• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.11
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• pp.757-762
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• 2000

This paper presents a digital controller for three-phase Boost Converter. Generally, the conventional Space-Vector Pulse Width Modulation (SVPWM) have complex computation. Thereby, it should be implemented with high performance processor. In order to reduce calculation burden of the conventional SVPWM, digital controller which has a simplified SVPWM algorithm is designed in this study. A proposed digital controller consists of fuzzy pwm controller and prediction controller. In simulations and experiments, the proposed digital controller is validated.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.113-116
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• 1990

In this paper, An expert system for electric furnace with time delay is proposed. The expert system uses Fuzzy control theory. The conventional controller uses Auto-Tuning control theory. From experiment, we can obtain that the response of expert system is superior to the response of the conventional controller. In this experiment, the expert controller is implemented with the IBM PC. The 8751 One chip processor controling the electric furnace is used.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.141-144
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• 2001

In this paper, we proposed a neural network controller with a fuzzy compensator which compensate a output of neural network controller. Even if learn by neural network controller, it can occur a bad results from disturbance or load variations. So in order to adjust above case. we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning an inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. In order to confirm a performance of the proposed controller, we implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.223-229
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• 2018

Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.368-373
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• 2007

In recent year s there have been increasing interests in real-time object tracking with image information. This dissertation presents a real-time object tracking method through the object recognition based on neural networks that have robust characteristics under various illuminations. This dissertation proposes a global search and a local search method to track the object in real-time. The global search recognizes a target object among the candidate objects through the entire image search, and the local search recognizes and track only the target object through the block search. This dissertation uses the object color and feature information to achieve fast object recognition. The experiment result shows the usefulness of the proposed method is verified.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.334-341
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• 2003

In this paper, we proposed a recurrent time delayed neural network(RTDNN) controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network(TDU) controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.371-376
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• 2003

In general, the electronic forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by speed control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the electronic forklift is demanded the robust drive mode. Some cases of the mode, there are trouble in torque and speed control following slope capacity. The control is sensitive concerning with slope angle and output speed, various control method is studied for stability of speed control. We apply speed controller for the self-tuning using DSP(TMS320F240) as main controller for high speed processor, embody dynamic characteristic of control compared the PI control to the fuzzy control.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.1-8
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• 1997

In this paper, we propose a new intelligent query processing system for relational database !systems. By analyzing previous research results related with fuzzy queries, a new intelligent query processing sysytem is developed and the role of each module including intelligent query processor is defined and :some algorithms for parser, query translation module, inference engine, semantic DB and result com-poser are suggested. By applying a typical example to the proposed intelligent query processing liysytem, reasonable results for the ambiguous query are drawn, and therefore it shows a promising model returning ordered result for both the ambiguous queries and general queries.

• Journal of Biomedical Engineering Research
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• v.12 no.1
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• pp.1-7
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• 1991

This paper describes and discusses the employment of HMG pattern analysis to provide upper-motor-neuron paraplegics with patient-responsive control of FES ( functional electrical stimulation) for the purpose of walker-supported walking. The use of above-lesion EMG signals as a solution to the control problem is considered. The AR(autoregressive)parameters are identified by time-varying nonstationary Kalman filler algorithm using DSP chip and classified by fuzzy theory. The control and stimuli part of the below-lesion are based on micro-processor(8031). The designed stimulator is a 4-channel version. The experiments described above have only attempted to discriminate between standing function and sit-down function A further advantge of the this system Is applied for motor rehabilitation of social readaption of paralyzed humans.