• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.313-318
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• 2001

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• 대한임베디드공학회논문지
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• 제14권5호
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• pp.239-247
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• 2019

Recently, successful attacks on cyber-physical systems have been reported. As existing network security solutions are limited in preventing the system from malicious attacks, appropriate countermeasures are required from the perspective of the control. In this paper, the cyber and physical attacks are interpreted in terms of actuator and sensor attacks. Based on the interpretation, we suggest a strategy for designing Kalman filters to secure the resilience and safety of the system. Such a strategy is implemented in details to be applied for the lateral control of autonomous driving vehicle. A set of simulation results verify the performance of the proposed Kalman filters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.169-171
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• 1988

This paper deals with the robustness property of Kalman filters for linear systems with delay in output. The operator-type Riccati equation is transformed to algebraic equations, and the circle condition is derived. Based on the circle condition, it is shown that the same nondivergence margin, (1/2, .inf.) gain margin and +-60.deg. phase margin, is guaranteed as for ordinary systems.

• 한국지리정보학회지
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• 제13권2호
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• pp.157-167
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• 2010

언센티드 칼만 필터 기반의 역방향 필터를 유도하고 시뮬레이션 테스트를 통하여 확장 칼만 필터, 언센티드 칼만 필터, 그리고 확장 칼만 스무더로부터의 위치결과와 비교 분석하였다. 시뮬레이션은 GPS의 수신환경이 극단적으로 좋지 않을 경우를 고려하여 $40m{\times}40m $ 의 공간에서 4개의 곡선 그리고 5개의 직선구간으로 이루어진 궤적에서 시작점과 끝점만을 기지점으로 가정하여 수행하였다. 실험 결과 스무더는 순방향 필터에 비하여 최대 위치 오차값이 약 8~9m 정도 크게 감소하는 결과를 보여주었다. 스무더의 경우 위치오차를 직선구간과 곡선구간으로 나누어 분석하였는데, 언센티드 칼만 스무더가 확장 칼만 스무더에 비하여 직선 구간에서는 최대 10cm, 곡선 구간에서는 최대 23cm 향상된 결과를 나타내었다.

• International Journal of Aeronautical and Space Sciences
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• 제14권1호
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• pp.91-98
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• 2013

The rigorous requirements of modern spacecraft missions necessitate a precise attitude determination strategy. This paper mainly researches that, based on three space-borne attitude sensors: 3-axis rate gyros, 3-antenna GPS receiver and star-sensor. To obtain global attitude estimation after an information fusion process, a feedback-involved Federated Kalman Filter (FKF), consisting of two subsystem Kalman filters (Gyros/GPS and Gyros/Star-sensor), is established. In these filters, the state equation is implemented according to the spacecraft's kinematic attitude model, while the residual error models of GPS and star-sensor observed attitude are utilized, to establish two observation equations, respectively. Taking the sensors' different update rates into account, these two subsystem filters are conducted under a variable step size state prediction method. To improve the fault tolerant capacity of the attitude determination system, this paper designs malfunction warning factors, based on the principle of ${\chi}^2$ residual verification. Mathematical simulation indicates that the information fusion strategy overwhelms the disadvantages of each sensor, acquiring global attitude estimation with precision at a 2-arcsecs level. Although a subsystem encounters malfunction, FKF still reaches precise and stable accuracy. In this process, malfunction warning factors advice malfunctions correctly and effectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.413-418
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• 2003

In this paper, a new multirate optimal finite impulse response (FIR) filter is proposed for the signal reconstruction in the nosy filter bank systems. The multirate optimal FIR filter replaces the conventional synthesis filters and the Kalman synthesis filter. First, the generic linear model is derived from the multirate state space model for an autoregressive (AR)input signal. Second, the multirate optimal FIR filter is derived from the multirate generic linear model using the minimum variance criterion. This paper also provides numerical examples and results. The simulation results illustrate that the performance is improved compared with conventional synthesis filters and the proposed filter has advantages over the Kalman synthesis filter.

• ETRI Journal
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• 제33권4호
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• pp.641-644
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• 2011

In this letter, we propose a novel bitrate control, using both Kalman and FIR filters, based on a Hamiltonian analysis with respect to the amount of bits from each macroblock, in an encoding of a general video codec such as H.264/AVC. Since the proposed bitrate control is based on the simple computation of an optimal control method based on the Hamiltonian analysis, it is not necessary to use additional computation, such as a DCT or quantization, to estimate the bits for bitrate control. As a result, the proposed algorithm can be applied to single-pass encoding and can provide sufficient encoding speed with respect to various applications, even those requiring real-time control.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.265-270
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• 2006

Recently, inertial sensors like gyros and accelerometers have been quite miniaturized by Micro Electro-Mechanical Systems (MEMS) technology. JAXA is developing a MEM-based GPS/INS hybrid navigation system named Micro-GAIA. The navigation performance of Micro-GAIA was evaluated through off-line analysis by using flight test data. The estimation errors of the roll, pitch, and azimuth were $0.03^{\circ}$, $0.05^{\circ}$, $0.05^{\circ}$ $(1{\sigma})$, respectively. he horizontal position errors after 60-second GPS outages were reduced to 25 m CEP. The attitude errors and position errors are nearly half of ones reported previously[2]. Furthermore, using the adaptive Kalman filters, the robustness against the uncertainty of the measurement noise was improved. Comparing the innovation-based and residual-based adaptive Kalman filters, it was confirmed that the latter is robuster than the former.

• 대한전기학회논문지
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• 제40권12호
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• pp.1302-1307
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• 1991

This paper presents robustness properties of Kalman filters for linear time-invariant systems with delays in both the state and the output. The circle condition concerning the return difference matrix is derived. From the circle condition, it can be seen that the Kalman filter guarantees such nondivergence margins as (1/2,$\infty$) gain margin and $\pm$60$^{\circ}$phase margin, which are the same as those for ordinary systems. The results in this paper might be expected to make theoretical background on extending the LQG/LTR method to systems with delay in the output.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.255-260
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• 2006

Safety-critical navigation systems have to provide 'reliable' position solutions, i.e., they must detect and exclude measurement or system faults and estimate the uncertainty of the solution. To obtain more accurate and reliable navigation systems, various filtering methods have been employed to reduce measurement noise level, or integrate sensors, such as global navigation satellite system/inertial navigation system (GNSS/INS) integration. Recently, particle filters have attracted attention, because they can deal with nonlinear/non-Gaussian systems. In most GNSS applications, the GNSS measurement noise is assumed to follow a Gaussian distribution, but this is not true. Therefore, we have proposed a fault detection and exclusion method using particle filters assuming non-Gaussian measurement noise. The performance of our method was contrasted with that of conventional Kalman filter methods with an assumed Gaussian noise. Since the Kalman filters presume that measurement noise follows a Gaussian distribution, they used an overbounded standard deviation to represent the measurement noise distribution, and since the overbound standard deviations were too conservative compared to the actual distributions, this degraded the integrity-monitoring performance of the filters. A simulation was performed to show the improvement in performance of our proposed particle filter method by not using the sigma overbounding. The results show that our method could detect smaller measurement biases and reduced the protection level by 30% versus the Kalman filter method based on an overbound sigma, which motivates us to use an actual noise model instead of the overbounding or improve the overbounding methods.