• 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.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.17-21
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• 2014

This paper presents the effects of the time delay on the stability of the haptic system that includes a virtual wall and a first-order-hold method. The model of a haptic system includes a haptic device model with a mass and a damper, a virtual wall model, a first-order-hold model and a time delay model. In this paper, the time delay is considered as the computational time delay that is assumed to be as much as the sampling time. As the time delay increases, the maximal available stiffness of a virtual wall model is reduced reversely. The relation among the time delay and the maximum available stiffness, the mass and the damper of the haptic device are analyzed using the MATLAB simulation.

• 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.

• 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.

• 전기의세계
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• v.24 no.5
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• pp.67-71
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• 1975

A dynamic stability analysis of a large interconnected power system takes much time even though the modern large computer is used because of the high order of the system dynamic equations. By the necessity of the low order power system models, a simplified power system model of the generator with the high speed solid state exciter is developed in this paper. The usefulness of the reduced model is confirmed by comparing its eigenvalues and the transient responses with those of the original model in the single machine to infinite bus power system.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.384-389
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• 2004

Recently a method of model reduction for discrete systems has been proposed in the literature based on a new impulse response Gramian. In this method, the system matrix$A_r$ of a reduced model is computed by approximating the reduced-order impulse response Gramian. The remaining matrices $b_r$ and $c_r$ are obtained so that various initial Markov parameters and time-moments of the original system are preserved in the reduced model. In this paper a different approach is presented based on the recursive relationship among the impulse response Gramians.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.293-304
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• 2007

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

• Smart Structures and Systems
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• v.18 no.1
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• pp.1-16
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• 2016

Model Order Reduction (MOR) denotes the theory by which one tries to catch a model of order lower than that of the real model. This is conveniently pursued in view of the design of an efficient structural control scheme, just passive within this paper. When the nonlinear response of the reference structural system affects the nature of the reduced model, making it dependent on the visited subset of the input-output space, standard MOR techniques do not apply. The mathematical theory offers some specific alternatives, which however involve a degree of sophistication unjustified in the presence of a few localized nonlinearities. This paper suggests applying standard MOR to the linear parts of the structural system, the interface remaining the original unreduced nonlinear components. A case study focused on the effects of a helicopter land crash is used to exemplify the proposal.