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SCIENCE CHINA Information Sciences, Volume 64 , Issue 3 : 132205(2021) https://doi.org/10.1007/s11432-019-2815-7

Observer-based self-triggered control for time-varying formation of multi-agent systems

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  • ReceivedDec 20, 2019
  • AcceptedFeb 9, 2020
  • PublishedFeb 7, 2021

Abstract


Acknowledgment

This work was partially supported by Fundamental Research Funds for the Central Universities (Grant No. FRF-GF-17-B46), National Natural Science Foundation of China (Grant Nos. 61703037, 61921004), and National Postdoctoral Program for Innovative Talents (Grant No. BX20200081). The authors would like to thank the anonymous associate editor and reviewers for their comments and suggestions.


References

[1] Tanner H G, Jadbabaie A, Pappas G J. Flocking in Fixed and Switching Networks. IEEE Trans Automat Contr, 2007, 52: 863-868 CrossRef Google Scholar

[2] Lin Z. Control design in the presence of actuator saturation: from individual systems to multi-agent systems. Sci China Inf Sci, 2019, 62: 026201 CrossRef Google Scholar

[3] Jin Z, Hu Y, Sun C. Event-triggered information fusion for networked systems with missing measurements and correlated noises. Neurocomputing, 2019, 332: 15-28 CrossRef Google Scholar

[4] Dong X, Yu B, Shi Z. Time-Varying Formation Control for Unmanned Aerial Vehicles: Theories and Applications. IEEE Trans Contr Syst Technol, 2015, 23: 340-348 CrossRef Google Scholar

[5] Zhang H, Feng G, Chen Q. Consensus of multi-agent systems with linear dynamics using event-triggered control. IET Contr Theor Appl, 2014, 57: 2275-2281 CrossRef Google Scholar

[6] Wang Q, Yu Y, Sun C. Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties. Neurocomputing, 2018, 272: 694-702 CrossRef Google Scholar

[7] Li Z, Ren W, Liu X. Distributed containment control of multi-agent systems with general linear dynamics in the presence of multiple leaders. Int J Robust NOnlinear Control, 2013, 23: 534-547 CrossRef Google Scholar

[8] Consolini L, Morbidi F, Prattichizzo D. Leader-follower formation control of nonholonomic mobile robots with input constraints. Automatica, 2008, 44: 1343-1349 CrossRef Google Scholar

[9] Lewis M A, Tan K H. Autonomous Robots, 1997, 4: 387-403 CrossRef Google Scholar

[10] Balch T, Arkin R C. Behavior-based formation control for multirobot teams. IEEE Trans Robot Automat, 1998, 14: 926-939 CrossRef Google Scholar

[11] Das A K, Fierro R, Kumar V. A vision-based formation control framework. IEEE Trans Robot Automat, 2002, 18: 813-825 CrossRef Google Scholar

[12] Oh K K, Park M C, Ahn H S. A survey of multi-agent formation control. Automatica, 2015, 53: 424-440 CrossRef Google Scholar

[13] Cai D, Zou H, Wang J. Event-triggered attitude tracking for rigid spacecraft. Sci China Inf Sci, 2019, 62: 222202 CrossRef Google Scholar

[14] Dimarogonas D V, Frazzoli E, Johansson K H. Distributed Event-Triggered Control for Multi-Agent Systems. IEEE Trans Automat Contr, 2012, 57: 1291-1297 CrossRef Google Scholar

[15] Ding L, Han Q L, Ge X. An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems. IEEE Trans Cybern, 2018, 48: 1110-1123 CrossRef Google Scholar

[16] Weng S, Yue D. Distributed event-triggered cooperative attitude control of multiple rigid bodies with leader-follower architecture. Int J Syst Sci, 2016, 47: 631-643 CrossRef ADS Google Scholar

[17] Wang W, Huang C, Cao J. Event-triggered control for sampled-data cluster formation of multi-agent systems. Neurocomputing, 2017, 267: 25-35 CrossRef Google Scholar

[18] Tang T, Liu Z X, Chen Z Q. Event-triggered formation control of multi-agent systems. In: Proceedings of the 30th Chinese Control Conference, Yantai, 2011. 4783--4786. Google Scholar

[19] Yi X L, Wei J Q, Dimarogonas D, et al. Formation control for multi-agent systems with connectivity preservation and event-triggered controllers. In: Proceedings of the 20th World Congress of the International-Federation-of-Automatic-Control (IFAC), Toulouse, 2017. 50: 9367--9373. Google Scholar

[20] Guo G, Ding L, Han Q L. A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems. Automatica, 2014, 50: 1489-1496 CrossRef Google Scholar

[21] Liu J, Zhang Y, Yu Y. Fixed-Time Event-Triggered Consensus for Nonlinear Multiagent Systems Without Continuous Communications. IEEE Trans Syst Man Cybern Syst, 2019, 49: 2221-2229 CrossRef Google Scholar

[22] Liu J, Zhang Y, Sun C. Fixed-time consensus of multi-agent systems with input delay and uncertain disturbances via event-triggered control. Inf Sci, 2019, 480: 261-272 CrossRef Google Scholar

[23] Ge X, Han Q L. Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism. IEEE Trans Ind Electron, 2017, 64: 8118-8127 CrossRef Google Scholar

[24] Li X, Dong X, Li Q. Event-triggered time-varying formation control for general linear multi-agent systems. J Franklin Institute, 2019, 356: 10179-10195 CrossRef Google Scholar

[25] Chu X, Peng Z, Wen G. Distributed formation tracking of multi-robot systems with nonholonomic constraint via event-triggered approach. Neurocomputing, 2018, 275: 121-131 CrossRef Google Scholar

[26] Sun N, Fang Y, Zhang X. Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs. Automatica, 2013, 49: 1318-1325 CrossRef Google Scholar

[27] Zhang H, Feng G, Yan H. Observer-Based Output Feedback Event-Triggered Control for Consensus of Multi-Agent Systems. IEEE Trans Ind Electron, 2014, 61: 4885-4894 CrossRef Google Scholar

[28] Yu H, Antsaklis P J. Output Synchronization of Networked Passive Systems With Event-Driven Communication. IEEE Trans Automat Contr, 2014, 59: 750-756 CrossRef Google Scholar

[29] Biggs N. Algebraic Graph Theory. Cambridge: Cambridge University Press, 1993. Google Scholar

[30] Dong X, Shi Z, Lu G. Time-varying output formation control for high-order linear time-invariant swarm systems. Inf Sci, 2015, 298: 36-52 CrossRef Google Scholar

[31] Dong X W. Formation and Containment Control for High-order Linear Swarm Systems. Berlin: Springer, 2015. Google Scholar

[32] Wei Ren , Beard R W. Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Trans Automat Contr, 2005, 50: 655-661 CrossRef Google Scholar

[33] Kucera V. A contribution to matrix quadratic equations. IEEE Trans Automat Contr, 1972, 17: 344-347 CrossRef Google Scholar

[34] Chen Z, Han Q L, Yan Y. How often should one update control and estimation: review of networked triggering techniques. Sci China Inf Sci, 2020, 63: 150201 CrossRef Google Scholar

[35] Xu Y, Wu Z G. Distributed Adaptive Event-Triggered Fault-Tolerant Synchronization for Multi-Agent Systems. IEEE Trans Ind Electron, 2020, : 1-1 CrossRef Google Scholar

[36] Xu Y, Fang M, Wu Z G. Input-Based Event-Triggering Consensus of Multiagent Systems Under Denial-of-Service Attacks. IEEE Trans Syst Man Cybern Syst, 2020, 50: 1455-1464 CrossRef Google Scholar

[37] Liu J, Zhang Y, Liu H. Robust event?triggered control of second?ørder disturbed leader?follower MASs: A nonsingular finite?time consensus approach. Int J Robust NOnlinear Control, 2019, 29: 4298-4314 CrossRef Google Scholar

[38] Liu J, Zhang Y, Yu Y. Fixed-Time Leader-Follower Consensus of Networked Nonlinear Systems via Event/Self-Triggered Control. IEEE Trans Neural Netw Learning Syst, 2020, : 1-9 CrossRef Google Scholar

  • Figure 1

    Undirected interaction topology emph G.

  • Figure 2

    (Color online) Formation error $z_i(t)$ $(i=1,2,\ldots,8)$ under the distributed event-triggered strategy with continuous communication. (a) $z_{i1}$ of each agent when $t\in[0,1]$; (b) $z_{i1}$ of each agent when $t\in[1.4,1.5]$; (c) $z_{i2}$ of each agent when $t\in[0,1]$; (d) $z_{i2}$ of each agent when $t\in[1.4,1.5]$; (e) $z_{i3}$ of each agent when $t\in[0,1]$; (f) $z_{i3}$ of each agent when $t\in[1.4,1.5]$.

  • Figure 3

    (Color online) Measurement error $e_i(t)$ $(i=1,2,\ldots,8)$ under the distributed event-triggered strategy with continuous communication. (a) $\|e_{i1}\|$ of each agent when $t\in[0,1]$; (b) $\|e_{i1}\|$ of each agent when $t\in[1.4,1.5]$; (c) $\|e_{i2}\|$ of each agent when $t\in[0,1]$; (d) $\|e_{i2}\|$ of each agent when $t\in[1.4,1.5]$; (e) $\|e_{i3}\|$ of each agent when $t\in[0,1]$; (f) $\|e_{i3}\|$ of each agent when $t\in[1.4,1.5]$.

  • Figure 4

    (Color online) Formation error $z_i(t)$ $(i=1,2,\ldots,8)$ under the self-triggered strategy with intermittent communication. (a) $z_{i1}$ of each agent when $t\in[0,1]$; (b) $z_{i1}$ of each agent when $t\in[1.4,1.5]$; (c) $z_{i2}$ of each agent when $t\in[0,1]$; (d) $z_{i2}$ of each agent when $t\in[1.4,1.5]$; (e) $z_{i3}$ of each agent when $t\in[0,1]$; (f) $z_{i3}$ of each agent when $t\in[1.4,1.5]$.

  • Figure 5

    (Color online) Measurement error $e_i(t)$ $(i=1,2,\ldots,8)$ under the self-triggered strategy with intermittent communication. (a) $\|e_{i1}\|$ of each agent when $t\in[0,1]$; (b) $\|e_{i1}\|$ of each agent when $t\in[1.4,1.5]$; (c) $\|e_{i2}\|$ of each agent when $t\in[0,1]$; (d) $\|e_{i2}\|$ of each agent when $t\in[1.4,1.5]$; (e) $\|e_{i3}\|$ of each agent when $t\in[0,1]$; (f) $\|e_{i3}\|$ of each agent when $t\in[1.4,1.5]$.

  • Table 1  

    Table 1The event-triggering times under the distributed event-triggered strategy

    Agent
    1 2 3 4 5 6 7 8
    Triggering times under condition (14) 71 83 86 72 142 118 72 87
    Triggering times under condition (15) 0 43 3 2 39 6 0 77
    Total 71 126 89 74 181 124 72 164
  • Table 2  

    Table 2The event-triggering times under the self-triggered strategy

    Agent
    1 2 3 4 5 6 7 8
    Triggering times under condition (59) 407 551 439 348 410 572 176 227
    Triggering times under condition (62) 5 0 8 2 11 4 7 0
    Total 412 551 447 350 421 576 183 227