Nonlinear Dyn (2014) 76:1977–1988
DOI 10.1007/s11071-014-1262-z
ORIGINAL PAPER
Actuator fault diagnosis for uncertain T–S fuzzy systems
with local nonlinear models
Huimin Wang · Dan Ye · Guang-Hong Yang
Received: 11 November 2013 / Accepted: 13 January 2014 / Published online: 1 February 2014
© Springer Science+Business Media Dordrecht 2014
Abstract This article investigates the problem of
fault diagnosis (FD) for a class of nonlinear state-
feedback control systems subject to parameter uncer-
tainties. The considered nonlinear systems are describ-
ed by T–S fuzzy models with local nonlinear parts and
uncertain grades of membership. First, a general actua-
tor fault model is proposed, which considers bias faults
and gain faults. Then, a switching technique is intro-
duced to address the unknown membership functions,
external disturbances, faults, and their coupling. Fur-
thermore, an adaptive FD observer design method com-
bined with the switching technique is proposed to esti-
mate the occurred actuator fault. It is noted that the
obtained fault errors converge exponentially to zero.
Finally, a numerical example of NSV reentry dynamic
model is given to confirm the effectiveness of the new
results.
Keywords T–S fuzzy systems · Local nonlinear
parts · Parameter uncertainty · Fault diagnosis (FD)
H. Wang · D. Ye (
B
) · G. H. Yang
College of Information Science and Engineering,
Northeastern University, Shenyang 110004, China
e-mail:yedan@ise.neu.edu.cn
H. Wang
e-mail: wanghuimin_neu@163.com
D. Ye · G.-H. Yang
State Key Laboratory of Synthetical Automation
for Process Industries, Northeastern University,
Shenyang 110004, China
e-mail: yangguanghong@ise.neu.edu.cn
1 Introduction
Over the recent decades, the system reliability require-
ments have increased in the practical applications of
safely-critical systems, especially flight control sys-
tems. To improve the reliability and safety of such
systems, the model-based on fault diagnosis (FD) in
dynamic systems has attracted considerable attention
from many researchers. Among the various FD meth-
ods, the observer-based FD technique is the one that
has been widely and most extensively considered; see
survey articles: [1–6]. The basic idea of the observer-
based FD is to estimate the states and/or the faults of
the system from measurements using some types of
observers, and define a residual evaluation function to
compare the residual evaluation value with a predefined
threshold.
In almost all of the above referenced articles, the
study on observer-based FD is mainly concentrated
on linear systems. Since almost all realistic physical
processes exhibit nonlinear dynamics, FD for nonlinear
systems has received a great deal of attention recently;
for examples, see [7–9]. In particular, an important
approach to nonlinear system FD is to model the con-
sidered nonlinear systems as Takagi and Sugeno (T–
S) fuzzy systems [10], which have been proven to be
a good universal approximator to nonlinear behaviors
[11]. The prominent feature of T–S fuzzy models is
that they are represented by some locally linear time-
invariant submodels in the form of IF-THEN rules.
In recent years, we have witnessed rapidly growing
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