Abstract—A direct adaptive type-2 fuzzy logic controller is
designed in this paper. The longitudinal dynamics of a generic
hypersonic flight vehicle is high-order, highly nonlinear, tight
coupling and most of all includes big uncertainties. The
computing of the dynamic inversion control signal is cost
ineffective and an adaptive interval type-2 fuzzy logic system is
used to approximate it. A
∞
controller is implemented in order
to attenuate the fuzzy approximation error and the system
uncertainty. Signals’ high-order derivatives are obtained by
tracking differentiators and nonlinear state observers. The
closed-loop stability is guaranteed by Lyapunov theory.
Simulation results validate the effectiveness and robustness of
the proposed controller.
I. INTRODUCTION
YPERSONIC flight vehicle (HFV) flies at a speed of
more than 5 Mach within a very complicated
environment. Due to its large thrust to weight ratio, HFV
can be used as reusable orbital transport plane and
intercontinental airliner. Although HFV has many application
advantages, its flight control law design is highly challenging.
The longitudinal dynamics of a generic hypersonic flight
vehicle (GHFV) is high-order, highly nonlinear, tight
coupling and most of all includes big uncertainties.
Furthermore, the signals’ high–order derivatives are difficult
to measure. So the design of robust controller has caused
extensive concern. If there is no uncertainty, the dynamic
inversion (DI) control law can be a good control scheme.
Many control methods based on DI control have been
proposed [1], [2].
Interval type-2 fuzzy set (IT2-FS) is characterized by
membership functions (MFs) which are themselves fuzzy as
in Fig. 1(a), whereas MF of type-1 fuzzy set (T1-FS) is crisp
as in Fig. 1(b). The domain between the upper MF (UMF) and
the lower MF (LMF) is called footprint of uncertainty (FOU).
Secondary MFs in FOU all equal 1. Interval type-2 fuzzy
logic system (IT2-FLS) can be more capable of dealing with
uncertain problems than traditional type-1 fuzzy logic system
(T1-FLS). The structure of IT2-FLS is shown in Fig. 2. The
type reduction of IT2-FLS just involves computing LMF and
UMF of the antecedent and consequent sets. A direct adaptive
interval type-2 fuzzy logic controller is proposed for a
Fang. Yang, Ruyi. Yuan*(corresponding author), Jianqiang. Yi, Guoliang.
Fan and Xiangmin. Tan are all with the Institute of Automation, Chinese
Academy of Sciences, Beijing, 100190 China (email: {fang.yang, ruyi.yuan*,
jianqiang.yi, guoliang.fan, xiangmin.tan}@ia.ac.cn).
This work was supported by National Natural Science Foundation of
China under Grant 61203003, 61273149 and 60904006, Knowledge
Innovation Program of the Chinese Academy of Sciences under Grant
YYYJ-1122, and Innovation Method Fund of China under Grant
2012IM010200.
two-link manipulator [3]. It works well even when the system
is corrupted by random noise. Adaptive IT2-FLS is more
often used to approximate unknown nonlinear system online
and it does not need any prior knowledge [4].
Some works have been done on type-1 fuzzy logic control
of hypersonic flight vehicle. T1-FLS is used to approximate
the uncertain terms of the linearized model [5]. T1-FLS is
also used to approximate the nonlinear terms in backstepping
control [6]. Multistage type-1 fuzzy logic controllers are used
to stabilize the outer and inner loop of the flight altitude [7].
An indirect interval type-2 fuzzy logic controller for GHFV is
discussed as in [8].
-20 -10 0 10 20
0
0.2
0.4
0.6
0.8
1
IT2 MF
(a) universe of discourse
-20 -10 0 10 20
0
0.2
0.4
0.6
0.8
1
T1 MF
(b) universe of disc ourse
UMF
FOU
LMF
Fig. 1. (a) MF example of IT2-FS; (b) MF example of T1-FS.
Fig. 2. The structure of IT2-FLS.
Here, a direct adaptive interval type-2 fuzzy logic
controller (DAIT2-FLC) is first adopted in the tracking
control of hypersonic flight vehicle. We use IT2-FLS to
directly obtain the fuzzy control signals which approximate
the dynamic inversion control signals.
∞
controller is
implemented to attenuate the fuzzy approximation
error and
the system uncertainty. This paper is organized as follows:
Section 2 describes the control problem and gives some
preliminary knowledge. Section 3 designs the controller in
detail and also gives stability analysis. In section 4,
simulations are conducted to validate the proposed controller.
Conclusions are given in the final part.
Direct Adaptive Type-2 Fuzzy Logic Control of a Generic Hypersonic
Flight Vehicle
Fang. Yang, Ruyi. Yuan, Jianqiang. Yi, Guoliang. Fan and Xiangmin. Tan
H
2013 Fourth International Conference on Intelligent Control and Information Processing (ICICIP)
June 9 – 11, 2013, Beijing, China
978-1-4673-6249-8/13/$31.00 ©2013 IEEE