• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.62-69
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• 2000

In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PID control and a fuzzy precompensated PID control in dynamic responses about the load disturbances of power system and is convinced robustness reliableness in view of structure.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2992-2994
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture. is systematically conducted for the automatic controlled system. In this paper, a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA: Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system (FMES: Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally. the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.27-33
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• 2016

The heat recovery system that was applied in this study, is the energy-saving type that can produce the maximum cooling capacity less power in use. In order to have a more precise control function the temperature and humidity of the constant temperature and humidity machine, control algorithm is applied to designed a fuzzy PID controller, and the outside air compensation device (air-cooled) demonstrated excellent ability to dehumidify the moisture, $-20^{\circ}C$ in winter. High efficiency and the low-noise type sirocco fan operate quitely and designed to fit the bottom-up and top-down in accordance with the characteristics of equipment. as a result of experiment data, the conversion efficiency is 95% or more, power recovery time is within 5sec, stop delay time is within 30sec, pump down time is 10sec, pump delay time is 5sec, heating delay time is 5sec, temperature deviation is ${\pm}2^{\circ}C$ (cooling deviation: $2^{\circ}C$, Heating deviation : $2^{\circ}C$), humidity deviation is a ${\pm}5%$ (humidification deviation 3.0%, dehumidification deviation 3.0%). Recently, ubiquitous technology is important. so, the constant temperature and humidity machine designed to be able to remotely control to via the mobile phone, and more scalable to support MMI software and automatic interface. Further, the life of the parts and equipment is extended by the failure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2769-2774
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• 2013

The key of USN(Ubiquitous Sensor Network) technology is low power wireless communication technology and proper resource allocation technology for efficient routing. The distinguished resource allocation method is needed for efficient routing in sensor network. To solve this problems, we propose an algorithm that can be adopted in USN with making up for weak points of PQ and WRR in this paper. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assign the weight of WRR scheduler with checking the Queue status of each class in sensor network. From simulation results, the proposed algorithm improves the packet loss rate of the EF class traffic to 6.5% by comparison with WRR scheduling method and that of the AF4 class traffic to 45% by comparison with PQ scheduling method.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.227-232
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• 2004

Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4％ error during a braking maneuver.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.494-499
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• 2007

In this paper we realized a system, if a user selects the area of the important parts or the arrangement parts when he reads the books or the papers, which amends, stores and readjusts the characters that are included in the selected area by outputting the characters to the word processor in sequence. If a user selects what he wishes lot with his finger, the system detects the movement of the finger by applying the hand recognition algorithm and recognizes the selected area. The system converts the distance of the width and the length of the selected area to the number of the pulse, and controls the motor to move the camera at the position. After the system scales up/down the zoom to be able to recognize the character and controls the focus to the regulated zoom closely, it controls the focus in detail to get more distinct image by using the difference of the light and darkness. We realize the recognition and editing support system of korean language that converts the obtained images to the document by applying the character recognition algorithm and arrange the important parts.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.369-376
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• 2015

Chemicals are injected in order to remove a variety of organic substances contained in the water purification plant influent. It can be determined with measuring sedimentation turbidity 4~7 hours later, whether the chemical dosage rate is proper or not, which make the real-time feedback control impossible. In addition, manual operation in accordance with the Jar-Test carried out in the laboratory and the operator's experience may cause the experimental and human error by the changes of organic characteristics and water quality. Especially at night ad weekend, the rate have been determined only by the operator judgment owing to environment engineer's absence. Therefore, the decision of optimal chemical dosage rate using proposed intelligent control algorithm is expected to result in real-time injection and cost reduction.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.226-238
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• 2007

In this paper, we present a novel fully distributed topology control protocol that can construct the multiple-ring topology of Minimal Connected Dominating Set (MCDS) as the transport backbone for mobile ad hoc networks. It makes a topology from the minimal nodes that are chosen from all the nodes, and the constructed topology is comprised of the minimal physical links while preserving connectivity. This topology reduces the interference. The all nodes work as the nodes of the distributed parallel Boltzmann machine, of which the objective function is consisted of two Boltzmann factors: the link degree and the connection domination degree. To define these Boltzmann factors, we extend the Connected Dominating Set into a fuzzy set, and also define the fuzzy set of nodes by which the multiple-ring topology can be constructed. To construct the transport backbone of the mobile ad hoc network, the proposed protocol chooses the nodes that are the strong members of these two fuzzy sets as the clusterheads. We also ran simulations to provide the quantitative comparison against the related works in terms of the packet loss rate and the energy consumption rate. As a result, we show that the network that is constructed by the proposed protocol has far better than the other ones with respect to the packet loss rate and the energy consumption rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.558-566
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• 2015

LED, the next-generation light source, rapidly develops and has advantages of low power, high efficiency, and long life. Accordingly, an interest in lightings by using LED rises. If emotional lighting is implemented by using LED, all colors can be represented by using 3 primary colors of light, differently from the conventional single-color lighting. LED emotional lightings which can control human emotions continue to be developed thanks to these advantages. This study was conducted to design an algorithm for expressing LED emotional lighting in line with the situation and temperature by extracting colors for concentration and resting situations in indoor environment and mixing them with colors of the temperature felt by user. The LED emotional lighting designed with a neuro-fuzzy system was found to have effects on user's emotions during concentration and resting.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.