Abstract

In this paper, a set-membership filtering-based leader–follower synchronization protocol for discrete-time linear multi-agent systems is proposed, wherein the aim is to make the agents synchronize with a leader. The agents, governed by identical high-order discrete-time linear dynamics, are subject to unknown-but-bounded input disturbances. In terms of its own state information, each agent only has access to measured outputs that are corrupted with unknown-but-bounded output disturbances. Also, the initial states of the agents are unknown. To deal with all these unknowns (or uncertainties), a set-membership filter (or state estimator), having the “correction-prediction” form of a standard Kalman filter, is formulated. We consider each agent to be equipped with this filter that estimates the state of the agent and consider the agents to be able to share the state estimate information with the neighbors locally. The corrected state estimates of the agents are utilized in the local control law design for synchronization. Under appropriate conditions, the global disagreement error between the agents and the leader is shown to be bounded. An upper bound on the norm of the global disagreement error is calculated and shown to be monotonically decreasing. Finally, a simulation example is included to illustrate the effectiveness of the proposed leader–follower synchronization protocol.

References

1.
Ren
,
W.
, and
Beard
,
R. W.
,
2008
,
Distributed Consensus in Multi-Vehicle Cooperative Control
,
Springer
, London.
2.
Fax
,
J. A.
, and
Murray
,
R. M.
,
2004
, “
Information Flow and Cooperative Control of Vehicle Formations
,”
IEEE Trans. Autom. Control
,
49
(
9
), pp.
1465
1476
.10.1109/TAC.2004.834433
3.
Murray
,
R. M.
,
2007
, “
Recent Research in Cooperative Control of Multivehicle Systems
,”
ASME J. Dyn. Syst. Meas. Control
,
129
(
5
), pp.
571
583
.10.1115/1.2766721
4.
Li
,
Z.
,
Duan
,
Z.
,
Chen
,
G.
, and
Huang
,
L.
,
2009
, “
Consensus of Multiagent Systems and Synchronization ofComplex Networks: A Unified Viewpoint
,”
IEEE Trans. Circuits Syst. I
,
57
(
1
), pp.
213
224
.10.1109/TCSI.2009.2023937
5.
Wu
,
J.
,
Ugrinovskii
,
V.
, and
Allgöwer
,
F.
,
2014
, “
Cooperative Estimation for Synchronization of Heterogeneous Multi-Agent Systems Using Relative Information
,”
IFAC Proc. Vol.
,
47
(
3
), pp.
4662
4667
.10.3182/20140824-6-ZA-1003.01938
6.
Bhusal
,
R.
, and
Subbarao
,
K.
,
2019
, “
Sensitivity Analysis of Cooperating Multi-Agent Systems With Uncertain Connection Weights
,” American Control Conference (
ACC
), Philadelphia, PA, July 10–12, pp.
4024
4029
.10.23919/ACC.2019.8815336
7.
Trentelman
,
H. L.
,
Takaba
,
K.
, and
Monshizadeh
,
N.
,
2013
, “
Robust Synchronization of Uncertain Linear Multi-Agent Systems
,”
IEEE Trans. Autom. Control
,
58
(
6
), pp.
1511
1523
.10.1109/TAC.2013.2239011
8.
Wang
,
X.
,
Zhu
,
J.
, and
Cheng
,
Z.
,
2015
, “
Synchronization Reachable Topology and Synchronization of Discrete-Time Linear Multi-Agent Systems
,”
IEEE Trans. Autom. Control
,
60
(
7
), pp.
1927
1932
.10.1109/TAC.2014.2362990
9.
Back
,
J.
, and
Kim
,
J.-S.
,
2017
, “
Output Feedback Practical Coordinated Tracking of Uncertain Heterogeneous Multi-Agent Systems Under Switching Network Topology
,”
IEEE Trans. Autom. Control
,
62
(
12
), pp.
6399
6406
.10.1109/TAC.2017.2651166
10.
Li
,
Z.
,
Wen
,
G.
,
Duan
,
Z.
, and
Ren
,
W.
,
2015
, “
Designing Fully Distributed Consensus Protocols for Linear Multi-Agent Systems With Directed Graphs
,”
IEEE Trans. Autom. Control
,
60
(
4
), pp.
1152
1157
.10.1109/TAC.2014.2350391
11.
Lewis
,
F. L.
,
Cui
,
B.
,
Ma
,
T.
,
Song
,
Y.
, and
Zhao
,
C.
,
2016
, “
Heterogeneous Multi-Agent Systems: Reduced-Order Synchronization and Geometry
,”
IEEE Trans. Autom. Control
,
61
(
5
), pp.
1391
1396
.10.1109/TAC.2015.2471716
12.
Arabi
,
E.
,
Yucelen
,
T.
, and
Haddad
,
W. M.
,
2017
, “
Mitigating the Effects of Sensor Uncertainties in Networked Multi-Agent Systems
,”
ASME J. Dyn. Syst. Meas. Control
,
139
(
4
), p.
041003
.10.1115/1.4035092
13.
Silvestre
,
D.
,
Rosa
,
P.
,
Cunha
,
R.
,
Hespanha
,
J. P.
, and
Silvestre
,
C.
,
2013
, “
Gossip Average Consensus in a Byzantine Environment Using Stochastic Set-Valued Observers
,”
52nd IEEE Conference on Decision and Control
, Florence, Italy,
Dec. 10–13
, pp.
4373
4378
.10.1109/CDC.2013.6760562
14.
Silvestre
,
D.
,
Rosa
,
P.
,
Hespanha
,
J. P.
, and
Silvestre
,
C.
,
2014
, “
Finite-Time Average Consensus in a Byzantine Environment Using Set-Valued Observers
,”
American Control Conference
, Portland, OR,
June 4–6
, pp.
3023
3028
.10.1109/ACC.2014.6859426
15.
Valcher
,
M. E.
, and
Misra
,
P.
,
2014
, “
On the Consensus and Bipartite Consensus in High-Order Multi-Agent Dynamical Systems With Antagonistic Interactions
,”
Syst. Control Lett.
,
66
, pp.
94
103
.10.1016/j.sysconle.2014.01.006
16.
Hengster-Movric
,
K.
,
You
,
K.
,
Lewis
,
F. L.
, and
Xie
,
L.
,
2013
, “
Synchronization of Discrete-Time Multi-Agent Systems on Graphs Using Riccati Design
,”
Automatica
,
49
(
2
), pp.
414
423
.10.1016/j.automatica.2012.11.038
17.
Zhang
,
H.
,
Lewis
,
F. L.
, and
Das
,
A.
,
2011
, “
Optimal Design for Synchronization of Cooperative Systems: State Feedback, Observer and Output Feedback
,”
IEEE Trans. Autom. Control
,
56
(
8
), pp.
1948
1952
.10.1109/TAC.2011.2139510
18.
Peng
,
Z.
,
Wang
,
D.
,
Zhang
,
H.
,
Sun
,
G.
, and
Wang
,
H.
,
2013
, “
Distributed Model Reference Adaptive Control for Cooperative Tracking of Uncertain Dynamical Multi-Agent Systems
,”
IET Control Theory Appl.
,
7
(
8
), pp.
1079
1087
.10.1049/iet-cta.2012.0765
19.
Anderson
,
B. D.
, and
Moore
,
J. B.
,
1979
,
Optimal Filtering
,
Prentice Hall
, Englewood Cliffs, NJ.
20.
Polyak
,
B. T.
,
Nazin
,
S. A.
,
Durieu
,
C.
, and
Walter
,
E.
,
2004
, “
Ellipsoidal Parameter or State Estimation Under Model Uncertainty
,”
Automatica
,
40
(
7
), pp.
1171
1179
.10.1016/j.automatica.2004.02.014
21.
Chabane
,
S. B.
,
Maniu
,
C. S.
,
Alamo
,
T.
,
Camacho
,
E. F.
, and
Dumur
,
D.
,
2014
, “
A New Approach for Guaranteed Ellipsoidal State Estimation
,”
IFAC Proc. Vol.
,
47
(
3
), pp.
6533
6538
.10.3182/20140824-6-ZA-1003.01629
22.
Shamma
,
J. S.
, and
Tu
,
K.-Y.
,
1997
, “
Approximate Set-Valued Observers for Nonlinear Systems
,”
IEEE Trans. Autom. Control
,
42
(
5
), pp.
648
658
.10.1109/9.580870
23.
El Ghaoui
,
L.
, and
Calafiore
,
G.
,
2001
, “
Robust Filtering for Discrete-Time Systems With Bounded Noise and Parametric Uncertainty
,”
IEEE Trans. Autom. Control
,
46
(
7
), pp.
1084
1089
.10.1109/9.935060
24.
Yang
,
F.
, and
Li
,
Y.
,
2009
, “
Set-Membership Filtering for Discrete-Time Systems With Nonlinear Equality Constraints
,”
IEEE Trans. Autom. Control
,
54
(
10
), pp.
2480
2486
.10.1109/TAC.2009.2029403
25.
Yang
,
F.
, and
Li
,
Y.
,
2009
, “
Set-Membership Filtering for Systems With Sensor Saturation
,”
Automatica
,
45
(
8
), pp.
1896
1902
.10.1016/j.automatica.2009.04.011
26.
Wei
,
G.
,
Liu
,
S.
,
Song
,
Y.
, and
Liu
,
Y.
,
2015
, “
Probability-Guaranteed Set-Membership Filtering for Systems With Incomplete Measurements
,”
Automatica
,
60
, pp.
12
16
.10.1016/j.automatica.2015.06.037
27.
Xiao
,
F.
, and
Wang
,
L.
,
2012
, “
Asynchronous Rendezvous Analysis Via Set-Valued Consensus Theory
,”
SIAM J. Control Optim.
,
50
(
1
), pp.
196
221
.10.1137/100801202
28.
Munz
,
U.
,
Papachristodoulou
,
A.
, and
Allgower
,
F.
,
2012
, “
Delay Robustness in Non-Identical Multi-Agent Systems
,”
IEEE Trans. Autom. Control
,
57
(
6
), pp.
1597
1603
.10.1109/TAC.2011.2178336
29.
Garulli
,
A.
, and
Giannitrapani
,
A.
,
2011
, “
Analysis of Consensus Protocols With Bounded Measurement Errors
,”
Syst. Control Lett.
,
60
(
1
), pp.
44
52
.10.1016/j.sysconle.2010.10.005
30.
Sadikhov
,
T.
,
Haddad
,
W. M.
,
Yucelen
,
T.
, and
Goebel
,
R.
,
2017
, “
Approximate Consensus of Multiagent Systems With Inaccurate Sensor Measurements
,”
ASME J. Dyn. Syst. Meas. Control
,
139
(
9
), p.
091003
.10.1115/1.4036031
31.
Ge
,
X.
,
Han
,
Q.-L.
, and
Yang
,
F.
,
2017
, “
Event-Based Set-Membership Leader-Following Consensus of Networked Multi-Agent Systems Subject to Limited Communication Resources and Unknown-but-Bounded Noise
,”
IEEE Trans. Ind. Electron.
,
64
(
6
), pp.
5045
5054
.10.1109/TIE.2016.2613929
32.
Jiang
,
Z.-P.
, and
Wang
,
Y.
,
2001
, “
Input-to-State Stability for Discrete-Time Nonlinear Systems
,”
Automatica
,
37
(
6
), pp.
857
869
.10.1016/S0005-1098(01)00028-0
33.
Lazar
,
M.
,
Heemels
,
W. P. M. H.
, and
Teel
,
A. R.
,
2013
, “
Further Input-to-State Stability Subtleties for Discrete-Time Systems
,”
IEEE Trans. Autom. Control
,
58
(
6
), pp.
1609
1613
.10.1109/TAC.2012.2231611
34.
Bhattacharjee
,
D.
, and
Subbarao
,
K.
,
2020
, “
Set-Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization
,” eprint arXiv:2001.06562v2.
35.
Vandenberghe
,
L.
, and
Boyd
,
S.
,
1996
, “
Semidefinite Programming
,”
SIAM Rev.
,
38
(
1
), pp.
49
95
.10.1137/1038003
36.
Sontag
,
E. D.
,
2003
, “
A Remark on the Converging-Input Converging-State Property
,”
IEEE Trans. Autom. Control
,
48
(
2
), pp.
313
314
.10.1109/TAC.2002.808490
37.
Löfberg
,
J.
,
2004
, “
Yalmip: A Toolbox for Modeling and Optimization in Matlab
,”
Proceedings of the CACSD Conference
, Vol.
3
,
Taipei, Taiwan
, Portland, OR, Sept. 2–4, pp. 284–289.10.1109/CACSD.2004.1393890
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