Conference Program of WCICA 2012

WCICA 2012
Book of Abstracts: Friday Sessions
slower update rate about the primary actuator,but the performance of
the whole system is not descending. A Simulink platform for dual-stage
actuator (DSA) control system is developed in this brief, the platform
is applied to test the influence of the ratio m on whole system performance.
Experimental results sufficiently demonstrate the usefulness of
the dual-stage actuator (DSA) control system , as well as the effectiveness
of the mentioned algorithm.
◁ PFrA-34
Research on Commutation fluctuation Self-Adaptive Control Suppression
Strategy for Brushless DC Motor, pp.265–269
Wang, Weihua
Huang, Haibo
Hubei Univ. of Automotive Tech.
Hubei Automobile Industries Inst.
In order to restrain the adverse influence of speed mutation and torque
ripple when brushless dc motor runs at the commutation moment, at
the same time, for the sake of avoiding the fact that traditional PI control
tragedy highly depends on the precise mathematical model of the
controlled system, this paper puts forward a kind of control tragedy of
domain self-regulating fuzzy control. At first, the basic operating principle
of brushless dc motor and the commutation ripple are analyzed,
then the process of domain self-regulating fuzzy control is detailedly
deduced, and the control tragedy is applied in the control system of
brushless dc motor. The experiment result shows that relative to the
traditional PI control tragedy, the domain self-regulating fuzzy controller
has better system reliability and robustness, and gains better suppression
effect of commutation ripple.
◁ PFrA-35
The Fuzzy Human-Simulated Intelligent Control for Hot-Rolling Strip
Width, pp.270–274
Tian, Jianyan
Zhang, Guanyu
Taiyuan Univ. of Tech.
Taiyuan Univ. of Tech.
Abstract: The hot-rolling strip process is a typical complex industrial
processes, and the effect of the traditional control strategy is not perfect.
Human-simulated intelligent controller, which does not rely on the accurate
mathematical model and also has a good control effect for complex
industrial system with delay or random disturbance, simulates the brain
of experts. This paper has designed a fuzzy human-simulated intelligent
controller whose parameters are corrected by fuzzy logic used to
the hot-rolling strip width control. The simulation results by MATLAB
show that the effect of the fuzzy human-simulated intelligent control
based on fuzzy control parameters calibration is better than that of PID
control, which provides a new way to solve the control problem of the
complex industrial systems.
◁ PFrA-36
On-Ramp Local Control with Neural Network Method, pp.286–289
Wang, Hao
Xu, Jinxue
Dalian Maritime Univ.
Dalian Maritime Univ.
Highway system is a strongly nonlinear system. Owing to the fact that
neural network has good nonlinear approximation properties and antijamming
capability, the neural network and PID control algorithm are introduced
to the freeway on-ramp control, by adjusting the on-ramp rate
to maintain the desired traffic density on the main highway. The stability
of the highway system will be enhanced owing to the fact that RBF algorithm
can overcome the disadvantage of conventional BP algorithm
and classical ALINEA control strategy, and the anti-perturbation ability
will also become stronger. Simulation results have shown that combining
the neural network and PID control technology can relieve traffic
congestion of the highway mainline.
◁ PFrA-37
A Wide Range of Course-changing Control Algorithm for Marine Vessel,
pp.295–299
Jia, Baozhu
ZHANG, Gui-chen
Dalian Maritime Univ.
Shanghai Jiaotong Univ.
This paper develop a named fuzzy switched multi-model algorithm for
marine vessel. The rudder angle is used to divide the course changing
process into multiple local operating regimes. The local controller
is designed in local operating regime by using parallel distributed compensate
method. The proposed algorithm can improve the global control
performance in course-changing within wide range. The Lyapunov
stability theorem is employed to derive the stability conditions of closed
loop system. Simulation results show that the proposed algorithm in
this paper provides a satisfactory result.
◁ PFrA-38
Rotary Kiln Combustion Working Condition Recognition Based on
Flame Image Texture Features and LVQ Neural Network, pp.305–309
Wang, Jie-sheng
Ren, Xiudong
Univ. of Sci. & Tech. Liaoning
Univ. of Sci. & Tech. Liaoning
According to the pulverized coal combustion flame image texture features
of the rotary-kiln oxide pellets sintering process, a combustion
working condition recognition method based on learning vector quantization
(LVQ) neural network is introduced. Firstly, the numerical flame
image was analyzed to extract texture features, such as energy, entropy
and inertia, based on grey-level co-occurrence matrix (GLCM) to provide
qualitative information on the changes in the visual appearance of
the flame. Then kernel principal component analysis (KPCA) method
is adopted to deduct the input vector with high dimensionality so as to
reduce the LVQ target dimension and network scale greatly. Finally,
LVQ neural network is trained and recognized by using the normalized
texture feature datum. Test results show that the proposed KPCA-LVQ
classifier has an excellent performance on training speed and correct
recognition ratio and meets the requirement for the real-time combustion
working conditions recognition.
◁ PFrA-39
Autonomous Navigation Research for Mobile Robot, pp.331–335
Cai, Jian Xian
Yu, Ruihong
Cheng, Lina
Inst. of Disaster Prevention
Inst. of Disaster Prevention
Inst. of Disaster Prevention
To solve the navigation problem of mobile robots in unknown environment,
we develop a navigation scheme based on the bionic strategy
which simulates operant conditioning mechanism. In this scheme, the
tendency Cell is designed by use of information entropy which represents
the tendency degree for state. The improved Q learning algorithm
used as learning core to direct the learning direction. The Boltzmann
machine is used to process annealing calculation, which can randomly
selected navigation action. The selected strategy of action will tend to
optimal with the learning process. Simulation analyses are carried out
in mobile robot; results show that the proposed method is effective.
◁ PFrA-40
A New Stability Condition of Neural Networks with Time-Varying Delay,
pp.336–340
Chen, Yun
Zheng, Wei Xing
Hangzhou Dianzi Univ.
Univ. of Western Sydney
This paper discusses stability of neural networks (NNs) with timevarying
delay. Delay-fractioning Lyapunov-Krasovskii functional (LKF)
method and convex analysis are applied to establish a new stability condition.
Two possible cases for the delay are taken into account when the
delay interval is equivalently divided into two subintervals. The maximal
allowable delay that ensures global asymptotical stability of the neural
network under consideration can be computed by solving a set of linear
matrix inequalities (LMIs). The advantage of the method is illustrated
by numerical examples.
◁ PFrA-41
The Study of Intelligent Space Environment Application and ManagementBased
on Wireless Networkt, pp.424–428
Duan, Ping
Hebei Univ. of Tech.
In Intelligent Space, the paper was successfully constructed using Zig-
Bee wireless sensor networks intelligent systems, and the corresponding
software and hardware design. The system uses star topology network.The
information is collected on each node (such as temperature,
humidity, light intensity, etc) integration.he central node accords corresponding
information to take automatically intelligent control of the en-
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