• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.112-116
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• 1992

In this paper, a fuzzy logic controller(FLC) is designed for the pointing loop of the spin-stabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. The pointing loop of the spin-stabilized platform using FLC has better performance of step responses than a proportional controller in case of same loop hain through the software simulation and the experiment of implemented hardware.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.56-66
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• 1993

In this paper, a fuzzy logic controll(FLC) is designed for the pointing loop of the spinstabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. Through the simulation and the experiment, it can be seen that the designed FLC shows better performance than a conventional controller using the same loop gain.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1066-1070
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• 2003

Recently technologies have created new principle and theory but the PID control system remains its popularity as the PID controller contains simple structure, including maintenance and parameter adjustment being so simple. Thus, this paper proposes auto tune PID by fuzzy logic controller based on FPGA which to achieve real time and small size circuit board. The digital PID controller design to consist of analog to digital converter which use chip TDA8763AM/3 (10 bit high-speed low power ADC), digital to analog converter which use two chip DAC08 (8 bit digital to analog converters) and fuzzy logic tune digital PID processor embedded on chip FPGA XC2S50-5tq-144. The digital PID processor was designed by fundamental PID equation which architectures including multiplier, adder, subtracter and some other logic gate. The fuzzy logic tune digital PID was designed by look up table (LUT) method which data storage into ROM refer from trial and error process. The digital PID processor verified behavior by the application program ModelSimXE. The result of simulation when input is units step and vary controller gain ($K_p$, $K_i$ and $K_d$) are similarity with theory of PID and maximum execution time is 150 ns/action at frequency are 30 MHz. The fuzzy logic tune digital PID controller based on FPGA was verified by control model of level control system which can control level into model are correctly and rapidly. Finally, this design use small size circuit board and very faster than computer and microcontroller.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.403-414
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• 1995

It is very difficult to quantize the ECG analysis because the decision criterion for ECG is different with each other depending on the medical specialists of the heart and there are measured detecting errors for each ECG measurement system. Therefore, we developed the real-time ECG identification system using digital fuzzy processor for STD-BUS, in order to reduce ambiguity generated in the process of ECG identification and to analyze the irregular ECG stastically to ECG's repetition interval. The variables such as AGE (months), width of QRS, average RRI, and RRI were used to classify the ECG, and were applied to ECG signal indentification system which is developed for the purpose of research. It was found that the automatic diagnosis of ECG signal was possible in the real time process which was impossible in general process of algorithm.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.123-126
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• 2006

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 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 Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1520-1526
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• 2003

Design and implementation method or the 100[W] DD/AC invertor using PICl6C711 processor is described in this paper. Especially, fuzzy inference algorithm is involved in this system which can be adaptive to the environment variation. Input/output control and power consumption monitoring is controlled based on PIC16C711 processor, which compute the optimal values acquired from inference engine. Such experimental as function, efficiency, motoring are performed and experimental results showed that monitoring error is less than 2% and widely used in the area of industrial fields.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.119-124
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• 2001

In this pattern recognition on the large volumes of remote sensing satellite images, the inference time is much increased. In the case of the remote sensing data [5] having 4 wavebands, the 778 training patterns are learned. Each land cover pattern is classified by using 159, 900 patterns including the trained patterns. For the fuzzy classification, the 778 fuzzy rules are generated. Each fuzzy rule has 4 fuzzy variables in the condition part. Therefore, high performance parallel fuzzy inference system is needed. In this paper, we propose a novel parallel fuzzy inference system on T3E parallel computer. In this, fuzzy rules are distributed and executed simultaneously. The ONE_To_ALL algorithm is used to broadcast the fuzzy input to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. This system can be used in a large expert system that ha many inference variables in the condition and the consequent part.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.13-17
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• 2024

In this paper, union-based rule antecedent neuro-fuzzy controller, which can guarantee a parsimonious knowledge base with reduced number of rules, is proposed. The proposed neuro-fuzzy controller allows union operation of input fuzzy sets in the antecedents to cover bigger input domain compared with the complete structure rule which consists of AND combination of all input variables in its premise. To construct the proposed neuro-fuzzy controller, we consider the multiple-term unified logic processor (MULP) which consists of OR and AND fuzzy neurons. The fuzzy neurons exhibit learning abilities as they come with a collection of adjustable connection weights. In the development stage, the genetic algorithm (GA) constructs a Boolean skeleton of the proposed neuro-fuzzy controller, while the stochastic reinforcement learning refines the binary connections of the GA-optimized controller for further improvement of the performance index. An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation and experiment.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.380-383
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• 2001

The paper presents a cost effective and increased performance position servo system using the TMS320F240 digital signal processor (DSP) produced by Texas Instruments as microprocessor and Brushless Direct Current Motor (BLDCM) as executor. In order to make up for the drawback of conventional PID controls, the fuzzy PID is employed. The result of simulations and experiments has confirmed that the whole system is simple and reliable; the robustness of system is improved by using fuzzy PID.