• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.104-111
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• 1999

A semi-active suspension system for a vehicle using an Electrorheological Fluid damper has been studied. Apparent viscosity of ERF(Electrorheological Fluid) can be changed rapidly by applying electric field. The damping force of ER damper can be selectively controlled by employing electric field to the ER fluid domain. This paper deals with a two-degree-of-freedom suspension using the ER damper for a quarter car model. An intelligent control method using fuzzy control with genetic algorithm has been employed to control the damping force of the ER damper. The GA designs the optimal structure and performance of Fuzzy Net Controller having hybrid structure. The designed fuzzy net controller has been compared with the skyhook type controller for a quarter car model. The computer simulation results show that the semi-active suspension with ER damper has a good performance in the sense of ride quality with less vibration for ground vehicle.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.487-492
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• 2004

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. In general, the modeling method of CDES has been studied many times, but that of FDES hasn't been nearly studied by qualitative character and scarcity of applicated system. This paper models traffic system with FDES's character in FTTPN and designs a traffic signal controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.10
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• pp.1833-1840
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• 1992

In the diagnostic process for automobile, Neuro-Fuzzy technique was compared with the conventional diagnostic method for the verification of performance, and proto-type system was developed. For the utilities of the system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then data were analyzed using octave band processing and pattern recognition using hamming network algorithm. In order to raise the reliability of the diagnostic results by considering many operating variables and condition of automobile to be diagnosed, fuzzy inference technique was applied in combining several information. The validation of this diagnostic system was examined through computer simulation and experiment, and it showed an acceptable performance for diagnostic process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1330-1333
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• 1993

In this paper, first, the fuzzy Petri net inference mechanism with learning function is proposed by using the extended fuzzy Petri nets. Secondly, a control system with this new inference engine is proposed. This system can do automatically and easily the knowledge acquisition from the operator's empirical data and can also be controller adaptively under the big parameter change.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.117-126
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• 2001

This paper presents fuzzy Pr/T nets to represent the fuzzy production rules of a knowledge-based system in the level of first-order predicate logic. The fuzzy Pr/T nets are fuzzy extension of the Pr/T nets. Based on the fuzzy Pr/T net, we propose a fuzzy reasoning algorithm. This algorithm is much closer to human intuition and reasoning than other methods because of using the proper belief functions according to fuzzy concepts in fuzzy production rules.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4724-4747
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• 2016

To efficiently reduce on-grid energy consumption, the admission control algorithm in the hybrid energy powered cellular network (HybE-Net) with base stations (BSs) powered by on-grid energy and solar energy is studied. In HybE-Net, the fluctuation of solar energy harvesting and energy consumption may result in the imbalance of solar energy utilization among BSs, i.e., some BSs may be surplus in solar energy, while others may maintain operation with on-grid energy supply. Obviously, it makes solar energy not completely useable, and on-grid energy cannot be reduced at capacity. Thus, how to control user admission to improve solar energy utilization and to reduce on-grid energy consumption is a great challenge. Motivated by this, we first model the energy flow behavior by using stochastic queue model, and dynamic energy characteristics are analyzed mathematically. Then, fuzzy logic based admission control algorithm is proposed, which comprehensively considers admission judgment parameters, e.g., transmission rate, bandwidth, energy state of BSs. Moreover, the index of solar energy utilization balancing is proposed to improve the balance of energy utilization among different BSs in the proposed algorithm. Finally, simulation results demonstrate that the proposed algorithm performs excellently in improving solar energy utilization and reducing on-grid energy consumption of the HybE-Net.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.872-877
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• 1991

This paper presents the composite control method using fuzzy and neural network theory. Fuzzy theory is applied to make control rules and neural net is used to learn them and to generate proper control signals. The electric furnace is controlled to maintain the desired temperature and to minimize the fluctuation of the temperatures in various locations inside the furnace. This controller consists of three neural nets which deal with the average of the temperatures, variances of them and the temperature stabilizing mechanism. Experiments are performed with the target temperatures of 70.deg. C and 80.deg. C. Test results show that this simple method is very effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.2
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• pp.119-126
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• 2001

시간 페트리 네트는 실시간 값을 갖는 이산사건 시스템을 모델링하고 해석하기 위한 방법중 하나이다. 시간 페트리 네트는 각 트랜지션에 대하여 두 개의 시간 값, 최초 발화 시간 $\alpha$$_{i}$와 최종 발화 시간 $\beta$$_{i}$를 갖는다. 본 논문에서는 최적 발화 시간을 결정하기 위하여 퍼지 이론을 적용한 퍼지 트랜지션 시간 페트리 네트를 제안하였다. 퍼지 트랜지션 시간 페트리 네트의 트랜지션 점화 시간 ${\gamma}$$_{i}$는 고정 최초 발화 시간 $\alpha$$_{i}$와 고정 최종 발화 시간 $\beta$$_{i}$ 사이에서 어떠한 복잡한 계산 절차나 임의의 조건 없이 입력정보를 이용한 퍼지 이론으로부터 결정된다. 교차로에서 교통 신호제어기는 퍼지 트랜지션 시간 페트리 네트에 의하여 모델링되고 해석되었다. 퍼지 트랜지션 시간 페트리 네트의 중요한 특성은 교통 신호기의 모델링과 시뮬레이션에 의해서 보여진다. 의해서 보여진다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.70-75
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• 1997

This paper proposes a new approach to the design of fuzzy-neuro control for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.30-41
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• 1992

As a general model of rule-based systems, we propose a model for a fuzzy production system having chaining rules and an inference engine associated with the model. The concept of so-called 'fuzzy petri nets' is used to model the fuzzy production system and the inference engine is designed to be capable of handling inexact knowledge. The fuzzy logic is adopted to represent vagueness in the rules and the certainty factor is used to express uncertainty of each rules given by a human expert. Parallel, inference schemes are devised by transforming Fuzzy Petri nets to matrix formula. Futher, the inference engine mechanism under the Mamdani's implication method can be desceribed by a simple algebraic formula, which makes real time inference possible.