Networked multi-agent systems consist of interacting agents that locally exchange information, energy, or matter. Since these systems do not in general have a centralized architecture to monitor the activity of each agent, resilient distributed control system design for networked multi-agent systems is essential in providing high system performance, reliability, and operation in the presence of system uncertainties. An important class of such system uncertainties that can significantly deteriorate the achievable closed-loop system performance is sensor uncertainties, which can arise due to low sensor quality, sensor failure, sensor bias, or detrimental environmental conditions. This paper presents a novel distributed adaptive control architecture for networked multi-agent systems with undirected communication graph topologies to mitigate the effect of sensor uncertainties. Specifically, we consider agents having identical high-order, linear dynamics with agent interactions corrupted by unknown exogenous disturbances. We show that the proposed adaptive control architecture guarantees asymptotic stability of the closed-loop dynamical system when the exogenous disturbances are time-invariant and uniform ultimate boundedness when the exogenous disturbances are time-varying. Two numerical examples are provided to illustrate the efficacy of the proposed distributed adaptive control architecture.

References

1.
Olfati-Saber
,
R.
,
Fax
,
A.
, and
Murray
,
R. M.
,
2007
, “
Consensus and Cooperation in Networked Multi-Agent Systems
,”
IEEE Trans. Autom. Control
,
95
(
1
), pp.
215
233
.
2.
Shamma
,
J. S.
,
2007
,
Cooperative Control of Distributed Multi-Agent Systems
,
Wiley
, Hoboken, NJ.
3.
Mesbahi
,
M.
, and
Egerstedt
,
M.
,
2010
,
Graph Theoretic Methods in Multiagent Networks
,
Princeton University Press
,
Princeton, NJ
.
4.
Ren
,
W.
, and
Cao
,
Y.
,
2011
,
Distributed Coordination of Multi-Agent Networks: Emergent Problems, Models, and Issues
,
Springer Science & Business Media
, Heidelberg, Germany.
5.
Hou
,
Z.-G.
,
Cheng
,
L.
, and
Tan
,
M.
,
2009
, “
Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks
,”
IEEE Trans. Syst. Man Cybern., Part B
,
39
(
3
), pp.
636
647
.
6.
Das
,
A.
, and
Lewis
,
F. L.
,
2010
, “
Distributed Adaptive Control for Synchronization of Unknown Nonlinear Networked Systems
,”
Automatica
,
46
(
12
), pp.
2014
2021
.
7.
Yucelen
,
T.
, and
Egerstedt
,
M.
,
2012
, “
Control of Multiagent Systems Under Persistent Disturbances
,”
American Control Conference
, Montreal, QC, Canada, June 27–29, pp.
5264
5269
.
8.
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
.
9.
Yucelen
,
T.
, and
Johnson
,
E. N.
,
2013
, “
Control of Multivehicle Systems in the Presence of Uncertain Dynamics
,”
Int. J. Control
,
86
(
9
), pp.
1540
1553
.
10.
Vemuri
,
A. T.
,
2001
, “
Sensor Bias Fault Diagnosis in a Class of Nonlinear Systems
,”
IEEE Trans. Autom. Control
,
46
(
6
), pp.
949
954
.
11.
Zhang
,
X.
,
Parisini
,
T.
, and
Polycarpou
,
M. M.
,
2005
, “
Sensor Bias Fault Isolation in a Class of Nonlinear Systems
,”
IEEE Trans. Autom. Control
,
50
(
3
), pp.
370
376
.
12.
Bevly
,
D. M.
, and
Parkinson
,
B.
,
2007
, “
Cascaded Kalman Filters for Accurate Estimation of Multiple Biases, Dead-Reckoning Navigation, and Full State Feedback Control of Ground Vehicles
,”
IEEE Trans. Control Syst. Technol.
,
15
(
2
), pp.
199
208
.
13.
Grip
,
H. F.
,
Fossen
,
T.
,
Johansen
,
T. A.
, and
Saberi
,
A.
,
2012
, “
Attitude Estimation Using Biased Gyro and Vector Measurements With Time-Varying Reference Vectors
,”
IEEE Trans. Autom. Control
,
57
(
5
), pp.
1332
1338
.
14.
Massoumnia
,
M.-A.
,
Verghese
,
G. C.
, and
Willsky
,
A. S.
,
1989
, “
Failure Detection and Identification
,”
IEEE Trans. Autom. Control
,
34
(
3
), pp.
316
321
.
15.
Blanke
,
M.
, and
Schröder
,
J.
,
2006
,
Diagnosis and Fault-Tolerant Control
,
Springer
, Heidelberg, Germany.
16.
Pasqualetti
,
F.
,
Dorfler
,
F.
, and
Bullo
,
F.
,
2013
, “
Attack Detection and Identification in Cyber-Physical Systems
,”
IEEE Trans. Autom. Control
,
58
(
11
), pp.
2715
2729
.
17.
Fawzi
,
H.
,
Tabuada
,
P.
, and
Diggavi
,
S.
,
2014
, “
Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks
,”
IEEE Trans. Autom. Control
,
59
(
6
), pp.
1454
1467
.
18.
Sadikhov
,
T.
,
Haddad
,
W. M.
,
Goebel
,
R.
, and
Egerstedt
,
M.
,
2014
, “
Set-Valued Protocols for Almost Consensus of Multiagent Systems With Uncertain Interagent Communication
,”
American Control Conference
, Portland, OR, June 4–6, pp.
4002
4007
.
19.
Arabi
,
E.
,
Yucelen
,
T.
, and
Haddad
,
W. M.
,
2016
, “
Mitigating the Effects of Sensor Uncertainties in Networked Multiagent Systems
,”
American Control Conference
, pp.
5545
5550
.
20.
Godsil
,
C.
, and
Royle
,
G. F.
,
2013
,
Algebraic Graph Theory
,
Springer Science & Business Media
, Heidelberg, Germany.
21.
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
.
22.
Ma
,
C.-Q.
, and
Zhang
,
J.-F.
,
2010
, “
Necessary and Sufficient Conditions for Consensusability of Linear Multi-Agent Systems
,”
IEEE Trans. Autom. Control
,
55
(
5
), pp.
1263
1268
.
23.
Haddad
,
W. M.
, and
Chellaboina
,
V.
,
2008
,
Nonlinear Dynamical Systems and Control: A Lyapunov-Based Approach
,
Princeton University Press
,
Princeton, NJ
.
24.
Li
,
Z.
,
Liu
,
X.
,
Lin
,
P.
, and
Ren
,
W.
,
2011
, “
Consensus of Linear Multi-Agent Systems With Reduced-Order Observer-Based Protocols
,”
Syst. Control Lett.
,
60
(
7
), pp.
510
516
.
25.
Boyd
,
S. P.
,
El Ghaoui
,
L.
,
Feron
,
E.
, and
Balakrishnan
,
V.
,
1994
,
Linear Matrix Inequalities in System and Control Theory
,
SIAM
, Philadelphia, PA.
26.
Pomet
,
J.-B.
, and
Praly
,
L.
,
1992
, “
Adaptive Nonlinear Regulation: Estimation From the Lyapunov Equation
,”
IEEE Trans. Autom. Control
,
37
(
6
), pp.
729
740
.
27.
Khalil
,
H. K.
,
2002
,
Nonlinear Systems
,
Prentice Hall
,
Upper Saddle River, NJ
.
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