Conference Program of WCICA 2012

Conference Program WCICA 2012
tion dynamics are used to establish the reference model implicating essential
nonlinearities for GEBF-FNN based ship motion model (GEBF-
FNN-SMM) identification. The GEBF-FNN-SMM starts without fuzzy
rules and online recruits efficient fuzzy rules via rule node generation
criteria and parameter estimation. The resultant GEBF-FNN-SMM reasonably
captures essential dynamics since the checking process validates
the prediction performance with high accuracy. Finally, in order to
demonstrate that the GEBF-FNN-SMM scheme is effective, simulation
studies are conducted on zig-zag maneuvers. Moreover, comprehensive
comparisons are carefully presented. Simulation results indicate
that the GEBF-FNN-SMM achieves promising performance in terms of
approximation and prediction.
◮ FrB02-2 16:10–16:30
A Probabilistic Fuzzy Controller with Operant Learning for Robot Navigation,
pp.368–373
Gao, Yuanyuan
Ruan, Xiaogang
Song, Hongjun
Beijing Univ. of Tech.
Beijing Univ. of Techbnology
Beijing Univ. of Tech.
Fuzzy logic system (FLS) promises an efficient way for obstacle avoidance.
However, it is difficult to maintain the correctness, consistency,
and completeness of a fuzzy rule base tuned by a human expert. In
this paper, a novel approach termed probabilistic fuzzy controller with
operant learning (PFCOL) for robot navigation is presented. Operant
learning (OL) is a form animal learning way. The key feature of this
approach is that it combines a probabilistic stage and a stochastic perturbation
generator module into FLS to handle problems. At last, the
ultimate output is determined by these two uncertain stages. This imitates
animal learning method of generating stochastic behavior in the
complex and uncertain environment. The simulation results show that
the proposed PFCOL method can automatically generate approximate
actor to adapt complex circumstances. Through studies on obstacle
avoidance and goal seeking tasks by a mobile robot verify the approach
is superior in generating efficient fuzzy inference systems.
◮ FrB02-3 16:30–16:50
The Optimization of Fuzzy Rules Based on Hybrid Estimation of Distribution
Algorithms, pp.561–565
Luo, Xiong
Bai, Xue
Univ. of Sci. & Tech. Beijing
Univ. of Sci. & Tech. Beijing
Optimization of fuzzy rules based on numerical data is an important issue
in the optimization design of fuzzy system. In this paper, based on
an improved estimation of distribution algorithm, an optimization learning
method COR MUMDA for fuzzy rules is proposed. This method can
generate fuzzy rules directly from numerical data. The method learn
fuzzy rules mainly based on MUMDA (multi-group univariate marginal
distribution estimation algorithm). Unlike the general estimation of distribution
algorithms, MUMDA can increase the diversity of the population
and avoid sticking at local optima. In addition, the elite genetic
strategy is used to generate the next population. In this way, it reduces
the possibility of losing the optimal solutions. To verify the efficiency of
this algorithm, the simulation experiments are performed. The comparative
results of three classic examples are given.
◮ FrB02-4 16:50–17:10
On the Definition of Type-2 Fuzzy Sets, pp.601–605
Mo, Hong
Zhou, Min
Changsha Univ. of Sci. & Tech.
Changsha Univ. of Sci. & Tech.
This paper introduces four kinds of definition of type-2 fuzzy sets(T2
FS), and provides their difference and connection,then presents a new
definition of type-2 fuzzy set to make it to be understood more easily,
In finial, we modify the definition and formula of footprint of uncertainty
(FOU) of T2 FS and give the relation of FOU and T2 FS.
◮ FrB02-5 17:10–17:30
Estimation of Hand Force from Surface Electromyography Signals using
Artificial Neural Network, pp.584–589
Srinivasan, Haritha
Sauvik, Das Gupta
Oklahoma State Univ.
Oklahoma State Univ.
Sheng, Weihua
Chen, Heping
Oklahoma State Univ.
Texas State Univ.
Haptic technology has many real world applications such as rehabilitation
robotics, telepresence surgery, gaming, virtual reality and humanrobot
interaction. Force plays an important role in the above mentioned
haptic applications. In this paper, we propose a method to estimate
force from surface Electromyography (SEMG) signals using Artificial
Neural Network (ANN). The haptic device is modeled to act as a virtual
spring. The neural network is trained with EMG data from wrist flexion
action as input and force values from the haptic device as target. The
results shown in this paper illustrate the neural network performance in
estimating the force values in real-time.
◮ FrB02-6 17:30–17:50
Supervisor Design with Petri Nets for Asymmetrical System, pp.628–
632
FENG, Aixiang
LUO, Xiong-lin
China Univ. of Petroleum
China Univ. of Petroleum
Asymmetrical processes are common nonlinear systems, where the
switching between two different operating modes depends on whether
the system input or output is increasing or decreasing. The existing
intelligent control methods for asymmetical system can’t explain the relationship
between continuous and discrete part of the system .With
the idea of hybrid systems, a supervisory control method is developed
to distinguish asymmetry phenomena of the thermal process of a furnace.
In order to ensure the stability of arriving at the setting point, a
supervisory controller modelled by the extended Controlled Petri nets
is designed to track errors and the direction of the output.Then the
system can be switched to an appropriate mode , where the tracking
determines the switch.Test result verifes the validity of this method.
FrB03 15:50–17:50 Room 203C
Control Design
Chair: Wang, Guo-sheng
Co-Chair: XIE, Wei
Acad. of Armored Force Engineering
South China Univ. of Tech.
◮ FrB03-1 15:50–16:10
Quadratically Stabilizing Observer-based Controller Design for LPV
Plant , pp.1073–1076
XIE, Wei
South China Univ. of Tech.
This paper presents a new quadratic stability-preserving state-space
realization and quadratically stabilizing observer-based controller design
for Linear Parameter Varying (LPV) plant, which is combined with
a set of local vertex LTI plants. A two-step procedure is taken to design
a quadratically stabilizing observer-based controller for LPV plant. First,
according to the stabilizabilities of local LTI plants, state-feedback gain
matrices and Lyapunov matrices could be solved for these local plants
with linear matrix inequality technique, independently. With these Lyapunov
matrices, a proper state space realization of LPV plant is provided.
Second, based on the state space realization, a quadratically
stabilizing observer-based controller is obtained.
◮ FrB03-2 16:10–16:30
A Closed-loop Evaluation for Regulatory Control Structure of Multivariable
System, pp.1083–1088
LUO, Xiong-lin
Ren, Li-hong
China Univ. of Petroleum
China Univ. of Petroleum
In multivariable processes, control structure selection represented as
the pairing of manipulated variables and controlled variables is a major
concern during the design of multi-loop regulatory PID control system.
Each pairing method has its application scope, and it is necessary to
analyze and evaluate the closed-loop application effect of the system
pairing. Based on the dynamic transmission ratio between manipulated
variables and controlled variables under the closed-loop state, the
degree of coupling for each loop is calculated for the system pairing,
and the closed-loop evaluation which is achieved by the determination
of whether the degree of coupling is within the threshold is proposed
to determine whether the result is satisfied. This method can not only
be used to compare several different pairing results during the design
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