Stabilization of primal and dual positive switched systems and
application to T-S fuzzy systems
ZHANG Junfeng
1
, MA Linli
1
, ZHOU Shaosheng
1,2
, CHEN Yun
1,2
1. Institute of Information and Control, Automation, Hangzhou Dianzi Univeristy, Hangzhou, 310018, P. R. China
E-mail: jfz5678@126.com, malinlity@163.com
2. Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Hangzhou, 310018, P. R. China
E-mail: sszhou@hdu.edu.cn, cloudscy@hdu.edu.cn
Abstract: This paper is concerned with stabilization of primal and dual positive switched systems and T-S fuzzy systems. State-
feedback stabilization of primal and dual positive switched systems is first addressed. All present conditions can be described
via linear programming. An implementable algorithm is given to increase the feasibility of the linear programming problems.
It is shown that, a switched linear copositive Lyapunov function of dual positive switched systems can be established, and
the controller of the dual systems can be also used to stabilize the primal systems. Then, the proposed design is applied to
primal and dual positive T-S fuzzy systems. A fuzzy linear copositive Lyapunov function for dual positive T-S fuzzy systems is
constructed, and stabilization of primal and dual positive T-S fuzzy systems is solved. The results obtained in this paper reduce
the conservatism of existing results on positive switched systems and T-S fuzzy systems based on common linear copositive
Lyapunov functions. Two illustrative examples verify the findings of theory.
Key Words: Positive switched systems; Positive T-S fuzzy systems; Linear programming
1 Introduction
Positive systems are an important class of systems that
arises frequently in many practical applications, for instance,
biology, communications, economics, population level, and
in other fields. Since these practical systems mentioned
above involve quantities that are intrinsically nonnegative,
the positivity assumption is a natural one. Past years have
witnessed an increasing interest in the class of systems.
More information about this class of systems can be found
in [1–4].
Positive switched systems (PSSs) consist of positive sub-
systems and a switching signal specifying the switching
takes place among the subsystems. There have many practi-
cal systems that can be modeled by PSSs such as network-
s employing TCP [5, 6], formation flying [7], and medical
treatment [8], to list a few. It has been shown that a lin-
ear copositive Lyapunov function is powerful for solving
corresponding problems of positive systems. Accordingly,
a common linear copositive Lyapunov function [9, 10] and
multiple linear copositive Lyapunov functions [11–14] have
been constructed to study stability, stabilization, and obser-
vation of PSSs. The notation of switched quadratic Lya-
punov function was introduced in [15] to study stability and
stabilization of switched systems (not positive). A switched
Lyapunov function is indeed a piecewise Lyapunov function
and the switching of the systems is arbitrary under such a
function. For PSSs, the concept of a switched linear copos-
itive Lyapunov function was first proposed in [16], where
several equivalent conditions for stability were established.
Some new switched linear copositive Lyapunov function-
based stability conditions of PSSs were given in [17].
This work was supported in part by the National Nature Science
Foundation of China (61503107, U1509205), the Zhejiang Provincial
Natural Science Foundation of China (LR16F030003, LY16F030005,
LZ12F03001), the National Natural Science Major Foundation of Research
Instrumentation of China under Grants 61427808, and the Open Founda-
tion of First Level Zhejiang Key in Key Discipline of Control Science and
Engineering.
On the other hand, fuzzy logic model is an effective
method to analyze nonlinear systems, especially in the pres-
ence of incomplete knowledge of the plant. Since Takagi-
Sugeno (T-S) fuzzy model was introduced in [18], it has
been found many successful applications in various fields
[19–22]. A model of positive fuzzy systems described by
T-S fuzzy form was constructed and sufficient conditions for
asymptotic stability of the obtained system were given in
[23]. The problems of output-feedback and state-feedback
stabilization of positive T-S fuzzy systems (PTSFSs) were
dealt with in [24, 25], respectively. Therein, the common lin-
ear copositive Lyapunov function approach was used. As the
statements in [26–28], finding a common Lyapunov function
for fuzzy systems is a considerably difficult work. It has
been demonstrated that piecewise Lyapunov functions are a
much richer class of Lyapunov function candidates than the
common Lyapunov function candidates and thus it is able to
deal with a larger class of fuzzy systems. However, up to
now, stabilization of PTSFSs based on fuzzy linear coposi-
tive Lyapunov functions has not yet been solved.
Motivated by the above observations, we carry out the
present work. This paper first addresses the stabilization of
primal and dual PSSs. Some conditions for the stabiliza-
tion of PSSs are established in terms of linear programming
(LP). An implementable algorithm is proposed to reduce the
restriction of the computational software. Then, the stabi-
lization of primal and dual PTSFSs is solved. An algorithm
can be obtained as that in studying the stabilization of PSSs.
The rest of the paper is organized as follows: Section 2 intro-
duces some preliminaries; Main results are proposed in Sec-
tion 3; Section 4 gives two examples; Section 5 concludes
the paper.
Notation: N and N
+
are the sets of nonnegative and pos-
itive integers, respectively. R
n
,R
n
+
, and R
n×n
are the vec-
tors of n−tuples of real numbers and positive real numbers,
and the space of n × n matrices with real entries, respective-
ly. A
T
is the transpose of matrix A. I
n
is the n × n iden-
tity matrix. For v in R
n
, v
i
is the i-th component of v, and
Proceedings of the 35th Chinese Control Conference
Jul
27-29, 2016, Chen
du, China
1465