ORIGINAL ARTICLE
Stability and stabilization of a delayed PIDE system via SPID
control
Chengdong Yang
1,2
•
Ancai Zhang
3
•
Xiao Chen
1
•
Xiangyong Chen
4
•
Jianlong Qiu
4
Received: 8 December 2015 / Accepted: 30 March 2016
Ó The Natural Computing Applications Forum 2016
Abstract This paper addresses the problem of exponen-
tial stability and stabilization for a class of delayed dis-
tributed parameter systems, which is modeled by partial
integro-differential equations (PIDEs). By employing the
vector-valued Wirtinger’s inequality, the sufficient condi-
tion of exponential stability of the PIDE system with a
given decay rate is investigated. The condition is presented
by linear matrix inequality (LMIs). After that, we develop a
spatial proportional-integral-derivative state-feedback
controller that ensures the exponential stabilization of the
PIDE system in terms of LMIs. Finally, numerical exam-
ples are presented to verify the effectiveness of the pro-
posed theoretical results.
Keywords Partial integro-differential equation
Distributed parameter system Exponential stabilization
Linear matrix inequality
1 Introduction
In the area of engineering, many industrial processes are
able to be described by distributed parameter system
(DPSs), such as thermal diffusion processes, fluid, and heat
exchangers (see [1–4]). For this reason, the properties (i.g.,
stability and stabilization) of distributed parameter systems
(DPSs) have attracted a lot of attention over the past few
decades. Generally speaking, DPSs can be modeled
mathematically by partial differential equations (PDEs) or
partial integro-differential equations (PIDEs). And the
nature of infinite-dimensional DPS is different from the
finite-dimensional one. In this situation, stability analysis
and stabilization problem of DPSs is of theoretical and
practical importance, which has important potential appli-
cations in complex networks, multi-agent systems, and
logistics networks and EPC system networks [5–7].
Many researchers have paid attention to the study on the
stability and stabilization of PDE systems in the past few
years. And many control design strategies have been pre-
sented. These strategies can be classified into two types:
‘‘reduce-then-design’’ (see [1, 2, 8–17]) and ‘‘design-then-
reduce’’ (see [18–35]). The former firstly employs the
model reduction techniques to obtain the approximated
ODE models and then design the controllers based on the
derived ODE model. However, a potential drawback of the
strategy is that the truncation prior to the control design
would lead to the inherent loss of physical features of the
problem as pointed out in [29–32]. In contrast, the design-
then-reduce approach with the infinite-dimensional control
solution is then lumped for implementation purpose.
Although most literatures about the stability and stabi-
lization of DPSs modeled by PDE systems have been
presented, there are few studies devoted to these properties
of PIDE systems with the exception of the result. More
& Chengdong Yang
yangchengdong@lyu.edu.cn
& Jianlong Qiu
qiujianlong@lyu.edu.cn
1
School of Informatics, Linyi University, Linyi 276005,
People’s Republic of China
2
School of Automation, Southeast University,
Nanjing 210096, People’s Republic of China
3
School of Automobile Engineering, Linyi University,
Linyi 276005, People’s Republic of China
4
School of Science, Linyi University, Linyi 276005,
People’s Republic of China
123
Neural Comput & Applic
DOI 10.1007/s00521-016-2297-5