• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.142-146
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• 1991

In order to develope transfer alignment algorithm which achieves accurate initial alignment of slave strapdown inertial navigation system(SDINS) of a missle using master SDINS of mobile launchers third-order suboptimal filter is constructed to estimate the transformation matrix between two SDINS coordinates. In Kalman Filter formulation, the measurement equation uses that of accelerometer when stationary, and is replaced by that of gyroscope when elevating the missle. This switching method is applied to increase the degree of observability and to remove the error generated by lever arm effect. Simulation results show that the azimuth transfer error is about 0.3 mrad, and confirm that this scheme has a potential for real application.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.510-520
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• 1988

In this paper, the output error variance due to the differential vcariation of the state-space coefficient [ABCD], which is the coefficient quentization error, is normalized on the variance for cases that infinite wordlength state-space digital filter is realized by the finite one. That is, defining S as the statistical sensitivity and extending controllability gramian, observability gramian, and 2nd order mode analysis method to the state space digital filter, we synthesize the realization structure with the minimum statistical sensitivity and prove the effecency of the minimum statistical sensitivity structure synthesis by the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.488-488
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• 2000

This paper proposes a stabilizing controller for multirate sampled-data systems which have a periodic output The proposed controller has IMC structure, and can be decomposed into a ye-stabilizing controller, an output estimator, a filtered disturbance estimator and the inverse of the fast ye-stabilized plant model. We assume that the plant is open-loop unstable and the disturbance consists of a sum of finite number of sinusoids with different frequencies. A sufficient condition for maintaining observability in the multirate sampled-data system is derived and a design strategy for filtered disturbance rejection is proposed. In addition, we propose a design method (or the plant output estimator. The simulation results show that the proposed stabilizing controllers can stabilize the plant

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.525-525
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• 2000

In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.219-220
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• 2007

Image plane상에서의 목표의 크기, 시선각 (Line-of-Sight angle) 및 관측자의 상태 정보 등을 이용하여 목표의 상태를 추정한다. 표적 모델을 Linear Time Varying(LTV) system처럼 다룰 수 있음을 밝히고, 이를 이용하여 가관측성(observability)이 성립하는 조건을 구하고 Kalman filter를 이용하여 비선형 추정기를 설계한다. 그리고 등가속도 표적 추정, 미사일의 정지 표적 공격 등의 모의실험에 적용해 본다.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.271-278
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• 2005

In this paper, we present an adaptive observer for multi-output nonlinear systems that include unknown constant parameters and are not necessarily observable. Based on generalized nonlinear observer canonical form, new adaptive observer canonical form is proposed. Sufficient conditions are given for a nonlinear system to be transformed into the proposed adaptive observer canonical form. The existence of the proposed adaptive observer is given in terms of Lyapunov-like condition and SPR condition. An illustrative example is presented to show the design procedure of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.843-848
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• 2001

Most of gimballed inertial navigation systems(GNIS) are calibrated periodically to maintain their inherent accuracy. The existing calibration techniques using the conventional schuler test with the least square method and the multiposition test take a long time and have some problems in procedures. To solve this problem, calibration method using a linear Kalman filter is proposed by us. In this paper, the calibration method by the change of Schuler period is studied in order to improve the calibration performance of the gimballed INS. First of all, it is shown that the observability of Kalman filter is also enhanced the Schuler period is decreased. Simulation results show that the calibration performance using the present scheme is improved according to the decrease of the Schuler period and the calibration time is shortened extremely, too. And our proposed technique shows desirable estimation performance for the g-sensitive errors of inertial sensors in particular.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.117-120
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• 2002

Electrical power system has very complexity problem that it is plan measurement system to achieve Harmonic State Estimation (HSE). This complexity problem depends on discord of necessary accuracy, certainty of noise that exist in data communication damage and converter, adaptability of network modification and minimum of expense size of system, estimated monitering. Also, quantity of available measurement equipment for harmonic measurement has been limited. Therefore, systematic method that choose measurement location for harmonic state estimation. This paper is that see proposed HSE that use Observability Analysis(OA) for harmonic state estimation of electrical power system. OA depends on measurement number, measurement location and measurement form here, it is analysis method that depend on network form and admittance of the system. OA used achieve harmonic state estimation that it is Applied to New Zealand electrical power system to prove validity of HSE algorithm that propose. This study result about harmonic state estimation of electrical power system displayed very economical and effective method by OA.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.