEEE Trans. Autom. Control 51(1), 116–120 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  48. L. Wang, F. Xiao, Finite-time consensus problems for networks of dynamic agents. IEEE Trans. Autom. Control 55(4), 950–955 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  49. F. Xiao, L. Wang, J. Chen, Y. Gao, Finite-time formation control for multi-agent systems. Automatica 45(11), 2605–2611 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  50. Z.-H. Guan, F.-L. Sun, Y.-W. Wang, T. Li, Finite-time consensus for leader-following second-order multi-agent networks. IEEE Trans. Circuits Syst. I: Regul. Papers 59(11) (2012)

    Article  MathSciNet  Google Scholar 

  51. Q. Lu, Q.-L. Han, B. Zhang, D. Liu, S. Liu, Cooperative control of mobile sensor networks for environmental monitoring: An event-triggered finite-time control scheme. IEEE Trans. Cybern. 47(12), 4134–4147 (2017)

    Article  Google Scholar 

  52. H. Liu, L. Cheng, M. Tan, Z. Hou, Y. Wang, Distributed exponential finite-time coordination of multi-agent systems: containment control and consensus. Int. J. Control 88(2), 237–247 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  53. G. Chen, F.L. Lewis, L. Xie, Finite-time distributed consensus via binary control protocols. Automatica 47(9), 1962–1968 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  54. X. Liu, J. Lam, W. Yu, G. Chen, Finite-time consensus of multiagent systems with a switching protocol. IEEE Trans. Neural Netw. Learn. Syst. 27(4), 853–862 (2016)

    Article  MathSciNet  Google Scholar 

  55. Y. Zhang, Y. Yang, Y. Zhao, G. Wen, Distributed finite-time tracking control for nonlinear multi-agent systems subject to external disturbances. Int. J. Control 86(1), 29–40 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  56. Y. Cao, W. Ren, Distributed coordinated tracking with reduced interaction via a variable structure approach. IEEE Trans. Autom. Control 57(1), 33–48 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  57. S. Khoo, L. Xie, Z. Man, Robust finite-time consensus tracking algorithm for multirobot systems. IEEE/ASME Trans. Mechatron. 14(2), 219–228 (2009)

    Article  Google Scholar 

  58. Z.-H. Guan, F.-L. Sun, Y.-W. Wang, T. Li, Finite-time consensus for leader-following second-order multi-agent networks. IEEE Trans. Circuits Syst. I: Regul. Papers 59(11), 2646–2654 (2012)

    Article  MathSciNet  Google Scholar 

  59. B. Ning, J. Jin, J. Zheng, Z. Man, Finite-time and fixed-time leader-following consensus for multi-agent systems with discontinuous inherent dynamics. Int. J. Control 91(6), 1259–1270 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  60. A. Polyakov, Nonlinear feedback design for fixed-time stabilization of linear control systems. IEEE Trans. Autom. Control 57(8), 2106–2110 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  61. S. Parsegov, A. Polyakov, P. Shcherbakov, Nonlinear fixed-time control protocol for uniform allocation of agents on a segment, In Proceedings of the IEEE Conference on Decision and Control (Hawaii, USA, 2013), pp. 7732–7737

    Google Scholar 

  62. Z. Zuo, L. Tie, A new class of finite-time nonlinear consensus protocols for multi-agent systems. Int. J. Control 87(2), 363–370 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  63. Z. Zuo, L. Tie, Distributed robust finite-time nonlinear consensus protocols for multi-agent systems. Int. J. Syst. Sci. 47(6), 1366–1375 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  64. D. Meng, Y. Jia, J. Du, Finite-time consensus for multiagent systems with cooperative and antagonistic interactions. IEEE Trans. Neural Netw. Learn. Syst. 27(4), 762–770 (2016)

    Article  MathSciNet  Google Scholar 

  65. B. Ning, Q.-L. Han, Z. Zuo, Distributed optimization for multiagent systems: an edge-based fixed-time consensus approach. IEEE Trans. Cybern. 49(1), 122–132 (2019)

    Article  Google Scholar 

  66. H. Hong, W. Yu, X. Yu, G. Wen, A. Alsaedi, Fixed-time connectivity-preserving distributed average tracking for multi-agent systems. IEEE Trans. Circuits Syst. II: Express Br. 64(10), 1192–1196 (2017)

    Article  Google Scholar 

  67. B. Ning, Z. Zuo, J. Jin, J. Zheng, Distributed fixed-time coordinated tracking for nonlinear multi-agent systems under directed graphs. Asian J. Control 20(2), 646–658 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  68. B. Ning, Q.-L. Han, Z. Zuo, J. Jin, J. Zheng, Collective behaviors of mobile robots beyond the nearest neighbor rules with switching topology. IEEE Trans. Cybern. 48(5), 1577–1590 (2018)

    Article  Google Scholar 

  69. B. Jiang, Q. Hu, M.-I. Friswell, Fixed-time rendezvous control of spacecraft with a tumbling target under loss of actuator effectiveness. IEEE Trans. Aerosp. Electron. Syst. 52(4), 1576–1586 (2016)

    Article  Google Scholar 

  70. S. Parsegov, A. Polyakov, P.S. Shcherbakov, Fixed-time consensus algorithm for multi-agent systems with integrator dynamics, In Proceedings of the IFAC Workshop on Distributed Estimation and Control in Networked Systems (Koblenz, Germany, 2013), pp. 110–115

    Article  Google Scholar 

  71. D. Meng, Z. Zuo, Signed-average consensus for networks of agents: a nonlinear fixed-time convergence protocol. Nonlinear Dyn. 85(1), 155–165 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  72. Y. Feng, X. Yu, Z. Man, On nonsingular terminal sliding-mode control of nonlinear systems. Automatica 49(6), 1715–1722 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  73. Z. Zuo, Nonsingular fixed-time consensus tracking for second-order multi-agent networks. Automatica 54, 305–309 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  74. J. Fu, J. Wang, Fixed-time coordinated tracking for second-order multi-agent systems with bounded input uncertainties. Syst. Control Lett. 93, 1–12 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  75. B. Tian, H. Lu, Z. Zuo, W. Yang, Fixed-time leader-following output feedback consensus for second-order multiagent systems. IEEE Trans. Cybern. 49(4), 1545–1550 (2019)

    Article  Google Scholar 

  76. Z. Zuo, B. Tian, M. Defoort, Z. Ding, Fixed-time consensus tracking for multi-agent systems with high-order integrator dynamics. IEEE Trans. Autom. Control 63(2), 563–570 (2018)

    Article  MATH  Google Scholar 

  77. Z. Zuo, Q.-L. Han, B. Ning, An explicit estimate for the upper bound of the settling time in fixed-time leader-following consensus of high-order multi-variable multi-agent systems. IEEE Trans. Ind. Electron. 66(8), 6250–6259 (2019)

    Article  Google Scholar 

  78. M. Basin, Y. Shtessel, F. Aldukali, Continuous finite- and fixed-time high-order regulators. J. Frankl. Inst. 253(18), 5001–5012 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  79. Z.-P. Jiang, Global tracking control of underactuated ships by Lyapunov’s direct method. Automatica 38(2), 301–309 (2002)

    Article  MATH  Google Scholar 

  80. Y. Wu, B. Wang, G. Zong, Finite-time tracking controller design for nonholonomic systems with extended chained form. IEEE Trans. Circuits Syst. II: Express Br. 52(11), 798–802 (2005)

    Article  Google Scholar 

  81. D.V. Dimarogonas, K.J. Kyriakopoulos, On the rendezvous problem for multiple nonholonomic agents. IEEE Trans. Autom. Control 52(5), 916–922 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  82. W. Dong, J.A. Farrell, Cooperative control of multiple nonholonomic mobile agents. IEEE Trans. Autom. Control 53(6), 1434–1448 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  83. M. Ou, H. Du, S. Li, Finite-time formation control of multiple nonholonomic mobile robots. Int. J. Robust Nonlinear Control 24(1), 140–165 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  84. H. Du, G. Wen, X. Yu, S. Li, M.Z. Chen, Finite-time consensus of multiple nonholonomic chained-form systems based on recursive distributed observer. Automatica 62, 236–242 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  85. B. Ning, Q.-L. Han, Prescribed finite-time consensus tracking for multi-agent systems with nonholonomic chained-form dynamics. IEEE Trans. Autom. Control 64(4), 1686–1693 (2019)

    Article  Google Scholar 

  86. X. Chu, Z. Peng, G. Wen, A. Rahmani, Robust fixed-time consensus tracking with application to formation control of unicycles. IET Control Theory Appl. 12(1), 53–59 (2018)

    Article  MathSciNet  Google Scholar 

  87. J. Ni, L. Liu, C. Liu, J. Liu, Fixed-time leader-following consensus for second-order multi-agent systems with input delay. IEEE Trans. Ind. Electron. 64(11), 8635–8646 (2017)

    Article  Google Scholar 

  88. Y. Yang, C. Hua, J. Li, X. Guan, Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system. Int. J. Control 90(12), 2711–2720 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  89. A. Nedić, A. Ozdaglar, P.A. Parrilo, Constrained consensus and optimization in multi-agent networks. IEEE Trans. Autom. Control 55(4), 922–938 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  90. D. Yuan, S. Xu, H. Zhao, Distributed primal-dual subgradient method for multiagent optimization via consensus algorithms. IEEE Trans. Syst. Man Cybern. Part B 41(6), 1715–1724 (2011)

    Article  Google Scholar 

  91. G. Shi, K.H. Johansson, Y. Hong, Reaching an optimal consensus: dynamical systems that compute intersections of convex sets. IEEE Trans. Autom. Control 58(3), 610–622 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  92. Q. Liu, J. Wang, A second-order multi-agent network for bound-constrained distributed optimization. IEEE Trans. Autom. Control 60(12), 3310–3315 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  93. S.S. Kia, J. Cortés, S. Martínez, Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication. Automatica 55, 254–264 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  94. Z. Qiu, S. Liu, L. Xie, Distributed constrained optimal consensus of multi-agent systems. Automatica 68, 209–215 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  95. S. Yang, Q. Liu, J. Wang, A multi-agent system with a proportional-integral protocol for distributed constrained optimization. IEEE Trans. Autom. Control 62(7), 3461–3467 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  96. S. Yang, Q. Liu, J. Wang, A collaborative neurodynamic approach to multiple-objective distributed optimization. IEEE Trans. Neural Netw. Learn. Syst. 29(4), 981–992 (2018)

    Article  Google Scholar 

  97. Q. Liu, S. Yang, J. Wang, A collective neurodynamic approach to distributed constrained optimization. IEEE Trans. Neural Netw. Learn. Syst. 28(8), 1747–1758 (2017)

    Article  MathSciNet  Google Scholar 

  98. S. Yang, Q. Liu, J. Wang, Distributed optimization based on a multiagent system in the presence of communication delays. IEEE Trans. Syste. Man Cybern.: Syst. 47(5), 717–728 (2017)

    Article  Google Scholar 

  99. Y. Shang, Finite-time scaled consensus through parametric linear iterations. Int. J. Syste. Sci. 48(10), 2033–2040 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  100. P. Lin, W. Ren, Y. Song, J. A. Farrell, Distributed optimization with the consideration of adaptivity and finite-time convergence, In Proceedings of the American Control Conference (ACC) (Oregon, USA, Portland, 2014), pp. 3177–3182

    Google Scholar 

  101. G. Notarstefano, K. Savla, F. Bullo, A. Jadbabaie, Maintaining limited-range connectivity among second-order agents, In Proceedings of the American Control Conference (ACC) (Minnesota, USA, Minneapolis, 2006), pp. 2124–2129

    Google Scholar 

  102. M. Ji, M. Egerstedt, Distributed coordination control of multiagent systems while preserving connectedness. IEEE Trans. Robot. 23(4), 693–703 (2007)

    Article  Google Scholar 

  103. D.V. Dimarogonas, K.J. Kyriakopoulos, Connectedness preserving distributed swarm aggregation for multiple kinematic robots. IEEE Trans. Robot. 24(5), 1213–1223 (2008)

    Article  Google Scholar 

  104. M.M. Zavlanos, G.J. Pappas, Distributed connectivity control of mobile networks. IEEE Trans. Robot. 24(6), 1416–1428 (2008)

    Article  Google Scholar 

  105. R.K. Williams, G.S. Sukhatme, Constrained interaction and coordination in proximity-limited multi-agent systems. IEEE Trans. Robot. 29(4), 930–944 (2013)

    Article  Google Scholar 

  106. Y.-L. Wang, Q.-L. Han, Network-based modelling and dynamic output feedback control for unmanned marine vehicles in network environments. Automatica 91, 43–53 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  107. Y.-L. Wang, Q.-L. Han, M.-R. Fei, C. Peng, Network-based T-S fuzzy dynamic positioning controller design for unmanned marine vehicles. IEEE Trans. Cybern. 48(9), 2750–2763 (2018)

    Article  Google Scholar 

  108. D. Yue, C. Peng, Q.-L. Han, Analysis and Synthesis of Networked Control Systems (Science Press, Beijing, P.R. China, 2007)

    Google Scholar 

  109. C. Peng, D. Yue, Q.-L. Han, Communication and Control for Networked Complex Systems (Springer, Berlin, 2015)

    Book  MATH  Google Scholar 

  110. D. Yue, E. Tian, Q.-L. Han, A delay system method for designing event-triggered controllers of networked control systems. IEEE Trans. Autom. Control 58(2), 475–481 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  111. C. Peng, Q.-L. Han, D. Yue, To transmit or not to transmit: a discrete event-triggered communication scheme for networked Takagi-Sugeno fuzzy systems. IEEE Trans. Fuzzy Syst. 21(1), 164–170 (2013)

    Article  Google Scholar 

  112. C. Peng, Q.-L. Han, A novel event-triggered transmission scheme and \(L_2\) control co-design for sampled-data control systems. IEEE Trans. Autom. Control 58(10), 2620–2626 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  113. C. Peng, Q.-L. Han, On designing a novel self-triggered sampling scheme for networked control systems with data losses and communication delays. IEEE Trans. Ind. Electron. 63(2), 1239–1248 (2016)

    Article  Google Scholar 

  114. X.-M. Zhang, Q.-L. Han, A decentralized event-triggered dissipative control scheme for systems with multiple sensors to sample the system outputs. IEEE Trans. Cybern. 46(12), 2745–2757 (2016)

    Article  Google Scholar 

  115. X. Ge, Q.-L. Han, Z. Wang, A dynamic event-triggered transmission scheme for distributed set-membership estimation over wireless sensor networks. IEEE Trans. Cybern. 49(1), 171–183 (2019)

    Article  Google Scholar 

  116. Y. Song, Y. Wang, J. Holloway, M. Krstic, Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time. Automatica 83, 243–251 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  117. Y. Liu, Y. Zhao, G. Chen, Finite-time formation tracking control for multiple vehicles: a motion planning approach. Int. J. Robust Nonlinear Control 26(14), 3130–3149 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  118. Y. Liu, Y. Zhao, W. Ren, G. Chen, Appointed-time consensus: Accurate and practical designs. Automatica 89, 425–429 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  119. L. Ma, Z. Wang, Q.-L. Han, H.-K. Lam, Variance-constrained distributed filtering for time-varying systems with multiplicative noises and deception attacks over sensor networks. IEEE Sens. J. 17(7), 2279–2288 (2017)

    Article  Google Scholar 

  120. L. Hu, Z. Wang, Q.-L. Han, X. Liu, State estimation under false data injection attacks: Security analysis and system protection. Automatica 87, 176–183 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  121. D. Ding, Z. Wang, Q.-L. Han, G. Wei, Security control for discrete-time stochastic nonlinear systems subject to deception attacks. IEEE Trans. Syst. Man Cybern.: Syst. 48(5), 779–789 (2018)

    Article  Google Scholar 

  122. D. Ding, Q.-L. Han, Y. Xiang, X. Ge, X.-M. Zhang, A survey on security control and attack detection for industrial cyber-physical systems. Neurocomputing 275, 1674–1683 (2018)

    Article  Google Scholar 

  123. S. Zhu, Q.-L. Han, C. Zhang, \(L_{1}\)-gain performance analysis and positive filter design for positive discrete-time markov jump linear systems: a linear programming approach. Automatica 50(8), 2098–2107 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  124. X. Ge, Q.-L. Han, Distributed event-triggered \(H_{\infty }\) filtering over sensor networks with communication delays. Inf. Sci. 291, 128–142 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  125. X. Yu, J. Xu, Y. Hong, S. Yu, Analysis of a class of discrete-time systems with power rule. Automatica 43(3), 562–566 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  126. H. Du, X. Yu, M. Chen, S. Li, Chattering-free discrete-time sliding mode control. Automatica 68, 87–91 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  127. D. Efimov, A. Polyakov, A. Levant, W. Perruquetti, Realization and discretization of asymptotically stable homogeneous systems. IEEE Trans. Autom. Control 62(11), 5962–5969 (2017)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zongyu Zuo .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zuo, Z., Han, QL., Ning, B. (2019). Introduction. In: Fixed-Time Cooperative Control of Multi-Agent Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-20279-8_1

Download citation

Publish with us

Policies and ethics