• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.933-936
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• 1993

A high speed fuzzy processor using bipolar technology is proposed in this paper. The hardware system uses a high-speed current-mode membership function circuit and normalization technique. The new membership function circuit generates an ideal membership function of the fuzzy set and its circuit is also simple and available for VLSI implementation. Several techniques have been implemented to speed up response of the processor. The fuzzy processor has been designed and implemented in bipolar circuit technology. The experiments and simulations show that the response speed is below 100ms. It can also be expected that the fuzzy processor can be integrated on one chip and its response time is only about the order of nanoseconds.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.789-792
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• 1993

We have proposed a fuzzy model for behavior of vehicles in the road traffic simulation system with microscopic model for analyzing traffic jam in the broad areas. It can exactly simulate each vehicle's behavior. We propose a new hardware processor to simulate fuzzy decision-making mechanism for its model. This paper describes the functions, performance and structure of the hardware processor.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.146-149
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• 2000

In this paper, Computer Colour Matching and Kitchen System (CCMKS) is developed on the basis of delphi package and one-chip processor with fuzzy-PID control. CCMKS will be widely used in the colour dyeing industry as an integrated colour matching and dispensing system which have more advantages than the conventional matching or dispensing system, when controlling the real dyeing processes. Delphi is utilized in making database and search/matching routes. The developed matching function reduces the search and matching time to about one third. One-chip processor is designed and manufactured for the distributed control of three-phase induction motors. Fuzzy-PID control is applied to the speed control of three-phase induction motors for a very precise weight of colour at CCMKS. The developed kitchen function decreases the dispensing time to about one twentieth. The experimental results show CCMKS has more excellent search time, more precise weight and much high fidelity than conventional colour matching or dispensing system, in the performance.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.5
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• pp.71-79
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• 1995

This paper describes the design and implementation of dryer controller using the dual processor. This system has higher performance of system recovery from the noise than the existing single processor dryer. And in this paper temperature control method of Dryer using on-off fuzzy logic is proposed to improve the overshoot of temperature in dryer. Experimental results shows that the performance of fuzzy controller is better than that of controller based upon on-off control method.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.469-471
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• 1999

In this paper, the method of Space-Vector Pulse Width Modulation(SVPWM) with Fuzzy Logic Regulator(FLR) is proposed. In a conventional SVPWM, the procedures of phase transformation and choosing PWM patterns are complex. So, it should be implemented with high performance processor like Digital Signal Processor(DSP). In order to reduce a calculation burden, a proposed system adopts FLR. Using a linguistic contro strategy based on expert knowledge, FLR relieves the processor from a heavy computations. In simulations, the proposed system is validated.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.438-443
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• 2005

Handy paint rollers with simple or no patterns are generally used to transcribe its design to a wall just after painting. However, the types of the patterns are limited to several conventional ones, so that interior planners' or decorators' demands are gradually tending to getting attractive roller designs. In order to obtain abundant kinds of the roller designs, a new advanced 3D machining method should be established for cylindrical models. In this paper, a post-processor that can generate suitable NC data is proposed for multi-axis NC machine tools with a rotary unit. The 3D machining system with the post-processor is also presented for an attractive interior decorating. The machining system allows us to easily transcribe the relief designs from on a flat model to on a cylindrical model. The effectiveness of the proposed 3D machining system using the post-processor is demonstrated through some machining experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.12
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• pp.1262-1268
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• 1991

The electric furnace which has time delay and time varying characteristics cannot be controlled easily. In this paper, a fuzzy controller for a electric furnace is implemented using one chip processor 8751 and IBM PC. The fuzzy controller is implemented in the PC. The One chip processor 8751 can sense the furnace internal temperature and pass it to IBM PC and generate the driving signal for SSR. The membership function of the fuzzy controller is determined by Least Square method. from the experiments, we can show that the fuzzy controller can improve robustness to the load variation. And the settling time is reduce 4500 (sec) to 2500 (sec).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.975-976
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• 1993

This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1112-1118
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• 2007

We propose a new-focusing method for test handlers of compact camera module (CCM), The MMD (max-min difference) method is applied to calculate the focus value quickly considering the noisy output of CCM. Also, the fuzzy search method is applied to find the maximum focus value effectively. We design a fuzzy processor to control the lens position by focus values and brightness values, which improves the focusing performance in the sense of speed and processor memory. The proposed method is implemented by computer program and installed at the CCM test handler machines. The simulation results are presented to verify the usefulness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.80-92
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• 1997

This research focuses onan efficient control method of temperature for multiple points using only one processor. For a yarn production system, the surface temperature control of heaters are very important for quality control. Therefore, we designed a temperature controller for a draw and twist machine and applied Fuzzy-PWM algorithm to the controller. If we use a processor for the temperature control of multiple points with the conventional ON/OFF control, the control performance of the system becomes poor. To overcome these problems, we developed a new Fuzzy-PWM algorithm for the adjustment of power rate to the heaters in the conventional ON/OFF control. It is shown that this algorithm has the same effects as the PID algorithm for the temperature control of each point. The proposed algorithm is robust against the production condition and environment such as the reference temperature and the thickness of yarn, since the power rate to the heater is adjusted by Fuzzy Rules derived from the values of the reference termperatureand the thickness of yarn. To obtain optimal Fuzzy rulees, the control simulations are perfodrmed through the modelling of the heater and simulation of Fuzzy rules. This algorithm is applied for the multiple pont temperature controller and showed satisfactory performance.