• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• 한국정밀공학회지
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• 제20권11호
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• pp.91-99
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• 2003

When the driver suddenly depresses the brake pedal under critical conditions, the desired trajectory of the vehicle can be changed. In this study, the vehicle dynamics and fuzzy logic controller are used to control the vehicle trajectory. The dynamic vehicle model consists of the engine, the rotational wheel, chassis, tires and brakes. The engine model is derived from the engine experimental data. The engine torque makes the wheel rotate and generates the angular velocity and acceleration of the wheel. The dynamic equation of the vehicle model is derived from the top-view vehicle model using Newton's second law. The Pacejka tire model formulated from the experimental data is used. The fuzzy logic controller is developed to compensate for the trajectory error of the vehicle. This fuzzy logic controller individually acts on the front right, front left, rear right and rear left brakes and regulates each brake torque. The fuzzy logic controlling each brake works to compensate for the trajectory error on the split - $\mu$ road conditions follows the desired trajectory.

• Computers and Concrete
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• 제21권1호
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• pp.103-110
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• 2018

This study introduces the supervised committee fuzzy model as a hybrid fuzzy model to predict compressive strength (CS) of geopolymers prepared from alumina-silica products. For this purpose, more than 50 experimental data that evaluated the effect of $Al_2O_3/SiO_2$, $Na_2O/Al_2O_3$, $Na_2O/H_2O$ and Na/[Na+K] on (CS) of geopolymers were collected from the literature. Then, three different Fuzzy Logic (FL) models (Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Larsen fuzzy logic (LFL)) were adopted to overcome the inherent uncertainty of geochemical parameters and to predict CS. After validating the model, it was found that the SFL model is superior to MFL and LFL models, but each of the FL models has advantages to predict CS. Therefore, to achieve the optimal performance, the supervised committee fuzzy logic (SCFL) model was developed as a hybrid method to combine the benefits of individual FL models. The SCFL employs an artificial neural network (ANN) model to re-predict the CS of three FL model predictions. The results also show significant fitting improvement in comparison with individual FL models.

• 대한전자공학회논문지
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• 제24권4호
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• pp.701-707
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• 1987

This paper is concerned with an accurate delay time modling of the ED MOS logic gates and its application to the multiple delay logic simulator. The proposed delay model of the ED MOS logic gate takes account of the effects of not only the loading conditions but also the slope of the input waveform. Defining delay as the time spent by the current imbalance of the active inverter to charge and discharge the output load, with respect to physical reference levels, rise and fall model delay times are obtained in an explicit formulation, using optimally weighted imbalance currents at the end points of the voltage transition. A logic simulator which uses multiple rise/fall delays based on the model as decribed in the above has been developed. The new delay model and timing verification method are evaluated with repect to delay accuracy and execution time.

• 한국BIM학회 논문집
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• 제14권1호
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• pp.30-38
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• 2024

This study aims to propose a smart city governance logic model that can accommodate more diverse information service systems by mixing hub-and-spoke and blockchain technologies as a data management model. Specifically, the research focuses on deriving the logic of an operating system that can work across smart city planning based on the two data governance technologies. The first step of the logic is the generation and collection of information, which is first divided into information that requires information protection and information that can be shared with the public, and the information that requires privacy is blockchainized, and the shared information is integrated and aggregated in a data hub. The next step is the processing and use of the information, which can actively use the blockchain technology, but for the information that can be shared other than the protected information, the governance logic is built in parallel with the hub-and-spoke type. Next is the logic of the distribution stage, where the key is to establish a service contact point between service providers and beneficiaries. Also, This study proposes the establishment of a one-to-one data exchange relationship between information providers, information consumers, and information processors. Finally, in order to expand and promote citizen participation opportunities through a reasonable compensation system in the operation of smart cities, we developed virtual currency as a local currency and designed an open operation logic of local virtual currency that can operate in the compensation dimension of information.

• Journal of Mechanical Science and Technology
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• 제15권11호
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• pp.1482-1489
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• 2001

Thermally-induced errors originating from machine tool errors have received significant attention recently because high speed and precise machining is now the principal trend in manufacturing proce sses using CNC machine tools. Since the thermal error model is generally a function of temperature, the thermal error compensation system contains temperature sensors with the same number of temperature variables. The minimization of the number of variables in the thermal error model can affect the economical efficiency and the possibility of unexpected sensor fault in a error compensation system. This paper presents a thermal error model with minimum number of variables using a fuzzy logic strategy. The proposed method using a fuzzy logic strategy does not require any information about the characteristics of the plant contrary to numerical analysis techniques, but the developed thermal error model guarantees good prediction performance. The proposed modeling method can also be applied to any type of CNC machine tool if a combination of the possible input variables is determined because the error model parameters are only calculated mathematically-based on the number of temperature variables.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• 대한기계학회논문집A
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• 제24권10호
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• 제어로봇시스템학회논문지
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• 제13권4호
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• pp.352-357
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• 2007

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

• 한국지능시스템학회논문지
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• 제19권1호
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• pp.13-18
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• 2009

인간의 감성은 애매하고 외부로 부터의 자극에 따라 다양하게 변화한다. Plutchik은 기본적인 패턴을 8가지 행동 패턴으로 분류한 감성 모델을 제시하고, 또 순수감성의 조합으로부터 혼합 감성을 추론하였다. 본 논문에서는 다치 논리함수의 차분 성질을 이용한 다치 논리 오토마타 모델을 이용하여 Plutchik의 감성 모델을 처리할 수 있는 방법을 제안한다. 여기서 제안된 감성처리 모델은 감성 데이터 해석과 처리에 널리 활용될 수 있을 것이다.