• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.149-158
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• 1994

Recently the fuzzy control is widely used as a tool for constructing automatic control systems which can replace the manual operation of large-scale nonlinear plants. In most applications of the fuzzy control however it is hard to meet the requirement of the operation time. In some real-time control the fuzzy control scheme requires too much computing time for fuzzification inference and defuzzification. To reduce the computing time there may be two alternatives the development of a new operation algorithm and the design of high-speed fuzzy hardware. In this paper to solve the problem of reducing the fuzzy operation time we propose a new high-speed fuzzy hardware scheme which has merits of its generality and extensibility. Finally we verify the proposed fuzzy hardware.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.662-665
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• 2001

As the fuzzy control is applied to servo system the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$-level set decomposition of fuzzy sets by quantize $\alpha$-cuts. This method can be easily implemented with analog hardware. The influence of quantization levels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of do servo system. It examined useful with experiment for dc servo system.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.200-209
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• 2004

The fuzzy control based on $\alpha$-level fuzzy set decomposition. It is known to produce quick response and calculating time of fuzzy inference. This paper derived the embodiment computational algorithm for defuzzification by min-max fuzzy inference and the center of gravity method based on $\alpha$-level fuzzy set decomposition. It is easy to realize the fuzzy controller hardware. based on the calculation formula. In addition. this study proposed a circuit that generates PWM actual signals ranging from fuzzy inference to defuzzification. The fuzzy controller was implemented with mixed analog-digital logic circuit using the computational fuzzy inference algorithm by min-min-max and defuzzification by the center of gravity method. This study confirmed that the fuzzy controller worked satisfactorily when it was applied to the position control of a dc servo system.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.38-40
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• 2000

In this paper we propose a calculation method for fuzzy control based on quantized $\alpha$-cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference results is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzification by gravity center method by PWM are also presented.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.133-136
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• 2001

In this paper, we propose a calculation method for fuzzy control based on quantized $\alpha$ -cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference result is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzificaion by gravity center method by PWM are also presented.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.147-150
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• 2000

Hausdorff distance(HD) commonly used measures for object matching, and calculates the distance between two point set of pixels in two-dimentional binary images without establishing correspondence. And it is realized as the image filter applying the fuzzy. In this paper, the fuzzy hardware realizes in order to construct the image filter applying HD, also, propose as the method for the noise removal using it in the image. MIN-MAX circuit designs the circuit using MAX-PLUS, and the fuzzy HD hardware results are obtained to the simulation. And then, the previous computer simulation is confirmed to the result by using MATLAB.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.17-27
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• 1996

More fuzzy hardware are expected to be utilized in the future to construct fuzzy logic controllers (FLCs). It is hard to find an existing fuzzy hardware which is adopting advanced functions such as self-tuning algorithm in addition to the conventional inference calculation. That is mainly because conventional self-tuning algorithms designed to implement with some hardware circuits is required for fuzzy hardwares to have self-tuning capability. As a first step toward the feature, a novel self-tuning algorithm is proposed in this paper. Based on the search method, the main idea of the proposed algorithm is to detemine valid ranges of input variables of an FLC in order to maximize performance indices fo the control system. The performance indices are so ismple as to be realized by hardware circuit. in dadditon to the conventional scaling-factor adjustment, the algorithm adjusts offset values as well, which, in effect, modifies fuzzy rules of the FLC. To justify the performance of the proposed algorithm, a simulation study is executed.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.148-154
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• 2012

Purpose: In order to improve road-friendliness of heavy vehicles, a fuzzy hybrid control strategy consisting of a hybrid control strategy and a fuzzy logic control module is proposed. The performance of the proposed strategy should be effectively evaluated using a hardware-in-the-loop (HIL) simulation model of a semi-active suspension system based on the fuzzy hybrid control strategy prior to real vehicle implementations. Methods: A hardware-in-the-loop (HIL) simulation system was synthesized by utilizing a self-developed electronic control unit (ECU), a PCI-1711 multi-functional data acquisition board as well as the previously developed quarter-car simulation model. Road-friendliness of a semi-active suspension system controlled by the proposed control strategy was simulated via the HIL system using Dynamic Load Coefficient (DLC) and Dynamic Load Stress Factor (DLSF) criteria. Results: Compared to a passive suspension, a semi-active suspension system based on the fuzzy hybrid control strategy reduced the DLC and DLSF values. Conclusions: The proposed control strategy of semi-active suspension systems can be employed to improve road-friendliness of road vehicles.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.907-910
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• 1993

This paper describes the use of fuzzy control and decision making to simulate the control of traffic flow at an intersection. To show the value of fuzzy logic as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller, a computer simulation was constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment, and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. In the hardware verifications, fuzzy logic was used to control acceleration of a model train on a circular path. For the software experiment, the fuzzy logic controller proved better than conventional control methods, especially in the case of highly uneven traffic flow between different directions. On the hardware si e of the research, the fuzzy acceleration control system showed a marked improvement in smoothness of ride over crisp control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1294-1310
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• 2010

User authentication using fingerprint information provides convenience as well as strong security. However, serious problems may occur if fingerprint information stored for user authentication is used illegally by a different person since it cannot be changed freely as a password due to a limited number of fingers. Recently, research in fuzzy fingerprint vault system has been carried out actively to safely protect fingerprint information in a fingerprint authentication system. In addition, research to solve the fingerprint alignment problem by applying a geometric hashing technique has also been carried out. In this paper, we propose the hardware architecture for a geometric hashing based fuzzy fingerprint vault system that consists of the software module and hardware module. The hardware module performs the matching for the transformed minutiae in the enrollment hash table and verification hash table. On the other hand, the software module is responsible for hardware feature extraction. We also propose the hardware architecture which parallel processing technique is applied for high speed processing. Based on the experimental results, we confirmed that execution time for the proposed hardware architecture was 0.24 second when number of real minutiae was 36 and number of chaff minutiae was 200, whereas that of the software solution was 1.13 second. For the same condition, execution time of the hardware architecture which parallel processing technique was applied was 0.01 second. Note that the proposed hardware architecture can achieve a speed-up of close to 100 times compared to a software based solution.