• Journal of Power Electronics
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• v.10 no.2
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• pp.115-124
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• 2010

In this paper, a simple yet efficient auto mode-hop ripple control structure for buck converters with light load operation enhancement is proposed. The converter, which operates under a wide range of input and output voltages, makes use of a state-dependent hysteretic comparator. Depending on the output current, the converter automatically changes the operating mode. This improves the efficiency and reduces the output voltage ripple for a wide range of output currents for given input and output voltages. The sensitivity of the output voltage to the circuit elements is less than 14%, which is seven times lower than that for conventional converters. To assess the efficiency of the proposed converter, it is designed and implemented with commercially available components. The converter provides an output voltage in the range of 0.9V to 31V for load currents of up to 3A when the input voltage is in the range of 5V to 32V. Analytical design expressions which model the operation of the converter are also presented. This circuit can be implemented easily in a single chip with an external inductor and capacitor for both fixed and variable output voltage applications.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1435-1437
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• 2003

In this paper, we proposed static output feedback model predictive control for Wiener models. We adopted polytopic uncertainty description of Wiener Model Predictive Control (WMPC) algorithms for considering output nonlinearities. Robust stability conditions have been presented under which the closed loop stability of static output feedback MPC is guaranteed. The proposed control law is determined from the static output feedback WMPC based on the current estimated state with explicit satisfaction of input constraints.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.399-407
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• 1996

A fuzzy learning algorithm to get the optimal fuzzy rules is presented in this paper. The algorithm introduces a reference model to generate a desired output and a performance index funtion instead of the performance index table. The performance index funtion is a cost function based on the error and error-rate between the reference and plant output. The cost function is minimized by a gradient method and the control input is also updated. In this case, the control rules which generate the desired response can be obtained by changing the portion of the error-rate in the cost funtion. In SISO(Single-Input Single- Output)plant, only by the learning delay, it is possible to experss the plant model and to get the desired control rules. In the long run, this algorithm gives us the good control rules with a minimal amount of prior informaiton about the environment.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.299-305
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• 2013

The complexity and severe nonlinearity of multi-machine power systems make it difficult to design a control input for voltage regulation using modern control theory. This paper presents a model-based PID control scheme for the regulation of the bus voltage to a desired value. To this end, a fourth-order linear system is constructed using input and output data obtained using the TSAT (Transient Security Assessment Tool); the input is assumed to be applied to the grid through the STATCOM (STATic synchronous COMpensator) and the output from the grid is a bus voltage. On the basis of the model, it is identified as to which open-loop poles of the system make the response to a step input oscillatory. To reduce this oscillatory response effectively, a model-based PID control is designed in such a way that the oscillatory poles are no longer problematic in the closed loop. Simulation results show that the proposed PID control dampens the response effectively.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.111-117
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• 2003

The Taylor model concept is introduced to design a controller with input and output data only. The parameters in Taylor model can be estimated using the input and output data and a controller can be designed based on Taylor model. The accuracy of Taylor model approximation can be improved by increasing the observation window and the order of Taylor model. The LQR method is applied to Taylor model to design power system stabilizers (PSS), and compared with the conventional PSS.

• Journal of Korean Society for Atmospheric Environment
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• v.5 no.1
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• pp.1-10
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• 1989

The sensitivity analysis is a method to quantify to what extent the output of a model changes with the values of input parameters. This will lead to increase model accuracy through measurement validation. Three line source air quality models, HIWAY 2, PAL, and CALINE 3 were selected for this study. The input parameters analysed included wind speed, wind direction, stability, emission rate, mixing height, receptor distance, initial dispersion coefficient, surface roughness, and averaging time. It turned out that PAL model generally showed higher concentration than other two models, and that between CALINE 3 and HIWAY 2, CALINE 3 showed higher concentration than HIWAY 2 model near the line sources, but beyond a certain downwind distances HIWAY 2 model showed higher concentration. The modesl were very sensitive to wind speed especially in the range of 0 $\sim$ 1 m/s and to wind direction near the parallel wind to streets. In case of emission rate, the output concentration was directly proportional to these input parameters. And the sensitivity of the input parameters such as stability, mixing height, initial dispersion coefficient, surface roughness, and averaging time were not very significant.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.41-49
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• 2010

In this paper, we propose a hierarchical RAM simulation model framework which are used to analyze the RAM specifications on the concept refinement phase. The hierarchical RAM simulation model framework consists of RAM simulation models, class library and each model's input and output data lists. The hierarchical RAM simulation models are co-operated with 3 kinds of model - type I, II, III. Type I, II models are used to analyze the target operational availability and Type III is used to establish the initial RAM specifications. Each model's input and output data lists are defined by considering each model's purpose of RAM analysis. The class library is arranged with each model's classes for implementing the hierarchical simulation models. The proposed framework may be applied for executing the RAM activities effectively.

• Water Engineering Research
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• v.4 no.1
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• pp.1-17
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• 2003

A mathematical model was developed to simulate the performance of a prototype wind-powered reverse osmosis desalination system. The model consists of two sub-models operated in a series. The first sub-model is the wind-energy conversion sub-model, which has wind energy and feed water as its input and pressurized feed water as its output. The second sub-model is a reverse osmosis (RO) process sub-model, with pressurized feed water as its input and the flow and salinity of the product water or permeate as its output. Model coefficients were determined based on field experiments of a prototype wind powered RO desalination system of the University of Hawaii, from June to December 2001. The mathematical model developed by this study predicts the performance of wind-powered RO desalination systems under different design conditions. The system optimization is achieved using a linear programming approach. Based on the results of system optimization, a design guide is prepared, which can be used by both manufacturer and end-user of the wind-driven reverse osmosis system.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.11-21
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• 1997

The delay models for CMOS invertr presented so far predicted the delay time quite accurately whens input transition-time is very small. But the problem that the accuracy is inclined to decrease becomes apparent as input transition tiem increases. In this paper, a delay model for CMOS inverter is presented, which accuractely predicts the delay time even though input transition-time increases. To inverter must be included in modeling process because the main reason of inaccuracy as input transition tiem is the leakage current through the complementary MOS. For efficient modeling, this paper first models the MOSes with simple I-V charcteristic, with which both the pMOS and the nMOS are considered easily in calculating the inverter delay times. This resulting model needs few parameters and re-models each MOS effectively and simply evaluates output voltage to predict delay time, delay values obtained from this effectively and simply evaluates output voltage to predict delay time, delay values obtained from this model have been found to be within about 5% error rate of the SPICE results. The calculation time to predict the delay time with the model from this paper has the speed of more than 70times as fast as to the SPICE.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.625-630
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• 1986

In this paper, an adaptive observer based upon the exponentially weighted least-square method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. The adaptive observer estimates the padrameter vectors and initial state vector. The control input is determined so that the output of the plant converges to the output of the stable model reference.