• 한국인터넷방송통신학회논문지
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• 제23권5호
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• pp.71-76
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• 2023

본 논문에서는 딥러닝을 이용한 영상 분할에서 성능을 향상하기 위해 퍼지 논리를 적용하는 퍼지 딥러닝 모델인 퍼지 U-Net을 제안한다. 퍼지 논리를 이용한 퍼지 모듈을 영상 분할에서 우수한 성능을 보이는 딥러닝 모델인 U-Net에 결합하여 다양한 형태의 퍼지 모듈을 시뮬레이션하였다. 제안된 딥러닝 모델의 퍼지 모듈은 이미지의 특징맵과 해당 분할 결과 사이의 본질적이고 복잡한 규칙을 학습다. 이를 위해 치아 CBCT 데이터에 적용하여 제안된 방법의 우수성을 입증하였다. 시뮬레이션 결과 제안된 퍼지 U-Net에서 더하기 스킵 연결을 사용한 모델의 ADD-RELU 퍼지 모듈 구조의 성능이 시험용 데이터에 대해 0.7928로 가장 우수한 것을 볼 수 있다.

• 한국시뮬레이션학회논문지
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• 제17권4호
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• pp.1-9
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• 2008

본 논문은 Programmable Logic Controller(PLC) 시뮬레이션을 하기 위한 공장 모델(Plant Model)을 자동으로 생성하는 절차에 대해 기술한다. PLC 프로그램은 공정을 제어하는 로직에 관한 정보이며 그 자체로 공장 모델에 대한 어떤 정보도 포함하고 있지 않기 때문에 시뮬레이션을 위해서는 PLC 프로그램에 대응하는 공장 모델이 반드시 필요하다. 지금까지 PLC 시뮬레이션을 위한 공장 모델은 사용자가 직접 구축하는 방식으로 모델링 되었으나 이는 많은 노력과 공정로직의 완전한 이해 및 시뮬레이션 지식이 요구된다. 이런 어려움을 극복하기 위해 논문은 PLC 프로그램의 심볼테이블(Symbol table)로부터 공장모델을 자동으로 생성하는 과정을 제안한다. 이를 위해P LC 심볼이 공장 모델의 생성을 위한 정보를 포함시키는 PLC 심볼의 작명 규칙을 제안한다. 입력된 심볼 리스트를 분석함으로써 공장 모델을 자동으로 추출할 수 있으며 간단한 예제 공정을 대상으로 구현해 본다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.166-169
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• 2002

The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model, and the GA is applied to identify this fuzzy model. The proposed method is compared with the AIMM algorithm in simulations.

• 한국수학사학회지
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• 제27권1호
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• pp.47-57
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• 2014

This paper aims to evaluate works of Frege and G$\ddot{o}$del, who play the trigger role in development of logic, by Knowledge Change Model. It identifies where their positions are in the model respectively. For this purpose I suggest types of knowledge change and their criteria for the evaluation. Knowledge change are classified into five types according to the degree of its change: improvement, weak glorious revolution, glorious revolution, strong glorious revolution, and total revolution. Criteria to evaluate the change are its contents, influence, pervasive effects, and so forth. The Knowledge Change Model consists of the types and the criteria. I argue that in the model Frege belongs to the total revolution and G$\ddot{o}$del to the weak glorious revolution. If we accept that the revolution in logic initiated by Frege was completed by G$\ddot{o}$del, it is a natural conclusion.

• 한국CDE학회논문집
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• 제4권3호
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• pp.238-246
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• 1999

The modeling method to support product development processes (PDP) must have certain characteristics including the ability to represent multiple viewpoints of the product development and integrate with currently available analysis and design methods based on CE concept. This paper describes the reference model to support multiple viewpoints (PPO: Products, Processes, and Organizations/Resources viewpoints) of the product development processes, from which each model (Products model, Processes model, and Organizations/Resources model) can be extracted, as well as produces PPO data schema. This reference model has associative relationships among the products, processes, and organizations/resources. To allow the extensibility to support design evolution, we propose structured dat representation methods using semantic network, which can be constructed through first-order logic. The product development processes is so represented by specifying entities and semantic relationships among them hat he appropriate information can be accessed and all of the relevant attributes about the entities can be retrieved simultaneously.

• 산업경영시스템학회지
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• 제37권4호
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• pp.1-11
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• 2014

This paper addresses the emotion computing model for software affective agents. In this paper, emotion is represented in valence-arousal-dominance dimensions instead of discrete categorical representation approach. Firstly, a novel emotion model architecture for affective agents is proposed based on Scherer's componential theories of human emotion, which is one of the well-known emotion models in psychological area. Then a fuzzy logic is applied to determine emotional statuses in the emotion model architecture, i.e., the first valence and arousal, the second valence and arousal, and dominance. The proposed methods are implemented and tested by applying them in a virtual training system for children's neurobehavioral disorders.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권3호
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• pp.370-377
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• 2017

This paper presents a simple noise margin (NM) model of MOS current mode logic (MCML) gates especially in CMOS processes where a large device mismatch deteriorates logic reliability. Trade-offs between speed and logic reliability are discussed, and a simple yet accurate NM equation to capture process-dependent degradation is proposed. The proposed NM equation is verified for 130-nm, 110-nm, 65-nm, and 40-nm CMOS processes and has errors less than 4% for all cases.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.44-47
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• 1996

Bang-bang control law provides the optimal solution for a minimum-time control problem, but ignores the intermediate path except for the initial and final points. In this paper, a near minimum-time suboptimal fuzzy logic controller is introduced that can control the intermediate path. A dynamic model for a system is established using the average dynamics method of linearization. System model is continuously updated over the control time periods. This makes it suitable for high speed or variable payload applications. Bang-bang control theory is modified and used to derive the preliminary control law. A fuzzy logic algorithm is then applied to adjust and find the best solution. The solution will provide the suboptimal minimum-time control law which can avoid obstacles in the workspace.

• 한국생산제조학회지
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• 제21권5호
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• pp.691-696
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• 2012

In this study, a rigid multi-body dynamic model has been developed for mechatronic analysis to evaluate dynamic behavior of a machine tool. The development environment was the commercialized analysis tool, ADAMS, for rigid multi-body dynamic analysis. A simplified servo control logic was implemented in the tool using its functions in order to negate any external tool of control definition. The advantage of the internal implementation includes convenience of the analysis process by saving time and efforts. Application of this development to a machine tool helps to evaluate its dynamic behavior against feeding its component, to calculate the motor torque, and to optimize parameters of the control logic.