Identification of observer/Kalman filter Markov parameters - Theory and experiments

Juang, Jer‐Nan; Phan, Minh Q.; Horta, Lucas G.; Longman, Richard W.

doi:10.2514/3.21006

Cited by 367 publications

(130 citation statements)

References 9 publications

(16 reference statements)

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“…(3) Using the simultaneous input/output responses, identify the individual impulse responses using the PULSE algorithm within SOCIT (Juang 1993). (4) Transform the individual impulse responses generated in Step 3 into an unsteady aerodynamic statespace system using the ERA (Juang and Pappa 1985) (within SOCIT).…”

Section: Fun3d Reduced-order Modelsmentioning

confidence: 99%

Evaluation of linear, inviscid, viscous, and reduced-order modelling aeroelastic solutions of the AGARD 445.6 wing using root locus analysis

Silva

Chwalowski

Perry

2014

International Journal of Computational Fluid Dynamics

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Reduced-order modelling (ROM) methods are applied to the Computational Fluid Dynamics (CFD)-based aeroelastic analysis of the AGARD 445.6 wing in order to gain insight regarding well-known discrepancies between the aeroelastic analyses and the experimental results. The results presented include aeroelastic solutions using the inviscid Computational Aeroelasticity Programme-Transonic Small Disturbance (CAP-TSD) code and the FUN3D code (Euler and Navier-Stokes). Full CFD aeroelastic solutions and ROM aeroelastic solutions, computed at several Mach numbers, are presented in the form of root locus plots in order to better reveal the aeroelastic root migrations with increasing dynamic pressure. Important conclusions are drawn from these results including the ability of the linear CAP-TSD code to accurately predict the entire experimental flutter boundary (repeat of analyses performed in the 1980s), that the Euler solutions at supersonic conditions indicate that the third mode is always unstable, and that the FUN3D Navier-Stokes solutions stabilize the unstable third mode seen in the Euler solutions. IntroductionClassical linear aeroelastic analyses typically produce velocity-damping-frequency (V-g-f) plots and/or root locus plots. The use of these plots has enabled the aeroelastician to view the nature of the flutter mechanism(s) in addition to identifying the condition(s) at which flutter occurs. The rapid creation of these plots was facilitated by the use of linear unsteady aerodynamics and linear aeroelastic equations of motion (Adams and Hoadley 1993).During the last few years, higher order CFD-based methods have become an important method for the computation of nonlinear unsteady aerodynamics for use in aeroelastic analyses. The use of these higher order methods provides valuable insight regarding complex flow physics at conditions where linear methods are not theoretically valid. However, the increased computational cost associated with the computation of unsteady aerodynamics and aeroelastic responses using higher order methods has resulted in a subtle change in the manner in which the aeroelastician evaluates and interprets these analyses. First, the increased computational cost of these analyses has tended to dictate a 'snapshot' approach to aeroelastic analyses whereby the aeroelastic response at a handful of dynamic pressures is all that is computed. This 'snapshot' approach is used to identify the flutter dynamic pressure but the actual flutter mechanism is not easily discernible. Second, due to the complexity of the computational methods, methods that could

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Section: Fun3d Reduced-order Modelsmentioning

confidence: 99%

Evaluation of linear, inviscid, viscous, and reduced-order modelling aeroelastic solutions of the AGARD 445.6 wing using root locus analysis

Silva

Chwalowski

Perry

2014

International Journal of Computational Fluid Dynamics

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“…It is suitable for system identification of multiple and close mode large flexible space structure, which characterizes in strict mathematic deduction, low computational complexity, and high precision. Considering that the applied range of ERA is limited to impulse excitation, Observer/Kalman filter identification (OKID) method had been generated [8] . OKID method has been successfully put into use in on-line system identification of Hubble telescope, autonomous underwater vehicle (AUV) and airplane etc.…”

Section: Introductionmentioning

confidence: 99%

“…OKID method has been successfully put into use in on-line system identification of Hubble telescope, autonomous underwater vehicle (AUV) and airplane etc. [8][9][10] . The time domain method fails to solve the two following problems in the previous researches: 1) It is unnecessary to optimize sensor deployment in simple small structure, such as plate and beam etc., while it is indispensable for complex shell structure like satellite antenna reflector; 2) How to reduce noise, determine system order and distinguish the true mode and noise mode from the polluted observation signals.…”

Section: Introductionmentioning

confidence: 99%

System identification of large flexible appendage on satellite for autonomous control

Li¹,

Wang²,

Liu³

2013

2013 10th IEEE International Conference on Control and Automation (ICCA)

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Vibration of Large flexible appendage seriously reduces the stability and accuracy of satellite attitude control, which can be solved by adjusting controller via on-orbit system identification method. This paper focuses on large flexible close mode satellite antenna, and Observer/Kalman filter identification (OKID) method is put into practice to solve the problem of system identification. Mode parameters and displacement responses under impulse and white noise excitations are extracted by finite element method (FEM), and then the concept of singular entropy is introduced to reduce observation noise and determine system order. Markov parameters are computed from displacement response and mode order, which is adopted in minimal realization of state space based on eigensystem realization algorithm (ERA). Comparing with the results of FEM in numerical simulation, OKID method is much more accurate and efficient for large flexible close mode satellite antenna on-orbit system identification.

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“…On-orbit identification experiments of spacecrafts that determine the modal parameters have been performed in some studies [1][2][3], such as the Galileo spacecraft and Hubble space telescope [4][5]. However, these identification experiments are mostly based on the linear time-invariant (LTI) system.…”

Section: Introductionmentioning

confidence: 99%

“…In existing identification algorithm for on-orbit spacecraft, the eigensystem realization algorithm (ERA) was mostly often used for the identification of modal parameters [1][2][3][4][5][9][10]. The ERA is a typical system realization method.…”

Section: Introductionmentioning

confidence: 99%

Time-varying modal parameters identification of large flexible spacecraft using a recursive algorithm

Ni¹,

Wu²,

Wu³

2016

International Journal of Aeronautical and Space Sciences

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In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.

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Identification of observer/Kalman filter Markov parameters - Theory and experiments

Cited by 367 publications

References 9 publications

Evaluation of linear, inviscid, viscous, and reduced-order modelling aeroelastic solutions of the AGARD 445.6 wing using root locus analysis

Evaluation of linear, inviscid, viscous, and reduced-order modelling aeroelastic solutions of the AGARD 445.6 wing using root locus analysis

System identification of large flexible appendage on satellite for autonomous control

Time-varying modal parameters identification of large flexible spacecraft using a recursive algorithm

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