• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1464-1468
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• 1997

We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.735-746
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• 1999

We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.750-753
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• 1998

This paper gives a simple parameterization of all stable unbiased filters to solve the suboptimal mixed $H_2/H_{\infty}$ filtering problem. Using the central filter, mixed $H_2/H_{\infty}$ filter is designed which minimizes the upper bound for the $H_2$ norm of the transfer matrix from a white noise to the estimation error subject to an $H_{\infty}$ norm constraint on the transfer matrix from an energy-bounded noise to the estimation error. The problem of finding suitable estimator gain can be converted into a convex optimization problem involving linear matrix inequalities.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.146-148
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• 1997

An LMI-based parameterization of all $\gamma$-suboptimal reduced-order unbiased $H_{\infty}$ filters is provided in terms of a free matrix, using the unbiasedness condition, bounded real lemma and the general solution of the basic LMI. Also, by sequentially solving the generalized eigenvalue minimization and basic LMI problem, the optimal filter coefficient matrix can be obtained with the best achievable performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2311-2313
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• 2000

In this paper, we consider $H^{\infty}$ optimal Kalman filter problems for linear weakly coupled stochastic systems. We introduce a decomposition for the systems of the Hamiltonian form, which plays an important role of exclusion of ill-condition by ${\varepsilon}$-effect and the parallel computation possibility. It is shown that the algebraic Riccati equation of the weakly coupled $H^{\infty}$ optimal Kalman filter problem is decoupled into completely independent reduced-order, well-defined, two suboptimal Kalman filters.

• 전자공학회논문지S
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• 제36S권2호
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• pp.38-45
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• 1999

본 논문에서는, $H_{\infty}-LTR$ 설계의 새로운 접근방법을 제시한다. 제시된 방법은 제어입력의 크기 및 회복오차의 적절한 가중을 조절할 수 있는 설계도구를 제공한다. 1단계에서, 요구되는 성능사양에 만족하도록 루프를 정형하기 위하여 Kalman 필터를 설계하고, 설계된 Kalman 필터는 플랜트의 전달함수와 함께 목표전달함수(target transfor function)로 사용된다. 2단계에서는 목표전달함수로 회복을 위하여 감도함수를 가중함수로 상요한 준 최적 $H_{\infty}_LTR$을 설계한다. 시뮬레이션을 통하여 LQG/LTR, $H_{\infty}-LTR$ 방법의 경과를 비교함으로써 제시된 $H_{\}-LTR$의 우수성을 보인다.