• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.10
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• pp.918-922
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• 2007

Most of the study on system identification has been carried out using input/output relation in physical domain. However identification concept of stochastic system has not been reported up to now. Interest is focused to identify an unknown dynamic system under random external disturbances which is not possible to measure. A concept to identify the system parameters in stochastic domain is proposed and implemented in terms of simulation. Attempt has been made to identify the system parameters in inverse manner in stochastic domain based on system output only. Simulation is conducted to reveal quite noticeable performance of the proposed concept.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.753-756
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• 1991

This paper aimed to analyse dose sensitivity to the controllable parameters of in-door radon $(^{222}Rn)$ and its decay products(Rn-D) by applying the input-output linear system theory. Physical behaviors of $^{222}Rn$ & Rn-D were analyzed in terms of $^{222}Rn$ gas generation, -migation and - infiltration to indoor environments, and the performance output-function(i.e. mean dose equivalent to Tracho-Bronchial(TB) lung region was assessed to the following ranges of the controllable parameters; a) the ventilation rate constant $({\lambda}_v)$ : $0{\sun}500[h^{-1}]$. b) the attachment rate constant$({\lambda}_a)$ : 0-500 $[h^{-1}]$. c) deposition rate constant $({\lambda}{_{d}^{u}})$: 0-50$[h^{-1}]$. A linear input-output model was reconstructed from the original models in literatures, as follows, which was modified into the matrices consisting of 111 nodal equations. a) indoor ${222}Rn$ & Rn-D Behaviour: jacobi- Porstendorfer- Bruno model. b) lung dosimerty : Jacobi-Eisfeld model. Some of the major findings, which identify the effectiveness of this model, were as follows. a) ${\lambda}_v$ is most effective, dominant controllable parameters in dose reduction, if mechanical ventilation is applied. b) ${\lambda}_v$, depending on the air particle-concentration, reduces the dose somewhat within ${\lambda}_v$<1 $h^{-1}R range. However, the dose increases conversely, ${\lambda}_v$>1 $h^{-1}R range range. c) ${\lambda}{_{d}^{4}}$ reduces the dose linearly as ${\lambda}_v$ dose. Such dose(z-axis) sentivities are shown with three-dimensional plots whoes x,y-axes are combined 2out the 3 parameter${\lambda}_v{\lambda}_s,\;{\lambda}_d^s$.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.3
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• pp.208-213
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• 2004

This paper is concerned with the theoretical estimation of the single-input single-output(SISO) positive position feedback(PPF) controller and the derivation of the stability conditions for the multi-input multi-output (MIMO) PPF controller. Although the stability condition for the SISO PPF controller was derived in the earlier works, the question regarding the performance estimation of the SISO PPF controller has never been studied theoretically. Hence, the SISO PPF controller for the single degree-of-freedom system was first investigated and then control parameters including gain, the filter frequency, and the damping factor of the PPF controller were analyzed in detail thus providing the design methodology for the SISO PPF controller. In the case of real structure. there are infinite number of natural modes so that some modes are to be controlled by a limited number of actuator and sensor. Based on the theoretical results on the SISO PPF controller, the stability condition for the multi-input multi-output PPF controller was derived when only the few number of modes are to be controlled. The control spillover problem is also discussed in detail.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.547-554
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• 2010

In this paper, we propose transmission systems for ultra high definition television (UHDTV) through terrestrial transmission by applying the multi-input multi-output (MIMO) technology. The space time block code, hybrid STBC, V-BLAST and linear dis- persion code are considered to support a high data rate of the UHDTV system. The performance of proposed MIMO systems are evaluated through computer simulations. Then we suggest MIMO parameters, number of antennas and optimal transmission scheme to achieve the transmission rate of the UHDTV system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.87.2-87
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• 2001

By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is an uncertain time-variant system. Control synthesis based on a reduced design model is a combined ...

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.333-335
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• 2005

In this paper, supposed to solve these problem to PID parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the speed of IM. In this process, EBPANN was constituted to an output error value of an IM and conspired an input and output. The performance of the self-tuning controller is compared with that of the PID controller tuned by conventional method (Ziehler-Nichols). The effectiveness of the proposed control method is verified thought the Matlab Simulink and experimental results.

• Journal of Welding and Joining
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• v.26 no.1
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• pp.63-68
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• 2008

This paper has aimed to prevent excessive heat input by controlling arc distribution and heat input capacity with pulse GTAW in order to improve weld quality in 0.08mm pressure gauge diaphragm and flange welding parts. A design of experiment was designed using Box-Behnken method to optimize a welding process. The pulse GTAW parameters such as pulse current, base current, pulse duty, frequency and welding speed were set to input variables while hydraulic pressure that represents welding characteristics in diaphragm and flange joint were set to output variables. Based on the test result, a second regression equation was obtained between input and output variables and turned out significant. Besides, an influence of parameters has been confirmed through response surface analysis using the second-order regression equation and optimum welding condition was obtained through a grid-search method. The optimum welding condition was set to pulse current 84.4(A), base current 29.6(A), pulse duty 58.8(%), frequency 10(%), and welding speed 596(mm/min). Then, decent bead shape was acquired with no excessive heat input under the $2.3kgf/cm^2$ of hydrostatic pressure.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• 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.