• 대한임베디드공학회논문지
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• 제12권5호
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• pp.311-318
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• 2017

A reduced order observer is developed for depth control of a hybrid underwater glider which combines the good aspects of a conventional autonomous underwater vehicle and a underwater glider. State variables include the center of gravity of the robot and the weight of the buoyancy bag, which can not be directly measured. By using the mathematical model and available information such as directional velocities, accelerations, and attitudes, we developed a Luenberger's reduced order observer to estimate the center of gravity and the buoyancy weight. By simulations using Matlab/Simulink, the efficiency of the proposed observer is shown, where a LQR controller using full state variables is adopted as a depth controller.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.683-688
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• 2017

The unscented Kalman filter features a direct transforming process involving unscented transformation for removing the linearization process error that may occur in the extended Kalman filter. This paper proposes a reduced-order unscented Kalman filter for the sensorless control of a permanent magnet synchronous motor. The proposed method can reduce the computational load without degrading the accuracy compared to the conventional Kalman filters. Moreover, the proposed method can directly estimate the electrical rotor position and speed without a back-electromotive force. The proposed Kalman filter for the sensorless control of a permanent magnet synchronous motor is verified through the simulation and experimentation. The performance of the proposed method is evaluated over a wide range of operations, such as forward and reverse rotations in low and high speeds including the detuning parameters.

• Journal of Mechanical Science and Technology
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• 제16권12호
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• pp.1561-1575
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• 2002

A reduced-order linear feedback controller, which is used to control the linear disturbance in two-dimensional plane Poiseuille flow, is applied to a boundary layer flow for stability control. Using model reduction and linear-quadratic-Gaussian/loop-transfer-recovery control synthesis, a distributed controller is designed from the linearized two-dimensional Navier-Stokes equations. This reduced-order controller, requiring only the wall-shear information, is shown to effectively suppress the linear disturbance in boundary layer flow under the uncertainty of Reynolds number. The controller also suppresses the nonlinear disturbance in the boundary layer flow, which would lead to unstable flow regime without control. The flow is relaminarized in the long run. Other effects of the controller on the flow are also discussed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.339-344
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• 2011

In the past much effort has been made to utilize advanced computational fluid dynamic (CFD) programs for aeroelastic simulations and analysis. However, it is limited in the field of unsteady aeroelasticity due to enormous size of computer memory and unreasonably long CPU time. Recently, AAEMS(Aerodynamics is Aeroelasticity minus Structure) was developed for linear time-invariant, coupled fluid-structure systems. In this paper, to demonstrate further the efficiency and accuracy of the new model reduction method, we successfully examine AGARD 445.6 wing modeled by FLUENT CFD, FSIPRO3D and NASTRAN FEM(Finite Element Method) programs. Using the ROM(Reduced Order Modeling) one can predict flutter boundary as a function of the dynamic pressure.

• 한국전산구조공학회논문집
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• 제31권5호
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• pp.275-282
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• 2018

등기하 해석법을 이용한 고유치 해석은 유한요소를 이용한 결과보다 고차 모드에서 더 정확한 결과를 주는 것으로 알려져 있다. 이는 유한요소법이 차수에 상관없이 요소 간에 $C^0$ 연속성을 보이는 것과 다르게 등기하 해석법은 p차 요소에 대해서 $C^{p-1}$의 연속성을 보장하기 때문이다. 본 논문에서는 이러한 장점을 이용하여 등기하 해석법을 이용하여 모드 기반의 축소 모델을 구성하고 동적 거동 해석을 수행하였다. 축소 모델 구성을 위해 Craig-Bampton(CB) 기법을 적용하였다. 수치 예제를 통해 간단한 봉 요소에 대해 등기하 해석법과 유한요소 해석법을 적용하여 요소의 차수에 따른 고유치 해석 결과를 비교분석하였다. 등기하 해석법에 중첩 노트를 허용하여 요소 간 연속성을 조절하고, 요소 간 연속성이 줄어듦에 따라 고차 모드에서의 수치 오차가 커짐을 확인하였다. 동적 거동 해석을 위한 축소 모델에 높은 차수의 외력이 주어지는 경우 요소간 연속성이 높은 등기하해석법을 사용하면, 해의 정확도를 높일 수 있다.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.142-148
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• 2008

In this paper, we deal with the problem of reducing the order of the detection filter for the linear time-invariant system. Even if the detection filter is generally designed in the form of full order linear observer, we show that it is possible to reduce its order when the response of fault signals is limited to a subspace of the estimation state space. We propose a method to extract the subspace using the observer canonical form considering the dynamics related to the remaining subspace acts as a disturbance. We designed a reduced order detection filter to reject the disturbance as well as to guarantee fault detection and isolation. A simulation result for a 5th order system is presented as an illustrative example of the proposed design method.

• Smart Structures and Systems
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• 제13권3호
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• pp.343-352
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• 2014

Given a body undergoing a stress-strain status as consequence of external excitations, sensors can be deployed on the accessible lateral surface of the body. The sensor readings are regarded as input of a numerical model of reduced order (i.e., the number of sensors is lower than the number of the state variables the full model would require). The goal is to locate the sensors in such a way to minimize the deviations from the response of the true (full) model. One adopts either accelerometers as sensors or devices reading relative displacements. Two applications are studied: a plane frame is first investigated; the focus is eventually on a 3D body.

• 대한기계학회논문집A
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• 제30권3호
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• pp.310-317
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• 2006

Currently most practical vibration and structural problems in automotive suspensions require the use of the finite element method to obtain their structural responses. When the finite element model has a very large number of degrees of freedom the harmonic and dynamic analyses are computationally too expensive to repeat within a feasible design process time. To alleviate the computational difficulty, this paper presents a moment-matching based model order reduction (MOR) which reduces the number of degrees of freedom of the original finite element model and speeds up the necessary simulations with the reduced-size models. The moment-matching model reduction via the Arnoldi process is performed directly to ANSYS finite element models by software mor4ansys. Among automotive suspension components, a knuckle is taken as an example to demonstrate the advantages of this approach for vibration simulation. The frequency and transient dynamic responses by the MOR are compared with those by the mode superposition method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.119-121
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• 2003

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator gives an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multimachine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimization of controller parameters to improve system stability. This paper compare the first order eigenvalue sensitivity coefficients of controllers in case of generator full model with those of two-axis model. As a result of an example the estimated eigenvalues using sensitivity coefficients in case of generator full model is very close to those of state matrix within 1% error ratios.