http://iet.metastore.ingenta.com
1887

Semi-global edge-consensus of linear discrete-time multi-agent systems with positive constraint and input saturation

Semi-global edge-consensus of linear discrete-time multi-agent systems with positive constraint and input saturation

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

, The authors study the semi-global edge-consensus of linear discrete-time multi-agent systems subject to edge state positive constraint and input saturation. By virtue of the positive system theory and low-gain feedback method, the distributed control protocols for undirected and directed networks are designed to guarantee the non-negative edge-consensus with input saturation. Then, sufficient conditions, which can guarantee the edge-consensus together with keeping the positive edge state constraint and avoiding the input saturation, are provided. Finally, two examples are presented to verify the theoretical results.

References

    1. 1)
      • 1. Valcher, M.E., Misra, P.: ‘On the stabilizability and consensus of positive homogeneous multi-agent dynamical systems’, IEEE Trans. Autom. Control, 2014, 59, (7), pp. 19361941.
    2. 2)
      • 2. Hong, Y., Hu, J., Gao, L.: ‘Tracking control for multi-agent consensus with an active leader and variable topology’, Automatica, 2006, 42, (7), pp. 11771182.
    3. 3)
      • 3. You, K., Xie, L.: ‘Network topology and communication data rate for consensusability of discrete-time multi-agent systems’, IEEE Trans. Autom. Control, 2011, 56, (10), pp. 22622275.
    4. 4)
      • 4. Yu, W.W., Chen, G.R., Cao, M., et al: ‘Second-order consensus for multi-agent systems with directed topologies and nonlinear dynamics’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2010, 40, (3), pp. 881891.
    5. 5)
      • 5. Xiao, F., Wang, L.: ‘Consensus problems for high-dimensional multi-agent systems’, IET Control Theory Appl., 2007, 1, (3), pp. 830837.
    6. 6)
      • 6. Li, T., Fu, M., Xie, L., et al: ‘Distributed consensus with limited communication data rate’, IEEE Trans. Autom. Control, 2011, 56, (2), pp. 279292.
    7. 7)
      • 7. Li, Z.K., Duan, Z.S., Chen, G.R., et al: ‘Consensus of multi-agent systems and synchronization of complex networks: a unified viewpoint’, IEEE Trans. Circuits Syst. I, Reg. Papers, 2010, 57, (1), pp. 213224.
    8. 8)
      • 8. Su, H.S., Ye, Y., Qiu, Y., et al: ‘Semi-global output consensus for discrete-time switching networked systems subject to input saturation and external disturbances’, IEEE Trans. Cybern., doi: 10.1109/TCYB.2018.2859436.
    9. 9)
      • 9. Long, M.K., Su, H.S., Liu, B.: ‘Group controllability of two-time-scale multi-agent networks’, J. Franklin Inst., 2018, 355, (13), pp. 60456061.
    10. 10)
      • 10. Long, M.K., Su, H.S., Liu, B.: ‘Second-order controllability of two-time-scale multi-agent systems’, Appl. Math. Comput., 2019, 343, pp. 299313.
    11. 11)
      • 11. Nedic, A., Ozdaglar, A., Parrilo, P.A.: ‘Constrained consensus and optimization in multi-agent networks’, IEEE Trans. Autom. Control, 2010, 55, (4), pp. 922938.
    12. 12)
      • 12. Tian, Y.P., Liu, C.L.: ‘Consensus of multi-agent systems with diverse pnput and communication delays’, IEEE Trans. Autom. Control, 2008, 53, (9), pp. 21222128.
    13. 13)
      • 13. Su, H.S., Chen, M.Z.Q., Wang, X.F., et al: ‘Semi-global observer-based leader-following consensus with input saturation’, IEEE Trans. Ind. Electron., 2014, 61, (6), pp. 28422850.
    14. 14)
      • 14. Palla, G., Barabási, A.L., Vicsek, T.: ‘Quantifying social group evolution’, Nature, 2007, 446, (7136), pp. 664667.
    15. 15)
      • 15. Slotine, J.J., Liu, Y.Y.: ‘Complex networks: the missing link’, Nat. Phys., 2012, 8, (8), pp. 512513.
    16. 16)
      • 16. Liu, Y.Y.: ‘Theoretical progress and practical challenges in controlling complex networks’, Natl. Sci. Rev., 2014, 1, (3), pp. 341343.
    17. 17)
      • 17. Su, H.S., Wu, H., Lam, J.: ‘Positive edge-consensus for nodal networks via output feedback’, IEEE Trans. Autom. Control, 2018, doi: 10.1109/TAC.2018.2845694.
    18. 18)
      • 18. Wu, H., Su, H.S.: ‘Observer-based consensus for positive multiagent systems with directed topology and nonlinear control input’, IEEE Trans. Syst. Man Cybern., Syst., 2018, doi: 10.1109/TSMC.2018.2852704.
    19. 19)
      • 19. Nepusz, T., Vicsek, T.: ‘Controlling edge dynamics in complex networks’, Nat. Phys., 2012, 8, (7), pp. 568573.
    20. 20)
      • 20. Herty, M., Klar, A.: ‘Modeling, simulation, and optimization of traffic flow networks’, SIAM J. Sci. Comput., 2003, 25, (3), pp. 10661087.
    21. 21)
      • 21. Hellmann, T., Staudigl, M.: ‘Evolution of social networks’, Eur. J. Oper. Res., 2014, 234, (3), pp. 583596.
    22. 22)
      • 22. Madani, R., Sojoudi, S., Lavaei, J.: ‘Convex relaxation for optimal power flow problem: mesh networks’, IEEE Trans. Power Syst., 2015, 30, (1), pp. 199211.
    23. 23)
      • 23. Li, Y., Canepa, E., Claudel, C.: ‘Optimal control of scalar conservation laws using linear/quadratic programming: application to transportation networks’, IEEE Trans. Control Netw. Syst., 2014, 1, (1), pp. 2839.
    24. 24)
      • 24. Wang, X.L., Su, H.S., Wang, L., et al: ‘Edge consensus on complex networks: a structural analysis’, Int. J. Control, 2016, 90, (8), pp. 129.
    25. 25)
      • 25. Wang, X.L., Su, H.S., Wang, X.F., et al: ‘Nonnegative edge quasi-consensus of networked dynamical systems’, IEEE Trans. Circuits Syst. II, Express Briefs, 2017, 64, (3), pp. 304308.
    26. 26)
      • 26. Wang, X.L., Su, H.S., Chen, M.Z.Q., et al: ‘Reaching non-negative edge consensus of networked dynamical systems’, IEEE Trans. Cybern., 2018, 48, (9), pp. 27122722.
    27. 27)
      • 27. Su, H.S., Wu, H., Chen, X., et al: ‘Positive edge consensus of complex networks’, IEEE Trans. Syst. Man Cybern., Syst., 2018, 48, (12), pp. 22422250.
    28. 28)
      • 28. Wu, H., Su, H.S.: ‘Discrete-time positive edge-consensus for undirected and directed nodal networks’, IEEE Trans. Circuits Syst. II, Express Briefs, 2018, 65, (2), pp. 221225.
    29. 29)
      • 29. Su, H.S., Wu, H., Chen, X.: ‘Observer-based discrete-time nonnegative edge synchronization of networked systems’, IEEE Trans. Neural Netw. Learn. Syst., 2017, 28, (10), pp. 24462455.
    30. 30)
      • 30. Chu, H.J., Yuan, J.Q., Zhang, W.D.: ‘Observer-based adaptive consensus tracking for linear multi-agent systems with input saturation’, IET Control Theory Appl., 2015, 9, (14), pp. 21242131.
    31. 31)
      • 31. Fan, M.C., Zhang, H.T., Lin, Z.: ‘Distributed semiglobal consensus with relative output feedback and input saturation under directed switching networks’, IEEE Trans. Circuits Syst. I, Reg. Papers, 2015, 60, (7), pp. 796800.
    32. 32)
      • 32. Su, H.S., Chen, M.Z.Q., Lam, J., et al: ‘Semi-global leader-following consensus of linear multi-agent systems with input saturation via low gain feedback’, IEEE Trans. Circuits Syst. I, Reg. Papers, 2013, 60, (7), pp. 18811889.
    33. 33)
      • 33. Chen, M.Z.Q., Zhang, L., Su, H.S., et al: ‘Stabilizing solution and parameter dependence of modified algebraic Riccati equation with application to discrete-time network synchronization’, IEEE Trans. Autom. Control, 2015, 61, (1), pp. 228233.
    34. 34)
      • 34. Su, H.S., Qiu, Y., Wang, L.: ‘Semi-global output consensus of discrete-time multi-agent systems with input saturation and external disturbances’, ISA Trans., 2017, 67, pp. 131139.
    35. 35)
      • 35. Teel, A.R.: ‘Semi-global stabilizability of linear null controllable systems with input nonlinearities’, IEEE Trans. Autom. Control, 1995, 40, (1), pp. 96100.
    36. 36)
      • 36. Lin, Z., Saberi, A., Stoorvogel, A.A.: ‘Semiglobal stabilization of linear discrete-time systems subject to input saturation via linear feedback an ARE-based approach’, IEEE Trans. Autom. Control, 1996, 41, (8), pp. 12031120.
    37. 37)
      • 37. Harary, F., Norman, R.Z.: ‘Some properties of line digraphs’, Rend. Circ. Math. Palermo, 1960, 9, (2), pp. 161168.
    38. 38)
      • 38. Godsil, C., Royle, G.: ‘Algebraic graph theory’ (Springer, New York, NY, USA, 2001).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2018.5266
Loading

Related content

content/journals/10.1049/iet-cta.2018.5266
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address