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Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems

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Abstract

Our study is concerned with the time-varying formation tracking problem for second-order multi-agent systems that are subject to unknown nonlinear dynamics and external disturbance, and the states of the followers form a predefined time-varying formation while tracking the state of the leader. The total uncertainty lumps the unknown nonlinear dynamics and the external disturbance, and is regarded as an extended state of the agent. To estimate the total uncertainty, we design an extended state observer (ESO). Then we propose a novel ESO based time-varying formation tracking protocol. It is proved that, under the proposed protocol, the ESO estimation error and the time-varying formation tracking error can be made arbitrarily small. An application to the target enclosing problem for multiple unmanned aerial vehicles (UAVs) verifies the effectiveness and superiority of the proposed approach.

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References

  • Bechlioulis CP, Rovithakis GA, 2017. Decentralized robust synchronization of unknown high order nonlinear multiagent systems with prescribed transient and steady state performance. IEEE Trans Autom Contr, 62(1):123–134. https://doi.org/10.1109/TAC.2016.2535102

    Article  MATH  Google Scholar 

  • Castañeda LA, Luviano-Juárez A, Chairez I, 2015. Robust trajectory tracking of a delta robot through adaptive active disturbance rejection control. IEEE Trans Contr Syst Technol, 23(4):1387–1398. https://doi.org/10.1109/TCST.2014.2367313

    Article  Google Scholar 

  • Chang XY, Li YL, Zhang WY, et al., 2015. Active disturbance rejection control for a flywheel energy storage system. IEEE Trans Ind Electron, 62(2):991–1001. https://doi.org/10.1109/TIE.2014.2336607

    Article  Google Scholar 

  • Chen LM, Li CJ, Mei J, et al., 2017. Adaptive cooperative formation-containment control for networked Euler-Lagrange systems without using relative velocity information. IET Contr Theory Appl, 11(9):1450–1458. https://doi.org/10.1049/iet-cta.2016.1185

    Article  MathSciNet  Google Scholar 

  • Chen YY, Wang ZZ, Zhang Y, et al., 2017a. A geometric extension design for spherical formation tracking control of second-order agents in unknown spatiotemporal flowfields. Nonl Dynam, 88(2):1173–1186. https://doi.org/10.1007/s11071-016-3303-2

    Article  MATH  Google Scholar 

  • Chen YY, Zhang Y, Wang ZZ, 2017b. An adaptive backstepping design for formation tracking motion in an unknown Eulerian specification flowfield. J Franklin Inst, 354(14):6217–6233. https://doi.org/10.1016/j.jfranklin.2017.07.020

    Article  MathSciNet  MATH  Google Scholar 

  • Cui RX, Ge SS, How BVE, et al., 2010. Leader-follower formation control of underactuated autonomous underwater vehicles. Ocean Eng, 37(17-18):1491–1502. https://doi.org/10.1016/j.oceaneng.2010.07.006

    Article  Google Scholar 

  • Dong XW, Yu BC, Shi ZY, et al., 2015. Time-varying formation control for unmanned aerial vehicles: theories and applications. IEEE Trans Contr Syst Technol, 23(1):340–348. https://doi.org/10.1109/TCST.2014.2314460

    Article  Google Scholar 

  • Dong XW, Xiang J, Han L, et al., 2017a. Distributed time-varying formation tracking analysis and design for second-order multi-agent systems. J Intell Robot Syst, 86(2):277–289. https://doi.org/10.1007/s10846-016-0421-5

    Article  Google Scholar 

  • Dong XW, Zhou Y, Ren Z, et al., 2017b. Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying. IEEE Trans Ind Electron, 64(6):5014–5024. https://doi.org/10.1109/TIE.2016.2593656

    Article  Google Scholar 

  • Du HB, Cheng MZQ, Wen GH, 2016. Leader-following attitude consensus for spacecraft formation with rigid and flexible spacecraft. J Guid Contr Dynam, 39(4):944–951. https://doi.org/10.2514/1.G001273

    Article  Google Scholar 

  • Freidovich LB, Khalil HK, 2008. Performance recovery of feedback-linearization-based designs. IEEE Trans Autom Contr, 53(10):2324–2334. https://doi.org/10.1109/TAC.2008.2006821

    Article  MathSciNet  MATH  Google Scholar 

  • Galzi D, Shtessel Y, 2006. UAV formations control using high order sliding modes. American Control Conf, p.4249–4254. https://doi.org/10.1109/ACC.2006.1657386

    Google Scholar 

  • Guo BZ, Zhao ZL, 2011. On the convergence of an extended state observer for nonlinear systems with uncertainty. Syst Contr Lett, 60(6):420–430. https://doi.org/10.1016/j.sysconle.2011.03.008

    Article  MathSciNet  MATH  Google Scholar 

  • Guo J, Yan GF, Lin ZY, 2010. Local control strategy for moving-target-enclosing under dynamically changing network topology. Syst Contr Lett, 59(10):654–661. https://doi.org/10.1016/j.sysconle.2010.07.010

    Article  MathSciNet  MATH  Google Scholar 

  • Han JQ, 2009. From PID to active disturbance rejection control. IEEE Trans Ind Electron, 56(3):900–906. https://doi.org/10.1109/TIE.2008.2011621

    Article  Google Scholar 

  • Herbst G, 2016. Practical active disturbance rejection control: bumpless transfer, rate limitation, and incremental algorithm. IEEE Trans Ind Electron, 63(3):1754–1762. https://doi.org/10.1109/TIE.2015.2499168

    Article  Google Scholar 

  • Hu WH, Camacho EF, Xie LH, 2018. Output feedback control based on state and disturbance estimation. https://arxiv.org/abs/1801.06058

    Google Scholar 

  • Isidori A, 1989. Nonlinear Control Systems. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-662-02581-9

    Book  Google Scholar 

  • Jiang TT, Huang CD, Guo L, 2015. Control of uncertain nonlinear systems based on observers and estimators. Automatica, 59:35–47. https://doi.org/10.1016/j.automatica.2015.06.012

    Article  MathSciNet  MATH  Google Scholar 

  • Khalil HK, 2002. Nonlinear Systems (3rd Ed.). Prentice Hall, New Jersey, USA.

    MATH  Google Scholar 

  • Leonard NE, Paley DA, Davis RE, et al., 2010. Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay. J Field Robot, 27(6):718–740. https://doi.org/10.1002/rob.20366

    Article  Google Scholar 

  • Li CJ, Chen LM, Guo YN, et al., 2018. Formationcontainment control for networked Euler-Lagrange systems with input saturation. Nonl Dynam, 91(2):1307–1320. https://doi.org/10.1007/s11071-017-3946-7

    Article  MATH  Google Scholar 

  • Li SB, Zhang J, Li XL, et al., 2017. Formation control of heterogeneous discrete-time nonlinear multi-agent systems with uncertainties. IEEE Trans Ind Electron, 64(6):4730–4740. https://doi.org/10.1109/TIE.2017.2674590

    Article  Google Scholar 

  • Li XX, Xie LH, 2018. Dynamic formation control over directed networks using graphical Laplacian approach. IEEE Trans Autom Contr, 63(11):3761–3774. https://doi.org/10.1109/TAC.2018.2798808

    Article  MathSciNet  MATH  Google Scholar 

  • Li ZK, Wen GH, Duan ZS, et al., 2015. Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs. IEEE Trans Autom Contr, 60(4):1152–1157. https://doi.org/10.1109/TAC.2014.2350391

    Article  MathSciNet  MATH  Google Scholar 

  • Liao F, Teo R, Wang JL, et al., 2017. Distributed formation and reconfiguration control of VTOL UAVs. IEEE Trans Contr Syst Technol, 25(1):270–277. https://doi.org/10.1109/TCST.2016.2547952

    Article  Google Scholar 

  • Lin ZY, Ding W, Yan GF, et al., 2013. Leader-follower formation via complex Laplacian. Automatica, 49(6):1900–1906. https://doi.org/10.1016/j.automatica.2013.02.055

    Article  MathSciNet  MATH  Google Scholar 

  • Liu Y, Jia YM, 2012. An iterative learning approach to formation control of multi-agent systems. Syst Contr Lett, 61(1):148–154. https://doi.org/10.1016/j.sysconle.2011.10.011

    Article  MathSciNet  MATH  Google Scholar 

  • Lotfi N, Zomorodi H, Landers RG, 2016. Active disturbance rejection control for voltage stabilization in open-cathode fuel cells through temperature regulation. Contr Eng Pract, 56:92–100. https://doi.org/10.1016/j.conengprac.2016.08.006

    Article  Google Scholar 

  • Lü J, Chen F, Chen GR, 2016. Nonsmooth leader-following formation control of nonidentical multi-agent systems with directed communication topologies. Automatica, 64:112–120. https://doi.org/10.1016/j.automatica.2015.11.004

    Article  MathSciNet  MATH  Google Scholar 

  • Meng DY, Jia YM, Du JP, et al., 2014. On iterative learning algorithms for the formation control of nonlinear multiagent systems. Automaitca, 50(1):291–295. https://doi.org/10.1016/j.automatica.2013.11.009

    Article  MATH  Google Scholar 

  • Meng ZY, Ren W, You Z, 2010. Distributed finite-time attitude containment control for multiple rigid bodies. Automatica, 46(12):2092–2099. https://doi.org/10.1016/j.automatica.2010.09.005

    Article  MathSciNet  MATH  Google Scholar 

  • Oh KK, Ahn HS, 2014. Formation control and network localization via orientation alignment. IEEE Trans Autom Contr, 59(2):540–545. https://doi.org/10.1109/TAC.2013.2272972

    Article  MathSciNet  MATH  Google Scholar 

  • Oh KK, Park MC, Ahn HS, 2015. A survey of multi-agent formation control. Automatica, 53:424–440. https://doi.org/10.1016/j.automatica.2014.10.022

    Article  MathSciNet  MATH  Google Scholar 

  • Peng ZH, Wang D, Chen ZY, et al., 2013. Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics. IEEE Trans Contr Syst Technol, 21(2):513–520. https://doi.org/10.1109/TCST.2011.2181513

    Article  Google Scholar 

  • Ran MP, Wang Q, Dong CY, et al., 2017a. Backstepping active disturbance rejection control: a delayed activation approach. IET Contr Theory Appl, 11(14):2336–2342. https://doi.org/10.1049/iet-cta.2016.1533

    Article  MathSciNet  Google Scholar 

  • Ran MP, Wang Q, Dong CY, 2017b. Active disturbance rejection control for uncertain nonaffine-in-control nonlinear systems. IEEE Trans Autom Contr, 62(11):5830–5836. https://doi.org/10.1109/TAC.2016.2641980

    Article  MathSciNet  MATH  Google Scholar 

  • Ren W, 2007. Consensus strategies for cooperative control of vehicle formations. IET Contr Theory Appl, 1(2):505–512. https://doi.org/10.1049/iet-cta:20050401

    Article  MathSciNet  Google Scholar 

  • Ren W, Sorensen N, 2008. Distributed coordination architecture for multi-robot formation control. Robot Auton Syst, 56(4):324–333. https://doi.org/10.1016/j.robot.2007.08.005

    Article  MATH  Google Scholar 

  • Wang JN, Xin M, 2013. Integrated optimal formation control of multiple unmanned aerial vehicles. IEEE Trans Contr Syst Technol, 21(5):1731–1744. https://doi.org/10.1109/TCST.2012.2218815

    Article  Google Scholar 

  • Wang Q, Ran MP, Dong CY, 2016. Robust partial integrated guidance and control for missiles via extended state observer. ISA Trans, 65:27–36. https://doi.org/10.1016/j.isatra.2016.08.017

    Article  Google Scholar 

  • Wang XH, Yadav V, Balakrishnan SN, 2007. Cooperative UAV formation flying with obstacle/collision avoidance. IEEE Trans Contr Syst Technol, 15(4):672–679. https://doi.org/10.1109/TCST.2007.899191

    Article  Google Scholar 

  • Yang AL, Naeem W, Irwin GW, et al., 2014. Stability analysis and implementation of a decentralized formation control strategy for unmanned vehicles. IEEE Trans Contr Syst Technol, 22(2):706–720. https://doi.org/10.1109/TCST.2013.2259168

    Article  Google Scholar 

  • Zhang HW, Lewis FL, 2012. Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics. Automatica, 48(7):1432–1439. https://doi.org/10.1016/j.automatica.2012.05.008

    Article  MathSciNet  MATH  Google Scholar 

  • Zheng Q, Gao LQ, Gao ZQ, 2012. On validation of extended state observer through analysis and experimentation. J Dynam Syst Meas Contr, 134(2):024505. https://doi.org/10.1115/1.4005364

    Article  Google Scholar 

  • Zhu B, Zaini AHB, Xie LH, 2017. Distributed guidance for interception by using multiple rotary-wing unmanned aerial vehicles. IEEE Trans Ind Electron, 64(7):5648–5656. https://doi.org/10.1109/TIE.2017.2677313

    Article  Google Scholar 

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Correspondence to Mao-Peng Ran.

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Project supported by the Delta-NTU Corporate Lab through the NRF Corporate Lab@University Scheme

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Ran, MP., Xie, LH. & Li, JC. Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems. Frontiers Inf Technol Electronic Eng 20, 76–87 (2019). https://doi.org/10.1631/FITEE.1800557

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