• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.103-114
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• 2009

This study investigated perceived discomfort and reasons related to use three information technology products (personal computer, mobile phone and digital television remote controller), and extracted the universal design factors. 240 people (30 females and 30 males for four age groups) participated in the one-to-one interview type of questionnaire, and replied to degree of discomfort at level of items and the reasons of discomfort at level of detailed elements for each product. As a result, almost all age groups answered that using input buttons of mobile phone and remote controller and watching display of mobile phone caused discomfort. Binary logistic regression of the detailed elements showed that response rate of discomfort mostly increased with age, except for specific elements such as shape of mouse and remote controller, and location of function button of mobile phone. Some of the detailed elements had high response rate of discomfort from all age groups. The age groups also showed similar tendency for the elements to select one alternative for the reason of discomfort, but not for sound volume and size of mobile phone and button sensitivity of remote controller. Finally, the universal design factors were extracted for each product based on the results, and divided into common factors and factors classified by the age group. Through this study, we identified using practices of various age groups and their demands for the products. It is expected that extracted detailed elements can be considered as important design factors to design the products universally.

• Journal of IKEEE
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• v.24 no.4
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• pp.1184-1187
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• 2020

This paper proposes an in-vehicle network controller fully exploiting the advantages of UART (Universal Asynchronous Receiver/Transmitter) and CAN (Controller Area Network). UART is used in 1-to-1 communication and it exploits parity bit for data integrity check. The proposed in-vehicle network controller converts UART into CAN, which enables multiple communications along with 1-to-1 communication. Also, the proposed in-vehicle network controller exploits CRC (cyclic redundancy check) for data integrity check, which increases communication reliability. CAN is controlled by microprocessor, but the proposed in-vehicle network controller can be controlled by any devices compliant with RS-232, RS-422, and RS-485.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2548-2557
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• 1999

As the size of the FPD(Flat Panel Display) becomes larger and its resolution is higher, it is required a new controller to support these specifications. In this paper, we have designed a universal controller of a-Si TFT LCD which will dominate the future market. We propose a new type of a LCD controller, which is constructed by four-line parallel-bus architecture and can enlarge low resolution images to SXGA class images by using a new interpolation algorithm. The proposed LCD controller has been simulated and synthesized by using Synopsys VHDL.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1267-1271
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• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• Journal of Information Display
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• v.2 no.2
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• pp.13-21
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• 2001

We propose a universal image processor for a-Si TFT LCD of UXGA class that can display the full screen on the LCD panel with low resolution of video sources such as NTSC, VGA, SVGA, XGA, and SXGA by using the proposed interpolation filter. In addition, we propose a real-time contrast controller for image improvement of multi-gray scale image. The operation of the proposed methods has been verified using Synopsys VHDL and computer simulation. Results show that the proposed methods might be suitable for a UXGA LCD controller for real-time image improvement.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.123-126
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• 1995

Characteristics of control system design using Universal Learning Network (U.L.N.) are that a system to be controlled and a controller are both constructed by U.L.N. and that the controller is best tuned through learning. U.L.N has the same generalization ability as N.N.. So the controller constructed by U.L.N. is able to control the system in a favorable way under the condition different from the condition of the control system in learning stage. But stability can not be realized sufficiently. In this paper, we propose a robust control method using U.L.N. and second order derivatives of U.L.N.. The proposed method can realize better performance and robustness than the commonly used Neural Network. Robust control considered here is defined as follows. Even though initial values of node outputs change from those in learning, the control system is able to reduce its influence to other node outputs and can control the system in a preferable way as in the case of no variation. In order to realize such robust control, a new term concerning the variation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivatives of criterion function with respect to the parameters. Finally it is shown that the controller constricted by the proposed method works in an effective way through a simulation study of a nonlinear crane system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4145-4164
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• 2016

Energy harvesting is an increasingly attractive source of power for cellular networks, and can be a promising solution for green networks. In this paper, we consider a cellular network with power beacons powering multiple mobile terminals with microwave power transfer in energy beamforming. In this network, the power beacons are powered by grid and renewable energy jointly. We adopt a dual-level control architecture, in which controllers collect information for a core controller, and the core controller has a real-time global view of the network. By implementing the water filling optimized power allocation strategy, the core controller optimizes the energy allocation among mobile terminals within the same cluster. In the proposed green energy cooperation paradigm, power beacons dynamically share their renewable energy by locally injecting/drawing renewable energy into/from other power beacons via the core controller. Then, we propose a new water filling optimized green energy cooperation management strategy, which jointly exploits water filling optimized power allocation strategy and green energy cooperation in cellular networks. Finally, we validate our works by simulations and show that the proposed water filling optimized green energy cooperation management strategy can achieve about 10% gains of MT's average rate and about 20% reduction of on-grid energy consumption.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.95.4-95
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• 2001

In this paper, we proposed and analyze an robust adaptive control scheme for uncertain nonlinear systems using Universal function approximators. The proposed scheme completely overcomes the singularity problem which occurs in the indirect adaptive feedback linearizing control. No projection in the estimated parameters and no switching in the control input are needed. The stability of the closed-loop systems is guaranteed in the Lyapunov standpoint.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.33-43
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• 2011

Since the fuzzy neural network(FNN) is universal approximators, the development of FNN control systems have also grown rapidly to deal with non-linearities and uncertainties. However, the major drawback of the existing FNNs is that their processor is limited to static problems due to their feedforward network structure. This paper proposes the recurrent FNN(RFNN) for high performance and robust control of SynRM. RFNN is applied to speed controller for SynRM drive and model reference adaptive fuzzy controller(MFC) that combine adaptive fuzzy learning controller(AFLC) and fuzzy logic control(FLC), is applied to current controller. Also, this paper proposes speed estimation algorithm using artificial neural network(ANN). The proposed method is analyzed and compared to conventional PI and FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2188-2190
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• 2004

This paper presents an implementation of power system stabilizer using inverse dynamic neuro controller. Traditionally, mutilayer neural network is used for a universal approximator and applied to a system as a neuro-controller. In this case, at least two neural networks are used and continuous tuning of neuro-controller is required. Moreover, training of neural network is required considering all possible disturbances, which is impractical in real situation. In this paper, Taylor Model Based Inverse Dynamic Neuro Model (TMBIDNM) is introduced to avoid this problem. Inverse Dynamic Neuro Controller (IDNC) consists of TMBIDNM and Error Reduction Neuro Model (ERNM). Once the TMBIDNM is trained, it does not require retuning for cases with other types of disturbances. The controller is tested for one machine and infinite-bus power system for various operating conditions.