© The Institution of Engineering and Technology
Finite-time output consensus tracking problem of n-order multi-agent systems (MAS) with matched and unmatched disturbances is investigated in this study. First, a distributed protocol is given for the nominal MAS to achieve finite-time consensus tracking. Second, the unmatched disturbances in every follower are converted to the matched ones through a state transformation, and a finite-time disturbance observer is utilised to estimate its disturbances and their derivatives up to the (n − l)-order (1 ≤ l ≤ n) subject to the bounded (n − l + 1)-order derivatives. Finally, the combined observer-based protocol achieves the finite-time output consensus tracking in spite of all the disturbances. Finally, simulation results validate the scheme.
References
-
-
1)
-
1. Cao, Y., Yu, W., Ren, W., Chen, G.: ‘An overview of recent progress in the study of distributed multi-agent coordination’, IEEE Trans. Ind. Inf., 2013, 9, (1), pp. 427–438.
-
2)
-
42. Li, S., Sun, H., Yang, J., et al: ‘Continuous finite-time output regulation for disturbed systems under mismatching condition’, IEEE Trans. Autom. Control, 2015, 60, (1), pp. 277–282.
-
3)
-
15. Wang, L., Xiao, F.: ‘Finite-time consensus problems for networks of dynamic agents’, IEEE Trans. Autom. Control, 2010, 55, (4), pp. 950–955.
-
4)
-
12. Khoo, S., Xie, L., Man, Z.: ‘Robust finite-time consensus tracking algorithm for multirobot systems’, IEEE/ASME Trans. Mechatronics, 2009, 14, (2), pp. 219–228.
-
5)
-
18. Xiao, F., Wang, L., Chen, T.: ‘Finite-time consensus in networks of integrator-like dynamic agents with directional link failure’, IEEE Trans. Autom. Control, 2014, 59, (3), pp. 756–762.
-
6)
-
9. Cortes, J.: ‘Finite-time convergent gradient flows with applications to network consensus’, Automatica, 2006, 42, (11), pp. 1993–2000.
-
7)
-
10. Hui, Q.: ‘Finite-time rendezvous algorithms for mobile autonomous agents’, IEEE Trans. Autom. Control, 2011, 56, (1), pp. 207–211.
-
8)
-
22. Lu, Q., Han, Q., Liu, S.: ‘A finite-time particle swarm optimization algorithm for odor source localization’, Int. J. Control, 2014, 277, pp. 111–140.
-
9)
-
40. Bhat, S.P., Bernstein, D.S.: ‘Geometric homogeneity with applications to finite-time stability’, Math. Control Signals Syst., 2005, 17, (2), pp. 101–127.
-
10)
-
25. Cao, Y., Ren, W., Meng, Z.: ‘Decentralized finite-time sliding mode estimators and their applications in decentralized finite-time formation tracking’, Syst. Control Lett., 2010, 59, (9), pp. 522–529.
-
11)
-
27. Du, H., He, Y., Cheng, Y.: ‘Finite-time synchronization of a class of second-order nonlinear multi-agent systems using output feedback control’, IEEE Trans. Circuits Syst. I, Regul. Pap., 2014, 61, (6), pp. 1778–1788.
-
12)
-
36. Zhou, Y., Yu, X., Sun, C., et al: ‘Higher order finite-time consensus protocol for heterogeneous multi-agent systems’, Int. J. Control, 2015, 88, (2), pp. 285–294.
-
13)
-
32. Hong, Y., Xu, Y., Huang, J.: ‘Finite-time control for robot manipulators’, Syst. Control Lett., 2002, 46, (4), pp. 243–253.
-
14)
-
6. Yu, S., Yu, X., Shirinzadeh, B., et al: ‘Continuous finite-time control for robotic manipulators with terminal sliding mode’, Automatica, 2005, 41, (11), pp. 1957–1964.
-
15)
-
33. Moreno, J.A., Osorio, M.: ‘Strict Lyapunov functions for the supertwisting algorithm’, IEEE Trans. Autom. Control, 2012, 57, (4), pp. 1035–1040.
-
16)
-
8. Li, C., Qu, Z.: ‘Distributed finite-time consensus of nonlinear systems under switching topologies’, Automatica, 2014, 50, (6), pp. 1626–1631.
-
17)
-
41. Shtessel, Y.B., Shkolnikov, I.A., Levant, A.: ‘Smooth second-order sliding modes: missile guidance application’, Automatica, 2007, 43, (8), pp. 1470–1476.
-
18)
-
14. Ghasemi, M., Nersesov, S.: ‘Finite-time coordination in multi-agent systems using sliding mode control approach’, Automatica, 2014, 50, (4), pp. 1209–1216.
-
19)
-
3. He, W., Chen, G., Han, Q., et al: ‘Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control’, Inf. Sci., 2015.
-
20)
-
31. Du, H., Li, S., Qian, C.: ‘Finite-time attitude tracking control of spacecraft with application to attitude synchronization’, IEEE Trans. Autom. Control, 2011, 56, (11), pp. 2711–2717.
-
21)
-
26. Li, S., Wang, X.: ‘Finite-time consensus and collision avoidance control algorithms for multiple AUVs’, Automatica, 2013, 49, (11), pp. 3359–3367.
-
22)
-
35. Yu, H., Shen, Y., Xia, X.: ‘Adaptive finite-time consensus in multi-agent networks’, Syst. Control Lett., 2013, 62, (10), pp. 880–889.
-
23)
-
38. Shen, Q., Shi, P.: ‘Distributed command filtered backstepping consensus tracking control of nonlinear multiple-agent systems in strict feedback form’, Automatica, 2015, 53, pp. 120–124.
-
24)
-
37. Khalil, H.K.: ‘Nonlinear systems’ (Prentice-Hall, 2002, 3rd edn.).
-
25)
-
30. Li, S., Du, H., Lin, X.: ‘Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics’, Automatica, 2011, 47, (8), pp. 1706–1712.
-
26)
-
11. Chen, G., Lewis, F.L., Xie, L.: ‘Finite-time distributed consensus via binary control protocols’, Automatica, 2011, 47, (9), pp. 1962–1968.
-
27)
-
29. Huang, J., Wen, C., Wang, W., et al: ‘Adaptive finite-time consensus control of a group of uncertain nonlinear mechanical systems’, Automatica, 2015, 51, pp. 292–301.
-
28)
-
43. Buskes, G., Vn Rooij, A.: ‘Almost f-algebras: commutativity and the Cauchy–Schwarz inequality’ (Kluwer Academic, Netherlands, 2000).
-
29)
-
19. Cao, Y., Ren, W.: ‘Finite-time consensus for multi-agent networks with unknown inherent nonlinear dynamics’, Automatica, 2014, 50, (10), pp. 2648–2656.
-
30)
-
34. Yu, S., Long, X.: ‘Finite-time consensus for second-order multi-agent systems with disturbances by integral sliding mode’, Automatica, 2015, 54, pp. 158–165.
-
31)
-
7. Franceschelli, M., Giua, A., Pisano, A., et al: ‘Finite-time consensus with disturbance rejection by discontinuous local interactions in directed graphs’, IEEE Trans. Autom. Control, 2015, 60, (4), pp. 1133–1138.
-
32)
-
28. Lu, X., Chen, S., Lü, J.: ‘Finite-time tracking for double-integrator multi-agent systems with bounded control input’, IET Control Theory Appl., 2013, 7, (11), pp. 1562–1573.
-
33)
-
2. Olfati-Saber, R., Fax, A., Murray, R.M.: ‘Consensus and cooperation in networked multi-agent systems’, Proc. IEEE, 2007, 95, (1), pp. 215–233.
-
34)
-
17. Lu, X., Lu, R., Chen, S., et al: ‘Finite-time distributed tracking control for multi-agent systems with a virtual leader’, IEEE Trans. Circuits Syst. I, Regul. Pap., 2013, 60, (2), pp. 352–362.
-
35)
-
5. Ding, L., Han, Q., Guo, G.: ‘Network-based leader-following consensus for distributed multi-agent systems’, Automatica, 2013, 49, (7), pp. 2281–2286.
-
36)
-
23. Guan, Z., Sun, F., Wang, Y., et al: ‘Finite-time consensus for leader-following second-order multi-agent networks’, IEEE Trans. Circuits Syst. I, Regul. Pap., 2012, 59, (11), pp. 2646–2654.
-
37)
-
13. Meng, Z., Ren, W., You, Z.: ‘Distributed finite-time attitude containment control for multiple rigid bodies’, Automatica, 2010, 46, (12), pp. 2092–2099.
-
38)
-
39. Wang, W., Huang, J., Wen, C., et al: ‘Distributed adaptive control for consensus tracking with application to formation control of nonholonomic mobile robots’, Automatica, 2014, 50, (4), pp. 1254–1263.
-
39)
-
24. Zhao, Y., Duan, Z., Wen, G., et al: ‘Distributed finite-time tracking control for multi-agent systems: an observer-based approach’, Syst. Control Lett., 2013, 62, (1), pp. 22–28.
-
40)
-
21. Lu, Q., Han, Q., Xie, X., et al: ‘A finite-time motion control strategy for odor source localization’, IEEE Trans. Ind. Electron., 2014, 61, (10), pp. 5419–5430.
-
41)
-
20. Liu, H., Cheng, L., Tan, M., et al: ‘Distributed exponential finite-time coordination of multi-agent systems: containment control and consensus’, Int. J. Control, 2015, 88, (2), pp. 237–247.
-
42)
-
4. Guo, G., Ding, L., Han, Q.: ‘A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems’, Automatica, 2014, 50, (5), pp. 1489–1496.
-
43)
-
16. Hui, Q., Haddad, W.M., Bhat, S.P.: ‘Finite-time semistability and consensus for nonlinear dynamical networks’, IEEE Trans. Autom. Control, 2008, 53, (8), pp. 1887–1890.
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