Research on consensus of multi-agent systems with and without input saturation constraints

doi:10.23919/JSEE.2021.000081

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (4): 947-955.doi: 10.23919/JSEE.2021.000081

收稿日期:2020-07-06 出版日期:2021-08-18 发布日期:2021-09-30

Research on consensus of multi-agent systems with and without input saturation constraints

Duo QI^1,²(), Junhua HU^3,*(), Xiaolong LIANG^1,²(), Jiaqiang ZHANG^1,²(), Zhihao ZHANG^1,²()

¹ Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China
² Shaanxi Province Lab. of Meta-Synthesis for Electronic & Information System, Xi’an 710051, China
³ Aeronautical Engineering College, Air Force Engineering University, Xi’an 710038, China

Received:2020-07-06 Online:2021-08-18 Published:2021-09-30
Contact: Junhua HU E-mail:qi33song@sina.com;56811366@ qq.com;afeu_lxl@sina.com;jiaqiang-z@163.com;408691252@qq.com
About author:|QI Duo was born in 1987. He received his M.S. degree of weapon system and application engineering, and Ph.D. degree of armament science and technology from the Aeronautical Engineering College, Air Force Engineering University in 2012 and 2016 respectively. He is a lecturer at the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation swarm technology and airspace management intelligence. E-mail: qi33song@sina.com||HU Junhua was born in 1980. He received his Ph.D. degree of armament science and technology from the Aeronautical Engineering College, Air Force Engineering University in 2008. Now he is an assistant professor in the Aeronautical Engineering College, Air Force Engineering University. His research interest is multi-agent system. E-mail: 56811366@ qq.com||LIANG Xiaolong was born in 1981. He received his M.S. degree of operational research and cybernetics, and Ph.D. degree of armament science and technology from the Air Force Engineering University. He is a professor in Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aircraft swarm technology, airspace management intelligence, and intelligent aviation system. E-mail: afeu_lxl@sina.com||ZHANG Jiaqiang was born in 1984. He received his M.S. degree of weapon system and application engineering, and Ph.D. degree of armament science and technology in the Aeronautical Engineering College, Air Force Engineering University in 2009 and 2012 respectively. He is a lecturer in the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation cluster technology and airspace management intelligence. E-mail: jiaqiang-z@163.com||ZHANG Zhihao was born in 1989. He received his M.S. degree of navigation engineering from Air Force Engineering University in 2014. He is a lecturer in the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation swarm technology and airspace management intelligence. E-mail: 408691252@qq.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61703427)

摘要/Abstract

Abstract:

In recent years, with the continuous development of multi-agent technology represented by unmanned aerial vehicle (UAV) swarm, consensus control has become a hot spot in academic research. In this paper, we put forward a discrete-time consensus protocol and obtain the necessary and sufficient conditions for the second-order consensus of the second-order multi-agent system with a fixed structure under the condition of no saturation input. The theoretical derivation verifies that the two eigenvalues of the Laplacian of the communication network matrix and the sampling period have an important effect on achieving consensus. Then we construct and verify sufficient conditions to achieve consensus under the condition of input saturation constraints. The results show that consensus can be achieved if velocity, position gain, and sampling period satisfy a set of inequalities related to the eigenvalues of the Laplacian matrix. Finally, the accuracy and validity of the theoretical results are proved by numerical simulations.

Key words: multi-agent system, consensus control, input constraint, distributed control

. [J]. Journal of Systems Engineering and Electronics, 2021, 32(4): 947-955.

Duo QI, Junhua HU, Xiaolong LIANG, Jiaqiang ZHANG, Zhihao ZHANG. Research on consensus of multi-agent systems with and without input saturation constraints[J]. Journal of Systems Engineering and Electronics, 2021, 32(4): 947-955.

图/表 6

参考文献 36

1	LU A Y, YANG G H Distributed consensus control for multi-agent systems under denial-of-service. Information Sciences, 2018, 439, 95- 107.
2	HU J P. Second-order event-triggered multi-agent consensus control. Proc. of the 31st Chinese Control Conference, 2012: 6339−6344.
3	DONG Y, XU S Y, HU X M Coordinated control with multiple dynamic leaders for uncertain Lagrangian systems via self-tuning adaptive distributed observer. International Journal of Robust and Nonlinear Control, 2016, 27 (16): 2708- 2721.
4	NI W, XIONG C, YANG J Leader-following consensus of high-order multi-agent linear systems with bounded transmission channels. International Journal of Systems Science, 2013, 44 (9): 1711- 1725. doi: 10.1080/00207721.2012.669867
5	BU X H, CUI L Z, HOU Z S, et al Formation control for a class of nonlinear multiagent systems using model-free adaptive iterative learning. International Journal of Robust and Nonlinear Control, 2017, 28 (4): 1402- 1412.
6	ZHANG J L, ZHANG H, FENG T Distributed optimal consensus control for nonlinear multiagent system with unknown dynamic. IEEE Trans. on Neural Networks and Learning Systems, 2018, 29 (8): 3339- 3348. doi: 10.1109/TNNLS.2017.2728622
7	SHEN D, ZHANG C, XU J X Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems. International Journal of Robust and Nonlinear Control, 2019, 29 (13): 4328- 4347. doi: 10.1002/rnc.4627
8	PENG X H, GENG Z Y Distributed observer-based leader-follower attitude consensus control for multiple rigid bodies using rotation matrices. International Journal of Robust and Nonlinear Control, 2019, 29 (14): 4755- 4774. doi: 10.1002/rnc.4649
9	OLFATI-SABER R, MURRAY R M Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. on Automatic Control, 2004, 49 (9): 1520- 1533. doi: 10.1109/TAC.2004.834113
10	REN W, BEARD R W Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Trans. on Automatic Control, 2005, 50 (5): 655- 661. doi: 10.1109/TAC.2005.846556
11	MOREAU L Stability of multiagent systems with time-dependent communication links. IEEE Trans. on Automatic Control, 2005, 50 (2): 169- 182. doi: 10.1109/TAC.2004.841888
12	PARK M J, KWON O M, PARK J H, et al Randomly changing leader-following consensus control for Markovian switching multi-agent systems with interval time-varying delays. Nonlinear Analysis: Hybrid Systems, 2014, 12, 117- 131. doi: 10.1016/j.nahs.2013.11.003
13	YAN Z P, YANG Z W, YUE L D, et al Discrete-time coordinated control of leader-following multiple AUVs under switching topologies and communication delays. Ocean Engineering, 2019, 172, 361- 372. doi: 10.1016/j.oceaneng.2018.12.018
14	DAI X S, WANG C, TIAN S P, et al Consensus control via iterative learning for distributed parameter models multi-agent systems with time-delay. Journal of the Franklin Institute, 2019, 356 (10): 5240- 5259. doi: 10.1016/j.jfranklin.2019.05.015
15	ZHANG W, ZENG J, YAN Z P, et al Consensus control of multiple AUVs recovery system under switching topologies and time delays. IEEE Access, 2019, 7, 119965- 119980. doi: 10.1109/ACCESS.2019.2935104
16	XIE X X, YANG Z, MU X W Observer-based consensus control of nonlinear multi-agent systems under semi-Markovian switching topologies and cyber attacks. International Journal of Robust and Nonlinear Control, 2020, 30 (14): 5510- 5528. doi: 10.1002/rnc.5088
17	SHANG Y L Consensus seeking over Markovian switching networks with time-varying delays and uncertain topologies. Applied Mathematics and Computation, 2016, 273, 1234- 1245. doi: 10.1016/j.amc.2015.08.115
18	ZHAN J Y, LI X Consensus of sampled-data multi-agent networking systems via model predictive control. Automatica, 2013, 49 (8): 2502- 2507. doi: 10.1016/j.automatica.2013.04.037
19	REN W, ATKINS E. Second-order consensus protocols in multiple vehicle systems with local interactions. Proc. of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 2005: 1−13.
20	YU W W, CHEN G, CAO M Some necessary and sufficient conditions for second-order consensus in multi-agent dynamical systems. Automatica, 2010, 46 (6): 1089- 1095. doi: 10.1016/j.automatica.2010.03.006
21	ZHANG Y, TIAN Y P Consentability and protocol design of multi-agent systems with stochastic switching topology. Automatica, 2009, 45 (5): 1195- 1201. doi: 10.1016/j.automatica.2008.11.005
22	XIE D M, WANG S K Consensus of second-order discrete-time multi-agent systems with fixed topology. Journal of Mathematical Analysis and Applications, 2012, 387 (1): 8- 16. doi: 10.1016/j.jmaa.2011.08.052
23	WANG X L, SU H S, WANG X F, et al An overview of coordinated control for multi-agent systems subject to input saturation. Perspectives in Science, 2016, 7, 133- 139. doi: 10.1016/j.pisc.2015.11.022
24	FAN M C, ZHANG H T, LIN Z Distributed semiglobal consensus with relative output feedback and input saturation under directed switching networks. IEEE Trans. on Circuits and Systems II: Express Briefs, 2015, 62 (8): 796- 800. doi: 10.1109/TCSII.2015.2433399
25	SU H, 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. on Circuits and Systems I: Regular Papers, 2013, 60 (7): 1881- 1889. doi: 10.1109/TCSI.2012.2226490
26	WANG B H, CHEN W S, ZHANG B S Semi-global robust tracking consensus for multi-agent uncertain systems with input saturation via metamorphic low-gain feedback. Automatica, 2019, 103, 363- 373. doi: 10.1016/j.automatica.2019.02.002
27	ZHAO Z Y, LIN Z L Global leader-following consensus of a group of general linear systems using bounded controls. Automatica, 2016, 68, 294- 304. doi: 10.1016/j.automatica.2016.01.027
28	MENG Z Y, ZHAO Z Y, LIN Z L On global leader-following consensus of identical linear dynamic systems subject to actuator saturation. Systems & Control Letters, 2013, 62 (2): 132- 142.
29	YANG T, MENG Z Y, DIMAROGONAS D V, et al. Global consensus in homogeneous networks of discrete-time agents subject to actuator saturation. Proc. of the European Control Conference, 2013: 244−249.
30	CHENG Z, ZHANG H T, FAN M C, et al Distributed consensus of multi-agent systems with input constraints: a model predictive control approach. IEEE Trans. on Circuits and Systems I: Regular Papers, 2015, 62 (3): 825- 834. doi: 10.1109/TCSI.2014.2367575
31	ZHONG Z Z, SUN L N, WANG J C, et al Consensus for first- and second-order discrete-time multi-agent systems with delays based on model predictive control schemes. Circuits Systems & Signal Processing, 2015, 34 (1): 127- 152.
32	LI Y, WEI W, XIANG J Consensus problems for linear time-invariant multi-agent systems with saturation constraints. IET Control Theory & Applications, 2011, 5 (6): 823- 829.
33	FENG Y Z, LU J W, XU S Y, et al Couple-group consensus for multi-agent networks of agents with discrete-time second-order dynamics. Journal of the Franklin Institute, 2013, 350 (10): 3277- 3292. doi: 10.1016/j.jfranklin.2013.07.004
34	HUANG N, DUAN Z S, CHEN G R Some necessary and sufficient conditions for consensus of second-order multi-agent systems with sampled position data. Automatica, 2016, 63, 148- 155. doi: 10.1016/j.automatica.2015.10.020
35	DONG X W, YU B C, SHI Z Y, et al Time-varying formation control for unmanned aerial vehicles: theories and applications. IEEE Trans. on Control Systems Technology, 2015, 23 (1): 340- 348. doi: 10.1109/TCST.2014.2314460
36	DONG X W, ZHOU Y, REN Z, et al Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying. IEEE Trans. on Industrial Electronics, 2017, 64 (6): 5014- 5024. doi: 10.1109/TIE.2016.2593656

Research on consensus of multi-agent systems with and without input saturation constraints

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 36

相关文章 0

编辑推荐

Metrics

本文评价