• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.883-890
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• 2004

In this paper, new structures of embedded internet remote control systems, which can control electo-mechanical systems, are developed. For this, remote interface system structure using embedded system are developed first, then the way of internet remote control and the PC program for the control are discussed. The developed syste in this paper can be applied to home automations such as to control entrance doors, lights, consumer electronics and other industrial applications. To show the example illustrations, in this paper, the deyeloped system has been applied to multiple motor control systems. The results show that the developed system can directly be applicable into the real industrial field.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.291-296
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• 2001

The computerized automation of modern manufacturing system is tremendously important for the cost reduction. Recently, the automation is being realized by Computer Integrated Manufacturing (CIM) concept and the unmanned factory is the final goal of the automation. The automation of the low level of factory is the most crucial and difficult aspect in total CIM environment since various machines are involved. A cell is defined as a manufacturing group of closely related machineries in the entire factory hierarchy, The management scheme for a cell controller is defined from the software viewpoint. The domain of a cell is designed with tasks(processes) in a multiple-task operating system. The operation of the cell is established by defining schemes for overall control of the cell domain, databases, job scheduling, communications within the domain, user-interface and communications with outside machines. Although the software is developed in a specific operating system and WINDOW facilities, the operating strategies can be applied globally.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.04a
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• pp.47-56
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• 2000

In this study, as the preliminary step for developing an unmanned vehicle to deliver a container-box, we designed and implemented Automatic Guided Vehicle(AGV) Simulator for the purpose of Port Facilities Automation. It is preferable to research the intelligent AGV for delivery all day long. For complementing AGV simulator driving, we used multiple-sensor systems with vision, ultrasonic, IR and adapted the high-speed wireless LAN that satisfies the IEEE 802.11 Standard for bi-directional communication between main processor in AGV and Host computer. Here, we mounted on bottom frame in AGV Pentium-III processor, which combine and compute the information from each sensor system and control the AGV driving, and used the 80C196KC micro-controller to control the actuating and steering motors.

• Journal of Biomedical Engineering Research
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• v.12 no.1
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• pp.9-18
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• 1991

A micro- computer system has been designed to evaluate the performance of commercial infant incubator and to develope the temperature controller of new incubator. The measure- ment system used a hybrid of analog electronics for amplification, integration, and switches and micro-computer for data storage, data display, and control of relay. This approach has been applied to measure the warm-up time, temperature stability, open/close door and port- holes, and temperature distribution on the mattress. The micro-computer provides on-line ac cess of multi-point temperature data, simplifies the analog part of the circuit and gives the flexibility.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.160-166
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• 2002

Since conventional mobile robot control with one module has limitation to solve complex problems, there have been a variety of works on combining multiple modules for solving them. Recently, many researchers attempt to develop mobile robot controllers using artificial life techniques. In this paper, we develop a mobile robot controller using cellular automata based neural networks, where complex tasks are divided to simple sub-tasks and optimal neural structure of each sub-task is explored by genetic algorithm. Neural network modules are combined dynamically using the action selection mechanism, where basic behavior modules compete each other by inhibition and cooperation. Khepera mobile robot simulator is used to verify the proposed model. Experimental results show that complex behaviors emerge from the combination of low-level behavior modules.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2843-2845
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• 2005

This paper deals with the design of real-time embedded system using RTOS (real-time operating system) and SOPC (system on a programmable chip). It is, in general, known that RTOS has the problem of time delay caused by the multiple tasks and task management approach. Since the increase in time delay in real-time embedded system makes the overall system have the poor performance or the critical behavior of instability and unreliability, the method employed RTOS and SOPC is proposed to attack the above problems. The proposed system is implemented on the RC-motor controller and is verified by real experiment.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.78-80
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• 2005

The pattern recognition of automobile and parking line for the automatic car parking system was processed based on statistical method for reducing the processing time. The command of driving for parking at the vacant parking lot was transmitted from processor to motor driven actuator using direct sequence spread spectrum communication, which enables the multiple transmission in CAN(controller area network). The test-bed which has CCD camera, processor, radio transceiver and FPGA was implemented and demonstrated to be operated well.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.660-665
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• 1993

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD ( an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very fast training and processing implementation required for real time control.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.189-196
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• 2015

In this paper, we present a rotating auto-zeroing offset cancellation technique, which can improve the performance of touch screen sensing circuits. Our target touch screen detection method employs multiple continuous sine waves to achieve a high speed for large touch screens. While conventional auto-zeroing schemes cannot handle such continuous signals properly, the proposed scheme does not suffer from switching noise and provides effective offset cancellation for continuous signals. Experimental results show that the proposed technique improves the signal-to-noise ratio by 14 dB compared to a conventional offset cancellation scheme. For the realistic simulation results, we used Cadence SPECTRE with an accurate TSP model and noise source. We also applied an asymmetric device size (10% MOS size mismatch) to the OP Amp design in order to measure the effectiveness of offset cancellation. We implemented the proposed circuit as part of a touch screen controller system-on-chip by using a Magnachip/SK Hynix 0.18-µm complementary metal-oxide semiconductor (CMOS) process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2050-2058
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• 2001

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of 7he convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.