• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1126-1130
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• 2010

Speech production can be viewed as a filtering operation in which a sound source excites a vocal tract filter. The vocal tract is modeled as a chain of cylinders of varying cross-sectional area in linear prediction acoustic tube modeling. In this modeling the most common implementation assumes equal length of tube sections. Therefore, to model complex vocal tract shapes, a large number of tube sections are needed. This paper proposes a new vocal tract model with unfixed sectionlengths, which uses the reduced lattice filter for modeling the vocal tract. This model transforms the lattice filter to reduced structure and the Burg algorithm to modified version. When the conventional and the proposed models are implemented with the same order of linear prediction analysis, the proposed model can produce more accurate results than the conventional one. To implement a system within similar accuracy level, it may be possible to reduce the stages of the lattice filter structure. The proposed model produces the more similar vocal tract shape than the conventional one.

• Design & Manufacturing
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• v.17 no.3
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• pp.1-7
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• 2023

Blow molding is a manufacturing process in which thermoplastic preforms are preheated and then pneumatically expanded within a mold to produce hollow products of various shapes. The two-step process, a type of blow molding method, requires the output of multiple infrared lamps to be adjusted individually, so the process of finding initial conditions hinders productivity. In this study, digital twin technology was applied to solve this problem. A blow molding simulation technique was established and simulation-based metadata was generated. A response surface ROM (Reduced Order Model) was built using the generated metadata. Then, a dynamic ROM was constructed using the results of 3D heat transfer analysis. Through this, users can quickly check the product wall thickness uniformity according to changes in the control value of the heating lamp for products of various shapes, and at the same time, check the temperature distribution of the preform in real time.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.12-20
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• 2002

To control the noise of an enclosed sound field, we built a state space model using the acoustic modal parameter description. Using the state space model, we can investigate the controllability and observability, and find an appropriate position of control speaker and microphone to control sound field of the enclosed space. We implemented LQR(linear quadratic regulator) controller and reduced order observer to reduce the first acoustic mode. Experiments showed satisfactory results of 4∼10 dB reduction of magnitude of the first acoustic mode, and support the feasibility of the proposed scheme to lightly damped acoustic field.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1844-1854
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• 2003

This paper discusses details of modeling and robust control of an AMB (active magnetic bearing) spindle, and part I presents a modeling and validation process of the AMB spindle. There are many components in AMB spindle : electromagnetic actuator, sensor, rotor, power amplifier and digital controller. If each component is carefully modeled and evaluated, the components have tight structured uncertainty bounds and achievable performance of the system increases. However, since some unknown dynamics may exist and the augmented plant could show some discrepancy with the real plant, the validation of the augmented plant is needed through measuring overall frequency responses of the actual plant. In addition, it is necessary to combine several components and identify them with a reduced order model. First, all components of the AMB spindle are carefully modeled and identified based on experimental data, which also render valuable information in quantifying structured uncertainties. Since sensors, power amplifiers and discretization dynamics can be considered as time delay components, such dynamics are combined and identified with a reduced order. Then, frequency responses of the open-loop plant are measured through closed-loop experiments to validate the augmented plant. The whole modeling process gives an accurate nominal model of a low order for the robust control design.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.448-449
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• 2010

This paper proposes a sensorless control strategy for the Interior Permanent Magnet Synchronous Motor (IPMSM) by using the parallel reduced-order Extended Kalman Filter. The sensorless control strategy is composed with two EKFs alternately computed every sampling period with a new model. The new model is based on the extended electromotive force (EEMF) which has a simple structure, making position estimation possible without approximation. The proposed strategy can save computation time and estimate rotor speed and position. To verify the merit of the proposed strategy, simulation and experimental results validate the theoretical analysis and show the feasibility of the proposed control strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.556-558
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• 1990

A method of model reduction for reducing a higher order Z-transfer function to its lower order model is developed based on the Block - pulse function. The approach is following : I. Block - pulse function can be applied for Z-transfer function of linear digital system described by high order. II. To determined both the coefficients of the denominator and numerator of reduced model. The proposed method is simple for computation, can preserve the dynamic characteristic of the original model satisfactorily.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.31 no.8
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• pp.33-38
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• 1982

This paper deals with the simplification of the transfer function in a frequency domain, viz. the integral of the squared errors between the original and the simplified model is minimized and the latter is estimated by the Walsh function. It tries to minimize the errors between the frequency responses of the two functions. This method is compared with the existing method by means of a numercal example. The frequency response of this simplified model approximates closely to that of the original model. The proposed method is simpler in analysis and easier in implementation than the existing methods. Though the Walsh function can be easily generated with the discrete values, it has errors because its zero crossings are not continuous. This method aims at the reduction of the errors in the real parts and the imaginary parts of the two functions by dividing into the more sub-intervals, and selecting the reduced-order model according to the response of the model. As a result, it can be applied for the simplification of higher order functions into lower order functions and for the design of control systems.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.9-15
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• 2003

To improve the performance of PID controller of high order systems by model reduction, we proposed two model reduction methods. One, Original model with two point $({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$ in Nyquist curve used gradient base method and genetic algorithm. The other, Original model without two point$({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$in Nyquist curve used to add very small dead time. This method has annexed very small dead time on the base model for reduction, and we remove it after getting the reduced model, and , we improved Smith-predictor for a dead-time compensator using genetic algorithms. This method considered four points$({\angle}G(jw)=0,\;-\pi/2,\;-\pi,\;-3\pi/2)$ in the Nyquist curve to reduce steady state error between original and reduced model. It is shown that the proposed methods have more performance than the conventional method.

• Management Science and Financial Engineering
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• v.4 no.2
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• pp.15-42
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• 1998

A joint problem of order delivery, setup reduction, and cost-sharing in a two-echelon inventory system in which a vendor supplies multiple products to a group of buyers is studied here. The basic premise is that buyers have independently implemented setup reduction programs to acquire benefits from small order sizes. Doing so, however, causes the buyers' individually optimal order cycles to be differ from that of the vendor. In conjunction with this, two models are considered. In the first model, a multi-buyers single product situation is considered in which the vendor implements a joint supply cycle policy. However, buyers, as the dominant party, insist after implementing the individually optimal setup reduction that the vendor accept their individually optimal order schedules. In the second model. a multi-products, single buyer situation is considered in which the buyer implements a joint order policy. Here, the vendor, as the dominant party, refuses to cooperate fully with the buyer's individually reduced joint order schedule, and designs his own individually optimal setup reduction mix for each product under a given budget constraint. This led to a study of an integrated Setup Reduction/Break-even Pricing Policy for each situation to eliminate mismatches in individually optimal cycle times.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.340-343
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• 1995

In this paper, we get a reduced order controller in $H^{\infty}$ mixed sensitivity problem with weighting functions. For this purpose, we define frequency weighted coprime factor of plant in $H^{\infty}$ mixed sensitivity problem and reduce the coprime factor using the frequency weighted balanced truncation technique. The we design the controller for plant with reduced order coprime factor using J-lossless coprime factorization technique. Using this approach, we can derive the robust stability condition and achieve good performance preservation in the closed loop system with reduced order controller. And it behaves well in both stable plant and unstable plant.t.