• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.354-358
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• 1992

This paper describes a development of high speed fuzzy inference circuit for the industrialprocesses. The hardware fuzzy inference circuit is developed utilizing a hardware fuzzy inference circuit is developed utilizing a DSP and a multiplier and accumulator chip. To enhance the inference speed, the pipeline disign is adopted at the bottleneck and the general Max-Min inference method is slightly modified as Max-max method. As a results, the inference speed is evaluated to be 100 KFLIPS. Owing to this high speed feature, satisfactory application can be attained for complex high speed motion control as well as the control of multi-input multi-output nonlinear system. As an application, the developed fuzzy inference circuit is embedded to a PLC (Porgrammable Logic Controller) for industrial process control. For the fuzzy PLC system, to fascilitate the design of the fuzzy control knowledge such as membership functions, rules, etc., a MS-Windows based GUI (Graphical User Interface) software is developed.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.71-71
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• 2000

In this paper, the fuzzy system is applied to MCZ Crystal Grower using at industrial field. The existing controller, which is PID controller, has a fixed gain and as a result of it it can not have an adaptive control function against the error or disturbance. Hence, the machine operator should always check the process status and when the error is occurred, the quality and the productivity may be decreased by each personal capability. In order to remove this drawback, a fuzzy control system which is known to be adaptive and flexible is applied to the machine. After applying the fuzzy system, and compared with the existing system, the diameter deviation and the defects were decreased. we proved the possibility of application fuzzy system to single silicon crystal grower.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.81-88
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• 2004

GIS (geographic information system) applications increasingly require the representation of geospatial objects with fuzzy extent and querying of time-varying information. In this paper, we Introduce a FSTDB (fuzzy spatiotemporal database) to represent and manage states and events causing changes of dynamic fuzzy objects using fuzzy set theory. We also propose the algorithms for the operators to be included in a GIS to make it able to answer queries depending on fuzzy predicates during a time interval and a method to identify the development process of objects during a certain period based on the designed database. They can be used in application areas handling time-varying geospatial data, including global change (as in climate or land cover change) and social (demographic, health, ect.) application.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.51-60
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• 2008

A solution method for fuzzy linear programs is proposed. A fuzzy linear program is converted to a crisp linear program with average indices being applied to the objective function and constraints. A comparative analysis between the proposed average index approach and the possibilistic approach is given. As an application example, the proposed method is applied to the linear programming model for fuzzy data envelopment analysis, and the result is compared with that of the possibilistic approach.

• Korean Journal of Mathematics
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• v.29 no.1
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• pp.137-167
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• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.63-74
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• 2002

This paper presents an application result of on-line fault diagnosis system for glass melting furnace using a fuzzy expert system. Operators maintain the furnace using the furnace Knowledge and experience, which directly influence the furnace and glass product. Firstly, knowledge and experience is achieved and analyzed to implement the furnace Knowledge and experience into fuzzy expert system. The acquired Knowledges determined as a crisp rule or a fuzzy rule to expect its characteristics. And, a linear regression is used as the input of fuzzy rule to consider the exact knowledge of human operator. The fuzzy expert system is implemented with G2 which is an on-line expert system tool of Gensym Co. The application to a production furnace of Samsung-Corning Co. in Suwon shows successful results of proposed fuzzy expert system.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.831-846
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• 2011

There are several methods, in the literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, a new method (based on fuzzy linear programming formulation) is proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems with a new representation of trapezoidal fuzzy numbers. The advantages of the proposed method over existing method are discussed. Also, it is shown that it is better to use the proposed representation of trapezoidal fuzzy numbers instead of existing representation of trapezoidal fuzzy numbers for finding the fuzzy optimal solution of fuzzy transportation problems. To illustrate the proposed method a fuzzy transportation problem (FTP) is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.24-34
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• 1994

Scientific involvement in complex decision-making system, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced and their weighted value structure is ignorant, the systems are become more complex. This paper presents a fuzzy dependenced relation model and fuzzy measure model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation and fuzzy measure in fuzzy systems theory. For the application of the model, a numdrical example is quoted.