Constraint impulsive consensus of nonlinear multi-agent systems with impulsive time windows

Qiangqiang Zhang; Yiyan Han; Chuandong Li; Le You

doi:10.3934/math.2020238

AIMS Mathematics, 2020, 5(4): 3682-3701. doi: 10.3934/math.2020238. Research article

Export file:

Format

RIS(for EndNote,Reference Manager,ProCite)
BibTex
Text

Content

Citation Only
Citation and Abstract

Constraint impulsive consensus of nonlinear multi-agent systems with impulsive time windows

Qiangqiang Zhang, Yiyan Han, Chuandong Li, Le You

1 Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, PR China
2 School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, and Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China

Received: , Accepted: , Published:

Abstract Full Text(HTML) Figure/Table Related pages

In this paper, the constraint impulsive consensus problem of nonlinear multi-agent systems in directed network is discussed. Impulsive time windows are designed for solving consensus problem of multi-agent systems. Different from the traditional impulsive protocol with fixed impulsive intervals, the impulsive protocol with impulsive time windows, where the impulsive instants can be changed randomly, is more effective and flexible. In addition, saturation impulse is also considered to restrict the jumping value of impulse beyond the threshold. Based on algebraic graph theory, matrix theory, and convex combination analysis, some novel conditions of impulsive consensus have been proposed. Our main results indicate that constraint impulsive consensus of the multi-agent systems via impulsive time windows can be achieved if the nonlinear systems satisfy suitable conditions. Numerical simulations are presented to validate the effectiveness of theoretical results.

Figure/Table

Supplementary

Article Metrics

Keywords: constraint impulsive consensus; nonlinear multi-agent systems; saturation impulse; directed network; impulsive time windows

Citation: Qiangqiang Zhang, Yiyan Han, Chuandong Li, Le You. Constraint impulsive consensus of nonlinear multi-agent systems with impulsive time windows. AIMS Mathematics, 2020, 5(4): 3682-3701. doi: 10.3934/math.2020238

References:

1. H. G. Tanner, A. Jadbabaie, G. J. Pappas, Flocking in fixed and switching, IEEE Trans. Autom. Control, 52 (2007), 863-868.
2. Y. Cao, W. Yu, W. Ren, et al. An overview of recent progress in the study of distributed multi-agent coordination, IEEE Trans. Ind. Inform., 9 (2013), 427-438.
3. X. Li, X. Yang, T. Huang, Persistence of delayed cooperative models: Impulsive control method, Appl. Math. Comput., 342 (2019), 130-146.
4. Z. Guan, Y. Wu, G. Feng, Consensus analysis based on impulsive systems in multiagent networks, IEEE Trans. Circuits Syst. I, 59 (2012), 170-178.
5. Y. Han, C. Li, W. Zhang, et al. Impulsive consensus of multiagent systems with limited bandwidth based on encoding-decoding, IEEE Trans. Cybern., 50 (2020), 1-12.
6. A. Jadbabaie, J. Lin, A. S. Morse, Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Trans. Autom. Control, 48 (2003), 988-1001.
7. H. Du, G. Wen, G. Chen, et al. A distributed finite-time consensus algorithm for higher-order leaderless and leader-following multiagent systems, IEEE Trans. Syst. Man Cybern., 47 (2017), 1625-1634.
8. B. Cui, C. Zhao, T. Ma, et al. Leaderless and leader-following consensus of multi-agent chaotic systems with unknown time delays and switching topologies, Nonlinear Anal. Hybrid Syst., 24 (2017), 115-131.
9. D. Yang, X. Li, J. Qiu, Output tracking control of delayed switched systems via state-dependent switching and dynamic output feedback, Nonlinear Anal. Hybrid Syst., 32 (2019), 294-305.
10. X. Tan, J. Cao, X. Li, et al. Leader-following mean square consensus of stochastic multi-agent systems with input delay via event-triggered control, IET Control Theory Appl., 12 (2018), 299-309.
11. Q. Zhang, S. Chen, C. Yu, Impulsive consensus problem of second-order multi-agent systems with switching topologies, Commun. Nonlinear Sci. Numer. Simulat., 17 (2012), 9-16.
12. Z. Xu, C. Li, Y. Han, Leader-following fixed-time quantized consensus of multi-agent systems via impulsive control, J. Franklin Inst., 356 (2019), 441-456.
13. J. Hu, Y. Hong, Leader-following coordination of multi-agent systems with coupling time delays, Phys. A Stat. Mech. Appl., 374 (2007), 853-863.
14. F. Wang, Y. Yang, Leader-following exponential consensus of fractional order nonlinear multiagents system with hybrid time-varying delay: A heterogeneous impulsive method, Phys. A, 482 (2017), 158-172.
15. G. Wen, W. Yu, Y. Xia, et al. Distributed tracking of nonlinear multiagent systems under directed switching topology: An observer-based protocol, IEEE Trans. Syst. Man Cybern. Syst., 47 (2017), 869-881.
16. Z. Guan, Z. Liu, G. Feng, et al. Impulsive consensus algorithms for second-order multi-agent networks with sampled information, Automatica, 48 (2012), 1397-1404.
17. Y. Han, C. Li, Z. Zeng, et al. Exponential consensus of discrete-time non-linear multi-agent systems via relative state-dependent impulsive protocols, Neural Netw., 108 (2018) 192-201.
18. Y. Han, C. Li, Z. Zeng, Asynchronous event-based sampling data for impulsive protocol on consensus of non-linear multi-agent systems, Neural Netw., 115 (2019), 90-99.
19. X. Li, J. Shen, R. Rakkiyappan, Persistent impulsive effects on stability of functional differential equations with finite or infinite delay, Appl. Math. Comput., 329 (2018), 14-22.
20. X. Li, P. Li, Q. Wang, Input/output-to-state stability of impulsive switched systems, Syst. Control Lett., 116 (2018), 1-7.
21. X. Liu, C. Du, P. Lu, et al. Distributed event-triggered feedback consensus control with statedependent threshold for general linear multiagent systems, Internat. J. Robust Nonlinear Control, 27 (2017), 2589-2609.
22. Z. Cao, C. Li, X. Wang, et al. Finite-time consensus of linear multi-agent system via distributed event-triggered strategy, J. Franklin Inst., 355 (2018), 1338-1350.
23. T. Ma, Z. Zhang, C. Bing, Adaptive consensus of multi-agent systems via odd impulsive control, Neurocomputing, 321 (2018), 139-145.
24. Y. Wang, J. Yi, Consensus in second-order multi-agent systems via impulsive control using position-only information with heterogeneous delays, IET Control Theory Appl., 9 (2015), 336-345.
25. F. Jiang, D. Xie, M. Cao, Dynamic consensus of double-integrator multi-agent systems with aperiodic impulsive protocol and time-varying delays, IET Control Theory Appl., 11 (2017), 2879-2885.
26. Q. Zhu, J. Cao, R. Rakkiyappan, Exponential input-to-state stability of stochastic Cohen-Grossberg neural networks with mixed delays, Nonlinear Dyn., 79 (2014), 1085-1098.
27. Q. Zhu, pth Moment exponential stability of impulsive stochastic functional differential equations with Markovian switching, J. Franklin Inst., 351 (2014), 3965-3986.
28. Q. Zhu, J. Cao, Stability analysis of Markovian jump stochastic BAM neural networks with impulse control and mixed time delays, IEEE Trans. Neural Netw. Learn. Syst., 23 (2012), 467-479.
29. Y. Li, J. Lou, Z. Wang, et al. Synchronization of dynamical networks with nonlinearly coupling function under hybrid pinning impulsive controllers, J. Franklin Inst., 355 (2018), 6520-6530.
30. C. Huang, J. Lu, D. W. C. Ho, et al. Stabilization of probabilistic Boolean networks via pinning control strategy, Inf. Sci., 510 (2020), 205-217.
31. X. Wang, C. Li, T. Huang, et al. Impulsive control and synchronization of nonlinear system with impulse time window, Nonlinear Dynam., 78 (2014), 2837-2845.
32. Y. Feng, C. Li, Comparison system of impulsive control system with impulse time windows, J. Intell. Fuzzy Syst., 32 (2017), 4197-4204.
33. X. Wang, H. Wang, C. Li, et al. Synchronization of coupled delayed switched neural networks with impulsive time window, Nonlinear Dynam., 84 (2016), 1747-1757.
34. X. Wang, J. Yu, C. Li, et al. Robust stability of stochastic fuzzy delayed neural networks with impulsive time window, Neural Netw., 67 (2015), 84-91.
35. Y. Feng, C. Li, T. Huang, Periodically multiple state-jumps impulsive control systems with impulse time windows, Neurocomputing, 193 (2016), 7-13.
36. T. Ma, Z. Zhang, C. Bing, Variable impulsive consensus of nonlinear multi-agent systems, Nonlinear Anal. Hybrid Syst., 31 (2019), 1-18.
37. Li. L, C. Li, H. Li, An analysis and design for time-varying structures dynamical networks via state constraint impulsive control, Int. J. Control, 92 (2019), 2820-2828.
38. Li. L, C. Li, H. Li, Fully state constraint impulsive control for non-autonomous delayed nonlinear dynamic systems, Nonlinear Anal. Hybrid Syst., 29 (2019), 383-394.
39. X. Liao, L. Wang, P, Yu, Stability of dynamical systems, Elsevier, 2007.

show all references

Reader Comments

your name: * your email: *

Download full text in PDF

Associated material

Metrics