Conference Program of WCICA 2012

Conference Program WCICA 2012
vironment movement.It realized the human living environment.It is low
power, low cost, easy to operate, easy to install under the Intelligent
Space.
◁ PFrA-42
The Research on Eruption Peak Mutation model of Lake and Reservoir
Alga Bloom, pp.2949–2952
Zhao, Xiaoping
Wang, Xiaoyi
beijing Tech. & bussiness Univ.
Beijing Tech. & business Univ.
Lake and reservoir alga bloom’s eruption is resulted by multiple factors,
and its formation mechanism is rather complicated. A simulation
of this eruption has been conducted in sunshine-room laboratory, then
analysis the primary factor influencing the alga growth by rough set theory,
through mutation theory to determine the critical factors of eruption.
On this basis, the peak mutation model featured by potential function
of chlorophyll-a is constructed so that the characteristic of alga bloom
is able to described. Finally, the simulation is proved that the model is
effective and feasibility.
◁ PFrA-43
Active fault-tolerant control for satellite system via learning unknown
input observer, pp.2965–2967
Jia, Qingxian
Guan, Yu
Zhang, Yingchun
Jiang, Yu
Shen, Yi
Harbin Inst. of Tech.
Harbin Inst. of Tech.
research centor of satellite Tech.
Harbin Inst. of Tech.
Harbin Inst. of Tech.
This paper presents an active fault-tolerant control( FTC) architecture
for satellite attitude control system(ACS) by combining iterative learning
ideology and unknown input observer(UIO). As an integral part of active
FTC system(FTCS), a learning UIO(LUIO) is proposed to achieve attitude
angular velocities estimation and robust reconstruction of adaptive
compensation law simultaneously based on the disturbance decoupling
principle of UIO and 𝐻∞control ideology. Finally, simulation
results on closed-loop ACS of satellite example demonstrate the effectiveness
of the proposed LUIO-based approach.
◁ PFrA-44
The Method of Multi-sources Fault Diagnosis in Gas Turbine & Compressor
Unit Based on SDG and Bayes Theory, pp.2973–2976
SONG, Yong-jie
XU, Bao-chang
China Univ. of Petroleum (Beijing)
China Univ. of Petroleum(Bejing)
With the development of Natural Gas Pipeline in China, gas turbine &
compressor unit has been widely used, so the fault diagnosis of its e-
quipment is important particularly. In this paper, the method based on
SDG (Signed Directed Graph) and Bayes theory is applied to fault diagnosis
of the equipment. According to SDG model and Bayes theory,
this method finds the consistent path and gets the optimizing model of
the diagnosis. Then the optimal combination is calculated by implicit
enumeration method. Finally, this method is applied to the lubrication
system of gas turbine & compressor unit. The results show that this
method can complete the multi-sources fault diagnosis quantitatively
and improve the diagnosis resolution effectively.
◁ PFrA-45
Research on Banknote Image Orientation Based on Least Square,
pp.2983–2987
Zhang, Ying
Univ. of Anshan
Banknote sorting is an important operation in the bank. The banknote
image orientation plays an key role in banknote recognition. In this
paper, the theory of least square is researched deeply and is used in
banknote orientation. Its properties and application circumstances are
summed up by experiments.
◁ PFrA-46
Dynamic Characteristics for Evaporator in Organic Rankine Cycle,
pp.2994–2998
Hou, Guolian
Li, Yanbin
North China Electric Power Univ.
North China Electric Power Univ.
Zhang, Jianhua
Zhou, Yeli
North China Electric Power Univ., Beijing
North China Electric Power Univ.
Organic Rankine Cycle (ORC) is suitable for recovering energy from
low-grade heat sources. A moving boundary model is introduced to
describe the transient phenomena of evaporator, which is an important
component of ORC. Based on the partial-differential equations expressing
the conservation principles of mass and energy, coupled with flue
gas and tube wall energy equations , a set of ordinary-differential equations
can be obtained by integrating separately over the three regions:
unsaturated liquid , liquid-vapor mixture, and the superheat vapor. The
state space equation of evaporator can be derived by linearizing the
obtained equations at the operating point. Finally, the simulation results
are presented to show the feasibility of the proposed method of
modeling.
◁ PFrA-47
An improved fuzzy identification method based on Sigmoid data transfer
function, pp.2999–3003
Liu, Fucai
Wang, Shu’en
Dou, Jinmei
Yanshan Univ.
Yanshan Univ.
Yanshan Univ.
Unlike the traditional approaches that utilize original data patterns to
construct the fuzzy model, an approach exploiting both data transformation
techniques and heuristic method is proposed to simplify the
modeling procedures. For the transferred data, firstly, the initial value
of fuzzy if-then rules with nonfuzzy singletons (i.e., real numbers)
in the consequent parts is generated by the heuristic method. Then,
fine-tuning is done by gradient descent learning algorithm. The proposed
method has better approximation accuracy and faster convergence
speed. Simulation result demonstrates the superiority of the
proposed model to the conventional methodologies.
◁ PFrA-48
Nonlinear System Modeling and Fault Detection Method Using Set
Membership Estimation and T-S Fuzzy Model, pp.3031–3036
Chai, Wei
Beijing Univ. of Tech.
A modeling method is proposed and applied in fault detection for nonlinear
dynamical systems with unknown but bounded noises. Since the
Takagi-Sugeno (T-S) fuzzy model is a universal approximator, it is used
to model the nonlinear dynamical system when the system runs without
a fault. After some input and output data of the system are obtained,
the input space is partitioned using a fuzzy clustering algorithm. Assuming
that the system noise and approximation error are unknown but
bounded, the consequence parameters of the T-S fuzzy model of the
system are determined by means of a linear-in-parameter set membership
estimation algorithm. An interval containing the actual output of
the system running without a fault can be easily predicted based on the
result of the estimation. If the measured output is out of the predicted
interval, it can be determined that a fault has occurred. Simulation
results show the effectiveness of the proposed method.
◁ PFrA-49
Sample Selection and Training of Self-Organizing Map Neural Network
in Multiple Models Approximation, pp.3053–3058
Gao, Dayuan
Zhu, Hai
Liu, Xijing
Wang, Chao
Navy submarine Acad.
navy submarine Acad.
Navy Submarine Acad.
navy submarine Acad.
The self-organizing map (SOM) neural network has been used widely
in multiple models approximation (MMA). However, the clustering property
of SOM may not be fit for MMA. This paper introduces the idea of
active learning into the training of SOM, especially for MMA. The neural
network selects actively the training samples according to the approximation
error of local models. As a result, the distribution of the neural
nodes is changed so that the performance of MMA is improved. The
process of this training method and the performance improvement are
illustrated by a simulation example.
◁ PFrA-50
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