• Title/Summary/Keyword: Degree of observability

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Singular Value Decomposition Approach to Observability Analysis of GPS/INS

  • Hong, Sin-Pyo;Chun, Ho-Hwan
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.133-138
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    • 2006
  • Singular value decomposition (SDV) approach is applied to the observability analysis of GPS/INS in this paper. A measure of observability for a subspace is introduced. It indicates the minimum size of perturbation in the information matrix that makes the subspace unobservable. It is shown that the measure has direct connections with observability of systems, error covariance, and singular structure of the information matrix. The observability measure given in this paper is applicable to the multi-input/multi-output time-varying systems. An example on the observability analysis of GPS/INS is given. The measure of observability is confirmed to be less sensitive to system model perturbation. It is also shown that the estimation error for the vertical component of gyro bias can be considered unobservable for small initial error covariance for a constant velocity horizontal motion.

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The Observability Analysis of SDINS on The Trajectory for The In-Flight Alignments (스트랩다운 관성항법 시스템의 운항 중 정렬을 위한 궤적에 따른 가관측성 분석)

  • Park, Joon-Goo;Lee, Jang-Gyu;Park, Chan-Gook;Chung, Do-Hyung
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1002-1004
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    • 1996
  • In this paper, presented are the results of observability analysis for the vehicle maneuver during In-Flight Alignment of SDINS. The target system for observability analysis is 10th order one. Three trajectories for IFA are considered. To analyze the observability of the time varying system, correlation coefficient is used and to measure the degree of observability of the given system, simulation is carried out using covariance matrix. The results of simulation show that trajectories which are having continuous changes in attitude and acceleration of system is superior to straight trajectory in correcting navigation errors.

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Power System Enhanced Monitoring through Strategic PMU Placement Considering Degree of Criticality of Buses

  • Singh, Ajeet Kumar;Fozdar, Manoj
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1769-1777
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    • 2018
  • This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs) considering system configuration and its attributes during the planning phase of PMU deployment. Each bus of the system is assessed on four diverse attributes; namely, redundancy of measurements, rotor angle and frequency monitoring of generator buses, reactive power deficiency, and maximum loading limit under transmission line outage contingency, and a consolidated 'degree of criticality' is determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The major contribution of the proposed work is the development of modified objective function which incorporates values of the degree of criticality of buses. The problem is formulated as maximization of the aggregate degree of criticality of the system. The resultant PMU configuration extends complete observability of the system and majority of the PMUs are located on critical buses. As budgetary restrictions on utilities may not allow installation PMUs even at optimal locations in a single phase, multi-horizon deployment of PMUs is also addressed. The proposed approach is tested on IEEE 14-bus, IEEE 30-bus, New England (NE) 39-bus, IEEE 57-bus and IEEE 118-bus systems and compared with some existing methods.

Fault Detection and Isolation of Integrated SDINS/GPS System Using the Generalized Likelihood Ratio (일반공산비 기법을 이용한 SDINS/GPS 통합시스템의 고장 검출 및 격리)

  • Shin, Jeong-Hoon;Lim, You-Chol;Lyou, Joon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.2
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    • pp.140-148
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    • 2000
  • This paper presents a fault detection and isolation(FDI) method based on Generalized Likelihood Ratio(GLR) test for the tightly coupled SDINS/CPS system. The GLR test is known to have the capability of detecting an assumed change while estimating its occurrence time and magnitude, and isolating the changing part. Once a fault is detected even if we don't know if the fault occurrs at either INS or GPS, multi-hypothesized GLR scheme performs the fault isolation between INS and GPS, and find which satellite malfunctions. However, in the INS faulty case, it turned out to fail to accomodate the fault isolation between accelerometer and gyroscope due to the coupling effects and a poor observability of the system. Hence, to isolate the INS fault, it needs to change the attitude of the vehicle resulting in enhancing the degree of observability.

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Estimation of Modal Participation Factor of a Structure under Earthquake Load (지진하중을 받는 구조물의 모드기여계수 산정)

  • 황재승;김홍진
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.461-468
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    • 2004
  • Modal participation factor(MPF) is essential to analyze structural response under earthquake load. MPF of real structure differs from that of analytic mathematical model due to the error induced from analytical assumption and construction. In this study, a identification method is proposed to calculate the MPF of real structure based on H∞ optimal model reduction. The MPF is obtained from the relationship between observability, controllability matrix of realized from S.I. and typical 2-degree state space model. The proposed method is verified thorough examples.

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Estimation of the First Modal Participation Factor of a Shear Building under Earthquake Load (지진하중을 받는 전단구조물의 1차 모드참여계수 산정)

  • Hwang, Jae-Seung;Kim, Hong-Jin;Kang, Kyung-Soo
    • Journal of the Earthquake Engineering Society of Korea
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    • v.9 no.1 s.41
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    • pp.25-32
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    • 2005
  • Seismic load is distributed to modes of a structure through the modal participation factor(MPF). The modal participation factor is essential to analyze structural response under earthquake load. MPF of a real structure differs from that of analytical mathematical model due to the error induced from analytical assumptions and during the construction. In this study, an identification method is proposed to calculate the 1st MPF of real structure based on $H^{\infty}$ optimal model reduction. The MPF is obtained from the relationship between observability and controllability matrices realized from system identification and those of a prototype 2-degree state space model. The proposed method is verified thorough numerical examples.

Initial value assumption for Estimation of Structural Dynamic System using Extended Kalman Filtering (구조물의 동특성치 예측을 위한 확장칼만필터기법의 초기치 설정에 관한 연구)

  • Jung, In-Hee;Yang, Won-Jik;Kang, Dae-Eon;Oh, Jong-Sig;Park, Hong-Shin;Yi, Waon-Ho
    • Proceedings of the Korea Concrete Institute Conference
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    • 2006.05a
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    • pp.506-509
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    • 2006
  • Extended Kalman Filter iterate the prediction and the filtering based on Initial state for the next time step. EKF method for the estimation of nonlinear parameters of a structural dynamic system is necessary that initial of state vector and error covariance matrix. Because those are unknown exactly, generally selected random values. That occasion observability problem appear because of unknown initial values. In this study, for the estimation of the nonlinear parameters, a simple one degree of Freedom example is carried out by Extended Kalman Filter. And initial value assumption for Parameter Estimation of Dynamic System are developed. The result of analysis is compared with calculated standard values.

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Optimal Selection of Master States for Order Reduction (동적시스템의 차수 줄임을 위한 주상태의 최적선택)

  • 오동호;박영진
    • Journal of KSNVE
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    • v.4 no.1
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    • pp.71-82
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    • 1994
  • We propose a systematic method to select the master states, which are retained in the reduced model after the order reduction process. The proposed method is based on the fact that the range space of right eigenvector matrix is spanned by orthogonal base vectors, and tries to keep the orthogonality of the submatrix of the base vector matrix as much as possible during the reduction process. To quentify the skewness of that submatrix, we define "Absolute Singularity Factor(ASF)" based on its singular values. While the degree of observability is concerned with estimation error of state vector and up to n'th order derivatives, ASF is related only to the minimum state estimation error. We can use ASF to evaluate the estimation performance of specific partial measurements compared with the best case in which all the state variables are identified based on the full measurements. A heuristic procedure to find suboptimal master states with reduced computational burden is also proposed. proposed.

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Design of the kalman filter for transfer alignment of strapdown inertial navigation system (스트랩다운 관성항법장치의 초기정렬 전달 칼만필터 설계)

  • Chung, Tae-Ho;Song, ki-Won;Jeon, Chang-Bae;Lyou, Joon
    • 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.

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