• Title/Summary/Keyword: Fuzzy-study-rule

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Memory Organization for a Fuzzy Controller.

  • Jee, K.D.S.;Poluzzi, R.;Russo, B.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1041-1043
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    • 1993
  • Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)+dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

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Real-time Fault Detection and Classification of Reactive Ion Etching Using Neural Networks (Neural Networks을 이용한 Reactive Ion Etching 공정의 실시간 오류 검출에 관한 연구)

  • Ryu Kyung-Han;Lee Song-Jae;Soh Dea-Wha;Hong Sang-Jeen
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.7
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    • pp.1588-1593
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    • 2005
  • In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

A Study on Fault Diagnosis in Face-Milling using Artificial Neural Network (인공신경망을 이용한 정면밀링에서 이상진단에 관한 연구)

  • Kim, Won-Il;Lee, Yun-Kyung;Wang, Dyuk-Hyun;Kang, Jae-Kwan;Kim, Byung-Chang;Lee, Kwan-Cheol;Jung, In-Ryung
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.4 no.3
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    • pp.57-62
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    • 2005
  • Neural networks, which have learning and self-organizing abilities, can be advantageously used in the pattern recognition. Neural network techniques have been widely used in monitoring and diagnosis, and compare favourable with traditional statistical pattern recognition algorithms, heuristic rule-based approaches, and fuzzy logic approaches. In this study the fault diagnosis of the face-milling using the artificial neural network was investigated. After training, the sample which measure load current was monitored by constant output results.

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Intelligent Controller for Constant Control of Residual Chlorine in Water Treatment Process (정수장 잔류염소 일정제어를 위한 지능형 제어기 개발)

  • Lee, Ho-Hyun;Jang, Sang-Bok;Hong, Sung-Taek;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.2
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    • pp.147-154
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    • 2014
  • In this study, chlorine modeling technique based on fuzzy system is proposed to reduce the carcinogenic substance and decide the optimal chlorine injection rate, which is affected by chlorine evaporation rate in sedimentation basin according to detention time, weather and water quality. The additional chlorine meter is installed in the inlet part of sedimentation to reduce the feedback time and implement cascade control, which leads to maintaining the residual chlorine concentration decided by fuzzy rule. It helps to take a preemptive action about long time delay, the characteristics of the disinfection process, and reduce the variation of residual chlorine rate by 7.3 times and the chlorine consumption by 40,000 dollars. It made a significant contribution to supply hygienically safe drinking water.

Program Development for Detecting Charged Refrigerant Amount in System Air-Conditioner using Fuzzy Algorithm (퍼지 알고리즘을 이용한 시스템 에어컨의 냉매충전량 감지 프로그램 개발)

  • Tae S. J.;Choi C. S.;Kim H. M.;Cho K.;Moon J. M.;Kim J. Y.;Kwon H. J.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.18 no.2
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    • pp.172-179
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    • 2006
  • This study developed a program for detecting charged refrigerant amount in system air-conditioner. System air-conditioner is an air-conditioning system with multiple indoor units. Due to the complexity of the system, it is more difficult to detect the refrigerant amount charged in the system air-conditioner than in a general single air-conditioner. Experiments were performed for a 6 HP outdoor unit with 3 indoor units in a psychrometric calorimeter. The experimental amount of the charged refrigerant was ranged from $60\%\;to\;140\%\;with\;10\%$ increasement. Fuzzy algorithm was employed for detecting the charged refrigerant amount in the system air-conditioner. The experimental data were used for curve-fitting for the general ranges of indoor and outdoor temperature conditions. Membership function was determined for the whole ranges of experimentally measured data and rule-bases were defined for each charged refrigerant amount. Developed program successfully predicted the measured data within $10\%$ resolution range.

A Study on Efficiency Analysis of Wind Power Generator (풍력 발전 효율성 분석에 관한 연구)

  • Park, SangJun;Hong, Yousik;Kang, Jeong Jin;Yang, JaeSoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.2
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    • pp.219-224
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    • 2017
  • These days, it is developed renewable energy-based wind power technology. Wind power generation is relatively quiet, and environmental damage is relatively low. In developed countries, a lot of wind power generation is being built. In Korea, the generation efficiency is low because there are few areas where the wind speed is maintained for four seasons. In recent years, forest damage, low noise, and environmental degradation complaints are frequent. In this paper, we performed an experiment to manage pitch control effectively by analyzing wind, direction, and temperature in real time based on FUZZY rule and cluster analysis.Using the new algorithm proposed by the simulation results, we could verify the efficiency of wind power generation pitch control for wind condition and direction condition by using the pitch control analysis technique.Furthermore, visualization representations have proven to automatically analyze early warning and efficiency of generator performance.

A Study on the Emotional Evaluation Model of Color Pattern Based on Adaptive Fuzzy System (적응 퍼지 시스템을 이용한 칼라패턴 감성 평가 모델에 관한 연구)

  • 엄경배
    • Journal of the Korean Institute of Intelligent Systems
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    • v.9 no.5
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    • pp.526-537
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    • 1999
  • In the paper. we propose an evaluation model based the adaptive fuzzy systems, which can transform the physical features of a color pattern to the emotional features. The model is motivated by the Soen's psychological experiments, in which he found the physical features such as average hue, saturation, intensity and the dynamic components of the color patterns affects to the emotional features represented by a pair of adjective words having the opposite meanings. Our proposed model consists of two adaptive fuzzy rule-bases and the y-model, a l i r ~ r ys et operator, to fuze the evaluation values produced by them. The model shows con~parablep erformances to the neural network for the approximation of the nonlinear transforms, and it has the advantage to obtain the linbwistic interpretation from the trained results. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

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A study on intelligent fish-drying process control system

  • Nakamura, Makoto;Shiragami, Teizoh;Sakai, Yoshiro
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.132-137
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    • 1993
  • In this paper, a fish drying process control system is proposed, which predicts the proper change with time in weight of the material fish and the drying conditions in advance, based on the performance of skilled worker. In order to implement a human expertise into an automated fish drying process control system, an experimental analysis is made and a model for the process is built. The proposed system divided into two procedures: The procedure before drying and the one during drying. The procedure before drying is for the prediction of necessary drying time. To estimate the necessary drying time, first, the proper change in weight for the product is obtained by using fuzzy reasoning. The condition part of the production rule consists of the factors of fish body and the expected degree of dryness. Kext, the necessary drying time is obtained by regression models. The variables employed in the models are the factors, inferred change in weight and drying conditions. The model for the procedure during drying is also proposed for more accurate estimation, which is described by a system of linear-differential equations.

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A Study on Cultivation facility Control Using Embedded Technology In Ubiquitous Environment (유비쿼터스 환경에서 임베디드 기술을 이용한 재배 시설 제어에 관한 연구)

  • Cho Soung-Jin;Park Jin-Hee;Chung Hwan-Mook
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.143-146
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    • 2005
  • 생활환경이 새로운 패러다임으로 변해가고 있다. 유비쿼터스 환경을 앞당기기 위하여 산업체 전반에 걸쳐 변화를 거듭하고 연구가 지속되고 있다. 유비궈터스 환경은 농업 분야에도 적용되어 농산물의 재배와 수확에 이르기까지 전반적인 형태를 변화 시키고 있다. 재배 시설을 원격지에서 제어함으로써 적절한 재배환경을 지원할 수 있도록 하여 환경변화 관리를 효율적으로 할 수 있으며, 사용자의 성향에 맞는 재배 환경 여건을 지능적으로 판단하고 제어 할 수 있는 시스템이 요구된다. 본 논문에서는 다양한 환경 즉, 온도, 습도, $CO_{2}$, 조도 등의 변화를 센서네트워크를 통하여 감지하고, 퍼지시스템을 통하여 환경변화를 추론하여 환기시설을 적절하게 제어할 수 있는 시스템과 알고리즘을 제안한다.

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유비쿼터스 기술을 이용한 태양광 감시 시스템

  • Jeong, Chang-Deok;Hong, Yu-Sik;Park, Jong-Cheol
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.255-259
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    • 2007
  • In this paper, It proposes that solar cell monitoring system using ubiquitous technique, solar cells development system occurs the attrition at the same time in several segments. This is the reason why, whole damage is also looked greatly increased inclination. Therefore, we progress study that find out damage factor by element and are more deeply about loss reduction by element part hereafter. Also, efficiency of solar photovoltaics system can be improved. we wish to forecast efficiency decrease of solar photovoltaics using neural network algorithm. Experiment result hereafter, We will expect to be remote management of solar cell.

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