• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.129-136
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• 2002

This paper presents a $H_{\infty}$ robust controller with parameter estimation in polynomial approach. For good performance of a uncertain system, the parameters are estimated by RLS algorithm. The controller minimizes the sum of $H_{\infty}$ norm between sensitivity function and complementary sensitivity function by employing the Youla parameterization and polynomial approach at the same time. A numerical example and its simulation results are given to show the validity of the proposed controller.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.994-996
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) $H_{\infty}$ controller $(H_{\infty}C)$ is extended to the nonlinear feedback linearization-$H_\infty$-based sliding mode controller (NFL-$H_\infty$-based SMC). A stability proof of the closed-loop stability is done by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.529-536
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• 2000

A robust controller to attenuate the various disturbances of tandem cold mills (TCM) is synthesized by measurement-feedback $H_{\infty}$ control techniques which can reflect the input direction of disturbances and the knowledge of entry thickness variation (disturbance) is synthesized by discrete-time measurement-feedback $H_{\infty}$ control theory. It is demonstrated that the $H_{\infty}$ preview control gain can be easily obtained by the seperation principle of the control and estimation problems in $H_{\infty}$ control. Finally the effectiveness of the proposed control method for TCM is evaluated by the computer simulation and compared to the other control methods which have been previously studied.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.759-762
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• 1996

In previous work Kwon and Yoo [5] have shown that the FIR tracking algorithm using the input estimation technique. However, it has not solved the problem of systems with parameter uncertainties. Therefore, in this paper we propose a new robust $H_{\infty}$ FIR tracking filter to solve the target tracking problems under systems with parameter uncertainties. Also, we use here the input estimation approach to account for the possibility of maneuver. Simulation results show that the robust $H_{\infty}$ FIR tracking filter proposed here still has good tracking performance for a maneuvering target tracking problem even under all system parameter uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.3-33
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• 2001

This paper considers a fault detection and diagnosis using estimation method in uncertain systems. In the state estimation method, we use the robust H$\infty$ FIR filtering algorithm. A novel aspect of the fault detection technique described here is that it explicitly accounts for the effects of simplified models and errors due to the linearization of nonlinear systems at an operating point.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.129-132
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• 1999

This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.56-59
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• 1996

Worst-case state estimation will be proposed in this paper. By using the worst-case disturbance and worst-case state estimation, we can obtain right/left constrained coprime factors. If constrained coprime factors are used in designing a controller, the infinity-norm of closed-loop transfer matrix can be smaller than any constant .gamma.(> .gamma.$_{opt}$) without matrix dilation optimization. The derivation of left/right constrained coprime factors is achieved by doubly coprime factorization for the plant constrained by the infinity norm. And the parameterization of stabilizing controllers gives us easily understanding for H$_{\infty}$ control theory.ry.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.270-277
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• 1999

This paper deals with the maneuver detection and target tracking problem in uncertain parameter systems using a robust{{{{ { H}_{ } }}}} FIR filter to improve the unacceptable tracking performance due to the parametr uncertainty. The tracking filter used in the current paper is based on the robust{{{{ { H}_{ } }}}} FIR filter proposed by Kwon et al. [1,2] to estimate the state signal in uncertain systems with parameter uncertainty, and the basic scheme of the proposed method is the input estimation approach. Tracking performance of the maneuver detection and target tracking method proposed is compared with other techniques, Bogler allgorithm [4] and FIR tracking filter [2], via some simulations to examplify the good tracking performance of the proposed method over other techniques.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.436-439
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• 1998

In this paper, we propose a centralized $H^{\infty}$ state estimator for the multi state estimation problem using the result suboptimal $H^{\infty}$ filter is a special form of Ka filter whose state equations are defined in md inner product spaces. Con- ventional decentr filters are based on Kalman filter assumes precesses and measurements noises are w Gaussian noise. Therefore, Kalman based decent filter design hasn't robust performance in situation. Simulation results show that decent $H^{\infty}$ filter has robust perfotmance in worst case sensor fault situation.