Conference Program of WCICA 2012

Conference Program WCICA 2012
Study on the Structure of Human Body Simulated Controller , pp.10–14
Wang, Peijin
Yantai Univ.
Wang, Xuejie
Li, Yanjun
Zhejiang Univ. City College
Zhejiang Univ. City College
According to object oriented methodology, all of the controller object,
sensor object and actor object are intelligent in a human body simulated
control system. The above three intelligent control objects can
co-operate with each other to keep the controlled system safety and
reliability although one of them does not work. The above three intelligent
objects consist of human body simulated controller, each of them
is analyzed simply in this paper. The human body simulated controller
has been used in a real control system, it proves that the controller is
best, and the control result is best.
◮ FrA01-3 14:10–14:30
Attitude Control of 3-DOF Helicopter based on Iterative Learning Control,
pp.128–132
Zhang, Xining
Liu, Chenglin
Liu, Fei
Jiangnan Univ.
Jiangnan Univ.
Inst. of Automation,Southern Yangtze Univ.
Tracking control problems of the elevation and travel angles are investigated
for 3-DOF (three degree of freedom) helicopter in this paper. By
combining the normal PID controller based on LQR (linear quadratic
regulator) and PID-type Iterative Learning Control, a new mixed controller
is proposed for 3-DOF helicopter to achieve higher tracking accuracy.
Compared with the normal PID controller based on LQR, the
mixed controller can achieve better asymptotic converging effect for the
control of the elevation and travel angles of 3-DOF helicopter. By the
relatively small times of iteration, the system achieves quite high tracing
accuracy under the mixed controller.
◮ FrA01-4 14:30–14:50
Dancing Behavior Modeling and Logic Control Simulation of Twowheeled
Robot based on Stateflow, pp.89–92
Yu, Jianjun
College of Electronic Information & Control
Engineering, Beijing Univ. of Tech.
Yang, Qiong
Sun, Liang
Wang, Guanwei
Beijing Univ. of Tech.
Inst. of Electric Information & Control Engineering
Beijing Univ. of Tech.
Using FSM (Finite State Machine) theory as the foundation, based on
the MATLAB / Stateflow graphical behavior description method, realizes
the wheeled robot dance behavior modeling, design of the wheeled mobile
robot behavior control logic. The simulation results show that the
simulation model can be constructed, simulated robot dance behavior
of the actual process; the logic control method can realize the wheeled
robot dance planning. And the modular design of concise and clear,
design and debugging time is greatly reduced, cost is reduced, operation
controllability enhancement, It can provide the theoretical basis for
wheeled robot dance planning.
◮ FrA01-5 14:50–15:10
Stable flocking of mobile agents in mixed absolute and relative navigations
context with communication , pp.67–73
Dang, Zhaohui
National Univ. of Defense Tech.
In this paper, we studied the flocking motion of multiple agents in mixed
absolute/relative navigation condition with communication. The difference
between navigation and communication in the role taken part in
the neighbourhood relations was firstly pointed out. We gave a criterion
which can judge whether a communication neighbourhood graph
with mixed absolute/relative navigation devices is connected. We also
proposed an algorithm to achieve the absolute navigation using the
communication. Based on above preliminaries, we design a control law
to stabilize the flocking motion of multiple agents whose dynamics are
nonlinear with noise. The simulation in three different scenarios was
performed and the corresponding results illustrated the effectiveness of
the control law.
◮ FrA01-6 15:10–15:30
A Modified Fruit-Fly Optimization Algorithm Aided PID Controller Designing,
pp.233–238
Liu, Yi
ZheJiang Univ. City College
Fruit Fly Optimization Algorithm (FOA) is one of the newest intelligent
optimization algorithms. Attracted by its simple implement procedure
with effective searching capability, our work is to popularize this algorithm
to tackle some practical optimization applications requesting
real-time performance. However, the updating strategy of FOA is with
strong randomness, thus bringing in some blindness searching in solution
updating, which will result in slow convergence rate and premature.
Therefore, a modified FOA (MFOA) based on PSO and SA was
proposed in this paper to improve the performance of basic FOA. Besides,
Chaos funtion was used to enhance the stochastic and ergodic
features of initial solution so as to improve the diversity of initial population
in MFOA. PSO is introduced to reduce the blindness searching in
solution updating. SA is used as a local search to improve the convergence
rate. Finally, in order to verify the efficiency of MFOA algorithm,
two common functions and a practical high-order AVR system with PID
controller were tested in simulation. Experimental results revealed the
encouraging performance of our proposed algorithm.
FrA02 13:30–15:30 Room 203B
Computational Intelligence and Applications (I)
Chair: Zhang, Xuncai
Co-Chair: Wu, Xiuli
Zhengzhou Univ. of Light Industry
Univ. of Sci. & Tech. Beijing
◮ FrA02-1 13:30–13:50
An Increasing on Knowledge of MAS Trained by Boltzmann Machine
Algorithm based Sugarscape CA Using a Synergy of Communication
and Cooperation bet Agents , pp.484–489
Nourafza, Nasim
Setayeshi, Saeed
Islamic Azad Univ. ,Najafabad Branch
Amirkabir Univ. of Technolog
Sugarscape model is a multi-agent environment that is used for modeling
and organizing processes such as social, political and economic.
After the previous studies which were concerned with the production
of a learned multi-agent model based on Boltzmann Machine learning
algorithm and also the evaluation of the learning of a learned system
in sugarscape, the purpose of this study is to evaluate the learning
done after adding the two parameters of communication and cooperation
to the sugarscape learned model. Thus a cellular learned multiagent
model with use of Boltzmann Machine learning algorithm based
on sugarscape model was considered. In this model, each agent has
been allocated with a parameter that indicates the knowledge of the
agent. Once all agents reach sugar peaks it means that all agents
have become knowledgeable and the model has converged. After that
the two parameters of communication and cooperation are added to
the given model and for each one of the models the number of agents
present in sugar peaks after the model had reached convergence per
the specific number of agents has been measured. After analyzing the
resulting diagram it was concluded that after the convergence of the
model, the average number of knowledgeable agents in learned model
with communication and cooperation is higher than the number of
knowledgeable agents in learned model without use of communication
and cooperation. Therefore communication and cooperation of the a-
gents causes to incre
◮ FrA02-2 13:50–14:10
Data Collection Based on Mobile Agent in Wireless Sensor Networks,
pp.392–396
Li, Tongying
National Astronomical Observatories / Nanjing Inst.
of Astronomical Optics & Tech., Chinese Acad. of
Sci., Nanjing
Environment Changes due to temperature, humidity, wind loading and
so on can affect the performance of a large telescope. The real-time
information of environment change must be got in order to exert control,
reduce or eliminate the adverse effects of environment changes on
the large telescope. A novel method of environment monitoring for a
large telescope based on wireless sensor networks has therefore been
proposed to realize environment data acquisition, on-line-detection and
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