A digital parameter-identification technique applied to biological signals
Arterial circulatory system parameter identification from diastolic blood pressure curves by digital filter techniques
Burrus, C. S.↗
SEARCH · Engineering Papers
Results for “Parameter identification”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Estimation of longitudinal aircraft characteristics using parameter identification techniques
This study compares the results from different parameter identification methods used to determine longitudinal aircraft characteristics from flight data. In general, these comparisons have found that the estimated short-period dynamics (natural frequency, damping, transfer functions) are only weakly affected by the type of identification method, however, the estimated aerodynamic coefficients may be strongly affected by the type of identification method. The estimated values for aerodynamic coefficients were found to depend upon the type of math model and type of test data used with each of the identification methods. The use of fairly complete math models and the use of long data lengths, combining both steady and nonsteady motion, are shown to provide aerodynamic coefficient values that compare favorably with the results from other testing methods such as steady-state flight and full-scale wind-tunnel experiments.
Wingrove, R. C.↗
On-orbit system parameter identification
Viewgraphs and discussion on on-orbit system parameter identification are included. Topics covered include: dynamic programming filter (DPF); cost function and estimator; frequency domain formulation structrual dynamic identification; and attributes of DPF.
Simonian, Stepan S.↗
Rotor dynamic state and parameter identification from simulated forward flight transients, part 1
State and parameter identifications from simulated forward flight blade flapping measurements are presented. The transients were excited by progressing cyclic pitch stirring or by hub stirring with constant stirring acceleration. Rotor dynamic inflow models of varying degree of sophistication were used from a one parameter inflow model (equivalent Lock number) to an eight parameter inflow model. The maximum likelihood method with assumed fixed measurement error covariance matrix was applied. The rotor system equations for both fixed hub and tilting hub are given. The identified models were verified by comparing true responses with predicted responses. An optimum utilization of the simulated measurement data can be defined. From the numerical results it can be anticipated that brief periods of either accelerated cyclic pitch stirring or of hub stirring are sufficient to extract with adequate accuracy up to 8 rotor dynamic inflow parameters plus the blade Lock number from the transients.
Hohenemser, K. H.↗
Performance Evaluation and Parameter Identification on DROID III
The DROID III project consisted of two main parts. The former, performance evaluation, focused on the performance characteristics of the aircraft such as lift to drag ratio, thrust required for level flight, and rate of climb. The latter, parameter identification, focused on finding the aerodynamic coefficients for the aircraft using a system that creates a mathematical model to match the flight data of doublet maneuvers and the aircraft s response. Both portions of the project called for flight testing and that data is now available on account of this project. The conclusion of the project is that the performance evaluation data is well-within desired standards but could be improved with a thrust model, and that parameter identification is still in need of more data processing but seems to produce reasonable results thus far.
Plumb, Julianna J.↗
NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model
A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.
Source record↗
Parameter identification and modeling of longitudinal aerodynamics
Using a comprehensive flight test database and a parameter identification software program produced at NASA Ames Research Center, a math model of the longitudinal aerodynamics of the Harrier aircraft was formulated. The identification program employed the equation error method using multiple linear regression to estimate the nonlinear parameters. The formulated math model structure adhered closely to aerodynamic and stability/control theory, particularly with regard to compressibility and dynamic manoeuvring. Validation was accomplished by using a three degree-of-freedom nonlinear flight simulator with pilot inputs from flight test data. The simulation models agreed quite well with the measured states. It is important to note that the flight test data used for the validation of the model was not used in the model identification.
Aksteter, J. W.↗
Single-Mode Projection Filters for Modal Parameter Identification for Flexible Structures
Single-mode projection filters are developed for eigensystem parameter identification from both analytical results and test data. Explicit formulations of these projection filters are derived using the orthogonal matrices of the controllability and observability matrices in the general sense. A global minimum optimization algorithm is applied to update the filter parameters by using the interval analysis method. The updated modal parameters represent the characteristics of the test data. For illustration of this new approach, a numerical simulation for the MAST beam structure is shown by using a one-dimensional global optimization algorithm to identify modal frequencies and damping. Another numerical simulation of a ten-mode structure is also presented by using a two-dimensional global optimization algorithm to illustrate the feasibility of the new method. The projection filters are practical for parallel processing implementation.
Huang, Jen-Kuang↗
Single-mode projection filters for modal parameter identification for flexible structures
Single-mode projection filters are developed for eigensystem parameter identification from both analytical results and test data. Explicit formulations of these projection filters are derived using the orthogonal matrices of the controllability and observability matrices in the general sense. A global minimum optimization algorithm is applied to update the filter parameters by using the interval analysis method. The updated modal parameters represent the characteristics of the test data. For illustration of this new approach, a numerical simulation for the MAST beam structure is shown by using a one-dimensional global optimization algorithm to identify modal frequencies and damping. The projection filters are practical for parallel processing implementation.
Huang, Jen-Kuang↗
A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling
A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.
Greenwood, Eric, II↗
Towards a methodology for robust parameter identification
Consideration is given to the problem of estimating, from experimental data, real parameters for a model with uncertainty in the form of both additive noise and norm-bounded perturbations. Such models frequently arise in robust control theory, and a framework is introduced for the consideration of experimental data in robust control analysis problems. If the analysis tools applied include robust stability tests for real parameter variations (real mu), the framework can be used to address the problem of robust parameter identification. While the techniques discussed can quickly become computationally overwhelming when applied to physical systems and real data, the approach introduces a novel way of looking at the identification problem and may be helpful in arriving at a more tractable methodology.
Smith, Roy S.↗
Modal Parameter Identification of a Flexible Arm System
In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.
Barrington, Jason↗
Parameter identification studies on the NASA/Ames Research Center Advanced Concepts Flight Simulator
The results of an aircraft parameters identification study conducted on the National Aeronautics and Space Administration/Ames Research Center Advanced Concepts Flight Simulator (ACFS) in conjunction with the Navy-NASA Joint Institute of Aeronautics are given. The ACFS is a commercial airline simulator with a design based on future technology. The simulator is used as a laboratory for human factors research and engineering as applied to the commercial airline industry. Parametric areas examined were engine pressure ratio (EPR), optimum long range cruise Mach number, flap reference speed, and critical take-off speeds. Results were compared with corresponding parameters of the Boeing 757 and 767 aircraft. This comparison identified two areas where improvements can be made: (1) low maximum lift coefficients (on the order of 20-25 percent less than those of a 757); and (2) low optimum cruise Mach numbers. Recommendations were made to those anticipated with the application of future technologies.
Mckavitt, Thomas P., Jr.↗
An Eigensystem Realization Algorithm in Frequency Domain for modal parameter identification
This paper demonstrates the close conceptual relationships between time domain and frequency domain approaches to identification of modal parameters for linear systems. A frequency domain eigensystem realization algorithm, via transfer functions, is developed using a known procedure formulated for a time domain eigensystem realization algorithm, via free decay measurement data. An important feature is the capability of windowing to concentrate analysis on the frequency range of interest. The procedure of overlap averaging is used to produce smoother spectra to reduce the effect of noise on identified modal parameters. Examples from simulation and experiments are given to illustrate the validity of formulations derived in the paper.
Juang, J.-N.↗
A simple, low cost application of a flight test parameter identification system
The flight test system combines state-of-the-art microprocessor technology and high accuracy instrumentation with parameter identification technology which minimize data and flight time requirements. The system was designed to avoid permanent modifications of the test airplane and allow quick installation. It is capable of longitudinal and lateral-directional stability and control derivative estimation. This paper presents details of this system, calibration and flight test procedures, and the results of the Cessna 172 flight test program. The system has proven easy to install, simple to operate, and capable of accurate estimation of stability and control parameters in the Cessna 172 flight tests.
Clarke, R.↗
Stability boundary and optimal operating parameter identification in milling using Bayesian learning
Here, this paper describes a novel Bayesian learning approach for stability boundary and optimal parameter identification in milling without the knowledge of the underlying tool dynamics or material cutting force coefficients. The paper is divided into two parts. First, a Bayesian learning method for stability lobe identification using test results is described. Each axial depth and spindle speed combination is characterized by a probability of stability which is updated using Bayes’ rule when a test result (stable or unstable) is made available. A novel likelihood function is defined which incorporates knowledge of the stability behavior. Numerical results show convergence to the analytical stability lobe diagram. Second, an adaptive experimental strategy to identify optimal operating parameters that maximize material removal rate is described. Numerical evaluation shows convergence to the optimal operating point with error less than 15 % within ten tests on average. The approach is validated using experimental results. Results show that the proposed method is an efficient and robust learning method to identify the stability lobe diagram and optimal operating parameters with a limited number of tests/data points.
Bayesian machine learning↗
The application of Legendre-tau approximation to parameter identification for delay and partial differential equations
Approximation schemes based on Legendre-tau approximation are developed for application to parameter identification problem for delay and partial differential equations. The tau method is based on representing the approximate solution as a truncated series of orthonormal functions. The characteristic feature of the Legendre-tau approach is that when the solution to a problem is infinitely differentiable, the rate of convergence is faster than any finite power of 1/N; higher accuracy is thus achieved, making the approach suitable for small N.
Ito, K.↗
The effectiveness of vane-aileron excitation in the experimental determination of flutter speed by parameter identification
The effectiveness of aerodynamic excitation is evaluated analytically in conjunction with the experimental determination of flutter dynamic pressure by parameter identification. Existing control surfaces were used, with an additional vane located at the wingtip. The equations leading to the identification of the equations of motion were reformulated to accommodate excitation forces of aerodynamic origin. The aerodynamic coefficients of the excitation forces do not need to be known since they are determined by the identification procedure. The 12 degree-of-freedom numerical example treated in this work revealed the best wingtip vane locations, and demonstrated the effectiveness of the aileron-vane excitation system. Results from simulated data gathered at much lower dynamic pressures (approximately half the value of flutter dynamic pressure) predicted flutter dynamic pressures with 2-percent errors.
Nissim, Eli↗