• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1592-1594
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• 2009

This paper presents an LMI-based method to design a reduced order output feedback sliding mode controller for a class of uncertain systems. Using LMIs we derive an existence condition of a reduced order sliding mode control law. And we give explicit formulas of the gain matrices. Finally, we give a numerical design example, together with a design algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1057-1060
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• 2006

This paper presents an LMI-based method to design a reduced order observer based sliding mode controller for a class of uncertain systems. Using LMIs we derive an existence condition of a reduced order observer and a sliding mode control law. And we give explicit formulas of the gain matrices. Finally, we give a numerical design example, together with a design algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4411-4417
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• 2012

The present study proposes the optimization of wing structure base on reduced model which assures the solution accuracy and computational efficiency. Well-constructed reduced model assures the accurate result in the eigenvalue problem, dynamic analysis or sensitivity of design optimization. Reduced system is classified into the reduce-order model based on structural modes and the reduced system based on degrees of freedom. Because this study uses the reduced system based on degrees of freedom, it is important to select the dominant degrees of freedom properly. For this work, robust selection method, two-level selection scheme, is employed and IRS(Improved Reduced System) is applied to construct the final reduced system. In the optimization process based on the reduced system, all of the equivalent stress, eigenvalue and design sensitivities are calculated from the reduced system. Through a numerical example, it is shown that the present optimization methodology based on the reduction method can provide an optimal results for objective function satisfying constraint condition.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1766-1769
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• 1997

Fast and accurate distillation design requires a model that significantly reduces the problem size withour loss of accruacy is especially suitable for rela-time applicatoins. the reduced order model is obtained by use of Principal Component Anlysis(PCA). Then the extended Kalman filter and the Recursie Predictiuon Error(RPE) mehtod are appliced to identify the model parameters and the feed compostion form the measuremenets of the coumn. as a consequence it is found that the model reduction thechique can account for the dynamics of the rigorous distillation model and not only the model parameters, bu also the feed compostion can be identified efficiently. this technique is applied to industrial operation data verify the performance of reduced order model.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.155-160
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• 2007

A fault detection and isolation (FDI) problem is considered for inertial sensors, such as gyroscopes and accelerometers and a new FDI method for double faults is proposed using reduced-order parity vector. The reduced-order parity vector (RPV) algorithm enables us to isolate double faults with 7 sensors. Averaged parity vector is used to reduce false alarm and wrong isolation, and to improve correct isolation. The RPV algorithm is analyzed by Monte-Carlo simulation and the performance is given through fault detection probability, correct isolation probability, and wrong isolation probability.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.466-470
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• 1988

A tunable reduced-order distillation model is proposed for real-time applications. To develop the model, a binary distillation column with MaCabe-Thiele assumptions was considered first and then the governing equations for the column were reduced to a simplified vector differential equations using the collocation method combined with cubic spline interpolation function. The final reduced-order model has four tuning parameters, relative volatilities and liquid holdups for rectifying and stripping sections, respectively. To assess the applicability of the developed model,the real-time adjustment of the model was tried by recursively updating the tuning parameters using the BKF algorithm. As a result, it was found that the reduced-model follows the simulated distillation process very closely as the parameters are improved.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.70-72
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• 1985

• 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.

• Current Optics and Photonics
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• v.7 no.6
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• pp.692-700
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• 2023

We present a method for improving the accuracy of the modal wavefront reconstruction in the radial shearing interferometers (RSIs). Our approach involves expanding the reduced radial terms of Zernike polynomials to high-order, which enables more precise reconstruction of the wavefront aberrations with high-spatial frequency. We expanded the reduced polynomials up to infinite order with symbolic variables of the radius, shearing amount, and transformation matrix elements. For the simulation of the modal wavefront reconstruction, we generated a target wavefront subsequently, magnified and measured wavefronts were generated. To validate the effectiveness of the high-order Zernike polynomials, we applied both low- and high-order polynomials to the wavefront reconstruction process. Consequently, the peak-to-valley (PV) and RMS errors notably decreased with values of 0.011λ and 0.001λ, respectively, as the order of the radial Zernike polynomial increased.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.59-65
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• 2011

In this paper, we present a reduced-order parameter-dependent robust $H_{\infty}$ filter design method for discrete-time singular systems with polytopic uncertainties. A BRL(bounded real lemma) for parameter-dependent singular systems is derived from a parameter-dependent Lyapunov function. On the basis of the obtained BRL, low order robust $H_{\infty}$ filter design method is presented by polytopic approach, new reduced-order method, and LMI(linear matrix inequality) technique. Finally, a numerical example is presented to illustrated the feasibility of the proposed method.