Conference Program of WCICA 2012

Conference Program WCICA 2012
The Research on Cross-Media Information Retrieval System Based on
Food Safety Emergencies, pp.706–710
Han, Pengcheng
Du, Junping
Lee, JangMyung
Univ. of Posts & Telecommunicatios
School of Computer Sicence & Tech., Beijing Univ.
of Posts & Telecommunications
Pusan National Univ.
In this paper, we design and implement a cross-media information retrieval
system based on the area of food safety emergencies. The system
collects Internet information using topic crawler, establishes data
index on cross-media information and makes fast retrieval by sort labeling.
The system supports image semantic retrieval and expansion
retrieval based on Ontology. The cross-media retrieval provides a new
technology for the research of emergencies field, and meets unique
retrieval needs by the largest extend.
◮ FrA03-5 14:50–15:10
Neural Networks Based Autonomous Learning for a Desktop Robot,
pp.739–742
Dai, Lizhen
Ruan, Xiaogang
Wang, Guanwei
Yu, Jianjun
Beijing Univ. of Tech.
Beijing Univ. of Tech.
Beijing Univ. of Tech.
College of Electronic Information & Control
Engineering, Beijing Univ. of Tech.
A method of realizing desktop robot’s negative phototaxis through a
neural network is presented. The biology is characteristic of biologic
phototaxis and negative phototaxis. Can a machine be endowed with
such a characteristic? This is the question we study in this paper. A randomly
generated network is used as the main computational unit. Only
the weights of the output units from this network are adjusted during the
training phase. Learning samples are collected according to the energy
function. It will be shown that this simple type of a biological realistic
neural network is able to simulate robot controllers like that incorporated
in desktop robots. The experiments are presented illustrating the
stage-like study emerging with this learning mode.
◮ FrA03-6 15:10–15:30
Predictive Temporal Patterns Detection in Multivariate Dynamic Data
System, pp.803–808
Zhang, Wenjing
Feng, Xin
Marquette Univ.
Marquette Univ.
In this paper we present a method for detecting multivariate temporal
patterns that are characteristic and predictive of significant events in
a multivariate dynamic data system. A new hybrid RPS-GMM method
is applied to identify patterns. This method constructs phase space
embedding by using individual embedding of each variable sequences.
We employ discriminative approach by applying Gaussian Mixture Model
(GMM) to the multivariate sequence data to cluster multidimensional
data into three categories of signals, e.g. normal, patterns and events.
An optimization method is applied to the objective function to search an
optimal classifier to identify temporal patterns that are predictive of future
events. We performed two experimental applications using chaotic
time series and Sludge Volume Index (SVI) series related to the Sludge
Bulking problem. Experiments show that the new approach presented
here significantly outperforms the original RPS framework and neural
network method.
FrA04 13:30–15:30 Room 203D
Nonlinear Control
Chair: Wang, Xingxuan
Co-Chair: Huang, Chaodong
Fudan Univ.
Chinese Acad. of Sci.
◮ FrA04-1 13:30–13:50
Estimate Error Analysis of the Nonlinear Third Order Extended State
Observer, pp.1621–1627
ZHANG, Yuan-wen
YANG, Le-ping
Zhu, Yanwei
National Univ. of defense Tech.
National Univ. of defence Tech.
National Univ. of Defense Tech.
Nonlinear extended state observer not only estimate all the state of
uncertain plant, but also the real-time inner and outer disturbance, independent
to plant model and having better robust capability. However,
the estimate error analysis of more than second order observer hasn’t
been depth researched. Based on the estimate error theory of second
order observer and some proper hypothesis, this paper firstly decoupled
the third order observer into two second order observers, then the
performance of estimate error is analyzed using continuous piece-wise
smooth Lyapunov function theory and a tuning rule is put forward. And,
based on the analysis of effect of observer parameters, an optimization
rule is used with the tuning process. Theoretic analysis and simulation
results indicate that the proposed estimate error analysis method
is proper, and the tuning law and optimization rule of observer parameter
are feasible.
◮ FrA04-2 13:50–14:10
Adaptive Sliding Mode Control with Nonlinear Disturbance Observer for
Uncertain Nonlinear System Based on Backstepping Method, pp.1609–
1614
Qiao, Jihong
Wang, Hongyan
Li, Zihao
Beijing Tech. & Business Univ.
Acad. of Armored Force Engineering
Beijing Tech. & Business Univ.
A chattering reduction sliding mode control (SMC) via backstepping
scheme is proposed for a class of mismatched uncertain nonlinear systems.
The most significant property of SMC system is its robustness,
but SMC has some difficulties to handling mismatched uncertainties.
Backstepping method doesn’t need matching conditions. The method
of combination of SMC and backstepping become effective in solving
the mismatched uncertainties. The robust of the systems is guaranteed.
But chattering caused by using SMC is not good for system. A
nonlinear disturbance observer is used to estimate disturbance. Whole
disturbance of the closed-loop systems is reduced. The chattering of
sliding controller is reduced clearly. The proposed method is validated
by simulation.
◮ FrA04-3 14:10–14:30
Control of a Class of Nonlinear Uncertain Systems by Combining State
Observers and Parameter Estimators, pp.2054–2059
Huang, Chaodong
Guo, Lei
Chinese Acad. of Sci.
Chinese Acad. of Sci.
The main purpose of this paper is to study the control problem for
a class of SISO affine nonlinear systems with unknown dynamics by
combining the extended state observer (ESO) technique and the projected
gradient estimator. While ESO can be used to estimate the total
uncertainties, the projected gradient algorithm is used to estimate
the nonparametric uncertainties treated as time-varying parameters.
This method improves the traditional active disturbance rejection control
(ADRC) technique. It overcomes the difficulty that the traditional
ADRC needs to have a “good”estimate for the uncertainties in the
input channel. Closed loop stability is proven and the control performance
is also analyzed.
◮ FrA04-4 14:30–14:50
Adaptive Control for A Class of Nonlinear Uncertain Dynamical Systems
With Time-varying, pp.2171–2176
Zhang, Jie
Wang, Xingxuan
Fudan Univ.
Fudan Univ.
This paper present a nonlinear adaptive control framework for a class
of nonlinear uncertain dynamical systems with time-varying that guarantees
ultimately bounded of the closed-loop systems. In particular, we
develop both full-state feedback control law and output feedback law.
In addition, we consider a expanded condition. By the analysis using a
Lyapunov function, we show that the framework guarantees ultimately
bounded of the closed-loop systems. An illustrative numerical example
is provided to demonstrate the efficacy of the proposed framework.
◮ FrA04-5 14:50–15:10
On the Modeling of a Nonlinear Plate and a Nonlinear Shell, pp.1585–
1590
Li, Shun
Acadamy of Mathematics & Sys. Sci., Chinese
Acadamy of Sci.
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