• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.925-928
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• 1999

A multi-channel gas leakage monitoring system was designed and fabricated by using CPLD(complex Programmable Logic .Device) for monitoring and controlling the leakage of natural gas from supplying-pipes under the ground. Fabricated SnO$_2$thick film gas sensor elements were attached on safeguard steel plate of natural gas supplying pipes, and the local monitoring system in this study received the signal from the gas sensors. The monitoring system was implemented by using CPLD chip to reduce the development time and implement simple one chip system. The time division multi-channel system received the input signal from individual gas sensor at one of divided times by multiplexor and signal processed sequentially. The system reduced the size of peripheral circuit resulted in implementation of creditable simple system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.125-130
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• 2003

This Paper describes a Nonlinear adoptive noise canceller using Neural Network for Machine Tools Controller System. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this Paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental results show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary Input is divided by Unit and each divided pan is processed for very short time than all the processed data are unified to whole data.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.345-351
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• 2004

This Paper describes a nonlinear adaptive noise filter using neural network for digital controller system. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental reaults show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary input is divided by unit and each divided part is processed for very short time than all the processed data are unified to whole data.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1987-1992
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• 2004

A Variable Structure Model Reference Adaptive Controller (VS-MRAC) using state Variables is proposed for single input multi output systems. . The structure of the switching functions is designed based on stability requirements, and global exponential stability is proved. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time. The effect of input disturbances on stability and transients is investigated and shows preference to the conventional MRAC schemes with integral adaptation law. Sliding surfaces are independent of system parameters and therefore VS-MRAC is insensitive to system parameter variations. Simulation is presented to clear the theoretical results.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.809-812
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• 1999

The pendulum is a SIMO(Single-input multi-output) system that both angle of pendulum and position of cart controlled simultaneously by one actuator. In this paper, propose a hybrid neuro-controller to apply to pendulum system. We design the conventional optimal controller and the neural network as a identifier, which can identify the uncertainty of plant not modeled, respectively. Then we combine them into a novel controller, with a structure that the error between plant and identifier is added in conventional optimal control input Finally, the paper shows the validity of the proposed controller through computer simulations and experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.53-58
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• 2003

In recent years, the need for multi-stage gear drives, which highly reduce output speed, has been increased. However, the design of multi-stage gear drives have been carried out by a limited number of experts. The consideration for the direction of input and output axes also makes their design very difficult. The purpose of this study is to develop an algorithm for automatically generating complex multi-stage gear drives and to implement a design supporting system for multi-stage gear drives. There are 4 stages in the proposed algorithm, and major design parameters,.such as the direction of input and output axes, reduction ratio, etc. are set up in the first stage. In the second stage, all mechanisms are generated, and various rules are applied to select feasible mechanisms. In the third stage, the gear ratio of each stage is divided from total gear ratio. Next, the specifications of gears for feasible mechanisms are calculated and their bending strength and surface durability are estimated. In the forth stage, appraised indexes are calculated and provided to support the estimation of the generated gear drives.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.41-48
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• 2005

In recent years, the need for multi-stage gear drives which highly reduce output speed has been increased. However, the design of multi-stage gear drives has been carried out by a limited number of experts. The consideration for the direction of input and output axes also makes their design very difficult. The purpose of this study is to develop an algorithm for automatically generating complex multi-stage gear drives and to implement a design supporting system for multi-stage gear drives. There are 4 stages in the proposed algorithm, and major design parameters, such as the direction of input and output axes, reduction ratio, etc. are set up in the first stage. In the second stage, all mechanisms are generated, and various rules are applied to select feasible mechanisms. In the third stage, the gear ratio of each stage is divided from total gear ratio. Next, the specifications of gears for feasible mechanisms are calculated and their bending strength and surface durability are estimated. In the forth stage, appraised indexes are calculated and provided to support the estimation of the generated gear drives.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.419-427
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• 2018

This paper designs and develops auto-tuning temperature controller with multi-channel, which controller with multi-channel could control a number of control system simultaneously. This controller has multi-channel input and output. And a number of control algorithms run in this controller simultaneously and independently. Firstly we present design method of controller with multi-channel. Secondly we design electrical circuit of sensor input, controller output and power control for temperature control board. And finally we design data protocol for serial communication to monitor control state and present verification of temperature controller with muiti-channel through field experiment.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.892-901
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• 2016

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.409-416
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• 2009

This paper presents a tool called Quality-Cost optimization system (QCOS), which integrates Multi-Objective Genetic Algorithm (MOGA) and Quality Function Deployment (QFD), for tradeoff between quality and cost of the unitized metal curtain-wall unit. A construction owner as the external customer pursues to maximize the quality of the curtain-wall unit. However, the contractor as the internal customer pursues to minimize the cost involved in designing, manufacturing and installing the curtain-wall unit. It is crucial for project manager to find the tradeoff point which satisfies the conflicting interests pursued by the both parties. The system would be beneficial to establish a quality plan satisfying the both parties. Survey questionnaires were administered to the construction owner who has an experience of curtain-wall project, the architects who are the independent assessor, and the contractors who were involved in curtain-wall design and installation. The Customer Requirements (CRs) and their importance weights, the relationship between CRs and Technical Attributes (TAs) consisting of a curtain-wall unit, and the cost ratios of each components consisting curtain-wall unit are obtained from the three groups mentioned previously. The data obtained from the surveys were used as the QFD input to compute the Owner Satisfaction (OS) and Contractor Satisfaction (CS). MOGA is applied to optimize resource allocation under limited budget when multi-objectives, OS and CS, are pursued at the same time. The deterministic multi-objective optimization method using MOGA and QFD is extended to stochastic model to better deal with the uncertainties of QFD input and the variability of QFD output. A case study demonstrates the system and verifies the system conformance.