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This paper investigates the convergence of fractional-order discrete-time multiagent systems with a leader and sampling delay by.using Hermite-Biehler theorem and the change of bilinearity. It is shown that such system can achieve convergence depending on.the sampling interval ℎ, the fractional-order , and the sampling delay and its interconnection topology. Finally, some numerical.simulations are given to illustrate the results
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Research Article
Networked Convergence of Fractional-Order Multiagent
Systems with a Leader and Delay
Yuntao Shi
1
and Junjun Zhang
2
1
Key Laboratory of Beijing for Field-Bus Technology & Automation, North China University of Technology, Beijing 100144, China
2
College of Science, North China University of Technology, Beijing 100144, China
Correspondence should be addressed to Yuntao Shi; shiyuntao@ncut.edu.cn
Received August ; Accepted October
Academic Editor: Michael Z. Q. Chen
Copyright © Y. Shi and J. Zhang. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
is paper investigates the convergence of fractional-order discrete-time multiagent systems with a leader and sampling delay by
using Hermite-Biehler theorem and the change of bilinearity. It is shown that such system can achieve convergence depending on
the sampling interval , the fractional-order ,andthesamplingdelayand its interconnection topology. Finally, some numerical
simulations are given to illustrate the results.
1. Introduction
Recently, more and more scholars focus on the coordinated
control [, ] of multiagent systems such as the consensus [–
] and the controllability [–]. However, most of the practi-
cal distribution systems are fractional order [–]. Recently,
with the development of society, fractional-order calculus
theory [–] is widely used to study the signal processing
and control, picture processing and articial intelligence,
and so on. e consensus of multiagent systems refers to
thefactthatagentsinthesystemcantransferinformation
and inuence each other according to a certain protocol or
algorithm, and eventually agents will tend to the consensus
behavior with the evolution of the time in []. In fact, for
most of multiagent systems, there widely exist time delays as
in []. So the property of multiagent systems with time delays
has always been the hot problem. In [], the authors studied
consensus of multiagent systems with heterogeneous delays
and leader-following with integer-order and continuous time.
In [], the paper considered the consensus of fractional-
order multiagent systems with sampling delays without the
leader.
However, for a complex environment, multiagent systems
with fractional-order can be better to describe some real
natural phenomena. Some basic issues of fractional-order
multiagent systems with time delay, such as the convergence,
arestilllackinginstudying.Specially,forafractional-order
multiagent system, which depends crucially on sampling
interval , the fractional-order ,anditsinterconnection
topology, therefore, it is more dicult to study the conver-
gence of the fractional-order multiagent system.
In this paper, we consider the convergence of fractional-
order discrete-time multiagent systems with a leader and
sampling delay. e leader plays the role of an external input
or signal to followers, and the followers update their states
basedontheinformationavailablefromtheirneighborsand
the leader. We will establish convergence conditions and
discuss relations among sampling interval , the fractional-
order ,itssamplingdelay,anditsinterconnectiontopology
of such network.
e remainder of this paper is organized as follows.
Section gives the model and some preliminaries. Section
presents the main results, and some simulations are given in
Section . Finally, Section gives the conclusion.
2. Preliminaries and Problem Statement
In this section, we introduce some useful concepts and
notations about the denition of fractional derivative [],
graph theory, and convergence of the multiagent systems.
Hindawi Publishing Corporation
Mathematical Problems in Engineering
Volume 2015, Article ID 314985, 6 pages
http://dx.doi.org/10.1155/2015/314985
Mathematical Problems in Engineering
Denote a directed graph as G = (V,E,)consisting of a
nonempty set of vertices V and E ={(,):,∈V}is a set
of edges, where (,)means an arc starts from and ends by .
If ,∈V and (,)∈E,thenwesaythatand are adjacent
or is a neighbor of .WemakeN
𝑖
={∈V : (,) ∈ E}
be the neighborhood set of node . =[
𝑖𝑗
]is an adjacency
matrix of graph G,where
𝑖𝑗
≥0is the coupling weight
between any two agents. =diag{
1
,
2
,...,
𝑛
}∈R
𝑛×𝑛
is a
degree matrix of G; its diagonal elements
𝑖
=∑
𝑗∈N
𝑖
𝑖𝑗
, =
1,2,...,, for the graph. en the Laplacian of the weighted
graph G is dened as
=−∈R
𝑛×𝑛
.
()
e agent isagloballyreachableagentifithaspathstoallof
other agents.
Denition 1 (see []). Assume that, for arbitrary given initial
values, if
lim
𝑡→∞
𝑖
(
)
−
𝑖
0
(
)
=0,
()
∈N,where
𝑖
() ∈ R
𝑛
is the state value of agent of
the multiagent system (∈N, N presents an index set
(1,2,...,)),
0
() ∈ R
𝑛
,and
𝑖
is a constant which is
changed with dierent . en we have that the multiagent
system is convergence.
Denition 2 (see [] (Grunwald-Letnikov)). For any real
number ,theintegerpartwrittenforis [].Ifthefunction
()has continuous (+1)-order derivative in the interval
[,]and equals []at last when >0,thenlet-order
derivative be
(𝛼)
(
)
= lim
ℎ→0
−𝛼
(𝑡−𝛼)/ℎ
𝑖=0
(
−1
)
𝑖
−
(
−
)
.
()
Consider a multiagent system is composed of +1agents,
where the rst (labeled from 1to )arefollowersandthe
remainder agent +1(labeled 0) is leader. e fractional-
order discrete-time multiagent system with a leader and
sampling time is described by
𝑖
(
+1
)
=
𝑖
(
)
+
𝛼
𝑖
(
)
,
0
(
+1
)
=
0
(
)
,
()
where
𝑖
(
)
=
𝑗∈N
𝑖
𝑖𝑗
𝑗
(
−1
)
−
𝑖
(
−1
)
+
𝑖0
0
(
−1
)
−
𝑖
(
−1
)
, ∈
[
,+
)
,
𝑗∈N
𝑖
𝑖𝑗
𝑗
(
)
−
𝑖
(
)
+
𝑖0
0
(
)
−
𝑖
(
)
, ∈
[
+
(
+1
)
+
)
,
()
∈ (0,1),
𝑖
∈ R
𝑛
is the state of follower (∈N, N
presents an index set (1,2,...,)), and
0
∈ R
𝑛
is the state
of the leader. N
𝑖
is the neighbor set of agent .
𝑖𝑗
≥0,
𝑖0
≥0represent the coupling information between followers
and from the leader to the followers, respectively; otherwise,
𝑖𝑗
=0and
𝑖0
=0; >0is the sampling interval and the
sampling interval is and the sampling delay is 0<<.
3. Main Results
Let () = (
1
(),
2
(),...,
𝑁
())
𝑇
and
0
() =
0
(+
1) be the state vectors of all the followers and the leader,
respectively. en such system can be rewritten as
(
+1
)
(
)
=
(
)
(
−1
)
+
𝛼
1
0
(
)
0
, ()
where
=
𝑛
−
𝛼
(
1−
)(
+
)
−
𝛼
(
+
)
𝑛
0
, ()
𝑁
is the ×identity matrix, =diag{
10
,
20
,...,
𝑁0
}∈
R
𝑁×𝑁
, 1 = (1,1,...,1)
𝑇
is the ×1identity matrix, and
=[
𝑖𝑗
]∈R
𝑁×𝑁
is Laplacian matrix with
𝑖𝑗
=
−
𝑖𝑗
,=,∈N
𝑖
,
𝑗∈N
𝑖
𝑖𝑗
,=,
0, otherwise.
()
Lemma 3 ((Hermite-Biehler theorem) []). Assume the
polynomial () =
0
+
1
+⋅⋅⋅+
𝑛
𝑛
,marking() =
()+().So()isHurwitzstableifandonlyiftheroots
of () = 0,
1
<
2
<⋅⋅⋅,and() = 0,
1
<
2
<⋅⋅⋅
satisfy
() (0)
(0)−
(0)(0)>0;
()
1
<
1
<
2
<
2
<⋅⋅⋅or
1
<
1
<
2
<
2
<
⋅⋅⋅.
Lemma 4 (see []).
2
= (),if∈R
𝑁×𝑁
is a
symmetrical matrix.
eorem 5. Suppose system (4) is a symmetrical and directly
weighted network and the leader is a globally reachable agent;
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