• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5164-5171
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• 2011

In fuzzy modeling for nonlinear process, typically using the given data, the fuzzy rules are formed by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is identified by selection of the input variables, the number of space division and membership functions and the consequent part of the fuzzy rule is identified by polynomial functions in the form of simplified and linear inference. In general, formation of fuzzy rules for nonlinear processes using the given data have the problem that the number of fuzzy rules exponentially increases. To solve this problem complex nonlinear process can be modeled by separately forming the fuzzy rules by means of fuzzy division of each input space. Therefore, this paper utilizes individual input space to generate fuzzy rules. The premise parameters of the fuzzy rules are identified by Min-Max method using the minimum and maximum values of input data set and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. And lastly, using the data which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.553-561
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• 2010

This paper proposed the face tracking method which can be effectively applied to the robot's vision system. The proposed algorithm tracks the facial areas after detecting the area of video motion. Movement detection of video images is done by using median filter and erosion and dilation operation as a method for removing noise, after getting the different images using two continual frames. To extract the skin color from the moving area, the color information of sample images is used. The skin color region and the background area are separated by evaluating the similarity by generating membership functions by using MIN-MAX values as fuzzy data. For the face candidate region, the eyes are detected from C channel of color space CMY, and the mouth from Q channel of color space YIQ. The face region is tracked seeking the features of the eyes and the mouth detected from knowledge-base. Experiment includes 1,500 frames of the video images from 10 subjects, 150 frames per subject. The result shows 95.7% of detection rate (the motion areas of 1,435 frames are detected) and 97.6% of good face tracking result (1,401 faces are tracked).

• The Journal of the Acoustical Society of Korea
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• v.19 no.7
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• pp.34-41
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• 2000

This paper proposes a new double-talk detection algorithm which is based on the fuzzy rules, in the adaptive echo canceller of telecommunication system. In this method, the two inputs of the fuzzy inference for detecting double-talk condition are used. One is the cross-correlation coefficient between the error signal and the primary signal which is the summation of the real echo signal and the near-end signal. The other one is the cross-correlation coefficient between the estimation error signal and the primary signal. The fuzzy controller makes a fuzzification for two inputs by the membership functions of trapezoid does the max-min composition using if-then rules. The composed result is defuzzificated by the center gravity method. And by defuzzificated values, the double-talt the echo path variance, and the echo path variance during the double-talk are detected. It is confirmed by computer simulation that this fuzzy double-talk detector is able to estimate the double talk and the echo path variation condition, and even track echo path variation more accurately than the conventional algorithm during the double-talk period.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.80-88
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• 1994

In the automation of rigid parts mating process with the intelligent robots, Peg-In-Hole is the most available task since inserting is some analytic and needs suitable range of forces that can be controlled by induatrial manipulators. In this Peg-In-Hole process, it is very important to identify the contact state between tow parts, peg and hole, to build the strategies for robot motion that leads to avoid the jamming condition occurs during insertion process. In this paper, we adpopted 3 parameters for identification, lFzl, lFxy/Fzl, and lMxy/Fxyl, derived from axes value of Whitney's jamming diagram. Also, we defined the fuzzy membership functions for these parameters and developed the identification algorithm based on fuzzy inference method of max-product. As an experimental result, we obtained about 96% of identification ratio that could be raised up to industrial requirements by further research.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.341-346
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• 2013

In this paper, we propose a rule extraction method using a modified Fuzzy Min-Max (FMM) neural network. The suggested method supplements the hyperbox definition with a frequency factor of feature values in the learning data set. We have defined a relevance factor between features and pattern classes. The proposed model can solve the ambiguity problem without using the overlapping test process and the contraction process. The hyperbox membership function based on the fuzzy partitions is defined for each dimension of a pattern class. The weight values are trained by the feature range and the frequency of feature values. The excitatory features and the inhibitory features can be classified by the proposed method and they can be used for the rule generation process. From the experiments of sign language recognition, the proposed method is evaluated empirically.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.563-569
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• 2015

A chemical reaction occurring in CSTR (Continuous Stirred Tank Reactor) is significantly affected by the concentration, temperature, pressure, and reacting time of materials, and thus it has strong nonlinear and time-varying characteristics. Also, when an existing linear PID controller with fixed gain is used, the performance could deteriorate or could be unstable if the system parameters change due to the change in the operating point of CSTR. In this study, a technique for the design of a fuzzy PD plus I controller was proposed for the temperature control of a CSTR process. In the fuzzy PD plus I controller, a linear integral controller was added to a fuzzy PD controller in parallel, and the steady-state performance could be improved based on this. For the fuzzy membership function, a Gaussian type was used; for the fuzzy inference, the Max-Min method of Mamdani was used; and for the defuzzification, the center of gravity method was used. In addition, the saturation state of the actuator was also considered during controller design. The validity of the proposed method was examined by comparing the set-point tracking performance and the robustness to the parameter change with those of an adaptive controller and a nonlinear proportional-integral-differential controller.