• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.619-625
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• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.47-48
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• 1985

This paper is concerned with the problem of designing satisfactory low-order controller starting with a high-order, state space model. The success of a design approach is rooted in the Choice of a model reduction procedure. The powerful new reduction method of a modal approach was already evaluated /1/. Application of the technique to a simulated steam generator is demonstrated for the case of modal control with low-order controllers.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.302-304
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• 1992

This paper presents the method to reduce the order of high-order linear time invarient system via Walsh function. It is based on the matrix pseudoinverse algorithm to determine the parameters of the reduced model which minimize the sum of the squares of the errors between the reponses of the high-order system and a reduced model to a given input. This proposed method can be conveniently implemented with a computer. They will be very useful in the study of control system via Walsh function.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.10
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• pp.396-401
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• 1984

This paper present a method of using simplified models for deriving suboptimal controllers to the original higher-order systems. Routh approximation method is a very useful technique for reducing the order of a linear systems. This method dose not require a knowlege of system eigenvalues and eigenvectors and possesses many desirable features such as preservation of reduced order model stability and minimum computational requirements. These properties are utilized to derive suboptimal controllers in this paper. In order to implement htese ocntrollers on the original system, the relationship between the state vectors of the original system and the reduced order models is required. A procedure fir evaluating an approximate aggregation matrix is also developed. A numerical example is given for the illustration of this method, shich is compared with the existing Model aggregation method in the resultant figures.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.366-369
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• 1994

In this paper, reduced-order $H_{\infty}$ robust controller is designed for the drum-type boiler system. From the known nonlinear dynamic model, a linearized multivariable model is obtained. To reduce order of robust controller, observer-based proper $H_{\infty}$ compensator is designed. The designed controller has robust property against the influence of sensor noise, system parameter variation and model uncertainty. A good Performance of the designed controller is shown by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.62.3-62
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• 2002

In this paper, we proposed a control technique that can be applied to various processes. The most of the process can bereduced to second order plus time delay (SOPTD) model. And we proposed improved model reduction algorithm using geneticalgorithm. This method considered four points to reduce the error between original model and reduced model in the Nyquistcurve. And, to compensate time delay, the Smith predictor plus PID controller is adopted. And a new PID tuning algorithm wasproposed, which got from numerical analysis and can be obtained the optimal performance. The PID parameters are obtainedfrom the coefficients and time delay of reduced model. The simulation results show the validity.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.688-698
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• 2012

This paper deals with ROLSO (Reduced Order Luenberger State Observer) design to prevent jackknifing phenomenon of articulated vehicles consisting of the tractor and semi-trailer by using GPS. In addition, by applying the regulator system using ROLSO feedback system, simulation's result presents that articulated vehicle's states are stabilized than the human's PR time (Preception Response time) rapidly. This simulation verifies that the automatic control of articulated vehicle's can be applied for the accident prevention for the time that the driver is unable to manage with the sudden accident. For this simulation, by using the equation of planar motion, the modeling of the articulated vehicle was performed. This modeling was expressed in the state space model. And FOLSO (Full Order Luenberger State Observer), ROLSO were designed by using the state space model of an articulated vehicle's dynamics.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.836-844
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• 2008

This paper presents an approach to order reduction of linear parameter varying controller for polytopic model. Feasible solutions which satisfy relevant linear matrix inequalities for constructing full-order parameter varying controller evaluated at each polytopic vertices are first found. Next, sufficient conditions are derived for the existence of a right coprime factorization of parameter varying controller. Furthermore, a singular perturbation approximation for time invariant systems is generalized to reduce full-order parameter varying controller via parameter varying right coprime factorization. This generalization is based on solutions of the parameter varying Lyapunov inequalities. The closed loop performance caused by using the reduced order controller is developed. To examine the performance of the reduced-order parameter varying controller, the proposed method is applied to reduce vibration of flexible structures having the transverse-torsional coupled vibration modes.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1219-1219
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• 1991

This paper proposes the model order reduction with pass band error reduction in the frequency domain of discrete time linear systems. The algorithm is the new method of reduced order model which reduces passband error by changing controllability and observability gramian used with weighted functions. A numerical example shows that this algorithm has lower passband error than balanced w&l and weighted function characteristics in frequency domain.