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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Computer experiments in preparation of system identification from transient rotor model tests, part 2

System identification methods which can extract model rotor paramenters with reasonable accuracy from noise polluted blade flapping transient measurements were developed. Usually parameter identification requires data on the state variables, that is on deflections and on rate of deflections. The small size of rotor models makes it, however, difficult to measure more than the blade flapping deflections. For the computer experiments it was, therefore, assumed that only noisy deflection measurements are available. Parameter identifications were performed for one and two unknown parameters. Both rotating coordinates and multiblade coordinates were used. It was found that data processing with a digital filter allowed by numerical differentiation a sufficiently accurate determination of the rates of deflection and of the accelerations to obtain reasonable parameter estimates with a simple linear estimator.

Hohenemser, K. H.↗
NASA NTRS1993

System identification and model reduction using modulating function techniques

Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

Shen, Yan↗
NASA NTRS1992

A second-order structural identification procedure via state space-based system identification

A theory is presented for transforming the system theory-based realization models into the corresponding physical coordinate-based structural models. The theory has been implemented into a computational procedure and applied to several example problems. The results show that the present transformation theory yields an objective model basis possessing a unique set of structural parameters from an infinite set of equivalent system realization models. For proportionally damped systems, the transformation directly and systematically yields the normal modes and modal damping. When non-proportional damping is present, the relative magnitude and phase of the damped model shapes are separately characterized, and a corrective transformation is then employed to capture the undamped normal modes and non-diagonal modal damping matrix.

Alvin, K. F.↗
NASA NTRS1985

On-orbit systems identification of flexible spacecraft

The process of on-orbit systems identification of flexible spacecraft is examined in terms of the difficulties that are expected because of the potentially unmanageable number of unknown model parameters due to the very high order system models involved. A Jordon block canonical form and global model parameters are used to reduce the number of unknown parameters to manageable numbers. A Bayesian approach is discussed which enables the merging of theoretical models with ground or on-orbit test results by using Unconditional Maximum Likelihood Parameter Estimation. A Modified Newton-Raphson technique is proposed for determining the model parameter estimates and an expected fit error criterion is recommended for the determination of the model structure and order reduction.

Taylor, L. W., Jr.↗
NASA NTRSDate not supplied

Recent System Identification Research at NASA Langley Research Center

This talk summarizes some of the recent advances in system identification at NASA Langley Research Center. Efforts discussed were applied to aeroelastic models, aircraft with redundant inputs and feedback control active, and aircraft flying in turbulence. Topics mentioned include experiment design with orthogonal multisine inputs, frequency response estimation, maximum likelihood parameter estimation, and parameter estimation considering process noise.

NASA LaRC↗
NASA NTRS1992

A Gamma Memory Neural Network for System Identification

A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

Motter, Mark A.↗
NASA NTRSDate not supplied

System Identification for Propellers at High Incidence Angles

Propellers used for electric vertical takeoff and landing (eVTOL) aircraft propulsion systems experience a wide range of aerodynamic conditions, including large incidence angles relative to oncoming airflow. In oblique flow, propellers exhibit deviations in thrust and torque oriented along the propeller axis of rotation, as well as significant off-axis forces and moments. Although important for modeling eVTOL aircraft aerodynamics, sparse experimental data or mathematical models exist for propellers at incidence. This paper describes a propulsion system modeling methodology for the Langley Aerodrome No. 8 (LA-8) tandem tilt-wing, eVTOL aircraft. System identification methods are applied to isolated propeller wind tunnel data gathered across the vehicle's flight envelope to develop a mathematical model of the propulsion system, including a static motor model, dynamic motor model, and propeller aerodynamic model. Modeling results validated against data withheld from the modeling process indicate good predictive capability and agree with theoretical expectations. The results are followed by a discussion of model implementation strategies into high-fidelity eVTOL aircraft simulations.

system identification↗
NASA NTRS2021

System Identification for Propellers at High Incidence Angles

Propellers used for electric vertical takeoff and landing (eVTOL) aircraft propulsion systems experience a wide range of aerodynamic conditions, including large incidence angles relative to oncoming airflow. In oblique flow, propellers exhibit deviations in thrust and torque oriented along the propeller axis of rotation, as well as significant off-axis forces and moments. Although important for modeling eVTOL aircraft aerodynamics, sparse experimental data or mathematical models exist for propellers at incidence. This paper describes a propulsion system modeling methodology for the LA-8 tandem tilt-wing, eVTOL aircraft. System identification methods are applied to isolated propeller wind tunnel data gathered across the vehicle's flight envelope to develop a mathematical model of the propulsion system, including a static motor model, dynamic motor model, and propeller aerodynamic model. Modeling results validated against data withheld from the modeling process indicate good predictive capability and agree with theoretical expectations. The results are followed by a discussion of model implementation strategies into high-fidelity eVTOL aircraft simulations.

system identification↗
NASA NTRS1993

Substructure system identification and synthesis

This paper explores the possibility of performing system identification at the substructure level and then synthesizing the results to obtain a mathematical model for the assembled structure. The study here shows that in order to enforce interface compatibility and equilibrium conditions to the substructure test data, it is necessary to place collocated actuator/sensor pair at every interface degree-of-freedom. Procedures for assembling substructure transfer function data, substructure state-space models, and substructure Markov parameters are presented. Testing difficulties and possible solutions are also discussed. A numerical simulation example is included to illustrate the proposed substructure synthesis methods.

Su, Tzu-Jeng↗
NASA NTRS1999

Fractional System Identification: An Approach Using Continuous Order-Distributions

This paper discusses the identification of fractional- and integer-order systems using the concept of continuous order-distribution. Based on the ability to define systems using continuous order-distributions, it is shown that frequency domain system identification can be performed using least squares techniques after discretizing the order-distribution.

Hartley, Tom T.↗
NASA NTRS1995

System Identification of Damped Truss-Like Space Structures

A spacecraft payload flown on a launch vehicle experiences dynamic loads. The dynamic loads are caused by various phenomena ranging from the start-up of the launch vehicle engine to wind gusts. A spacecraft payload should be designed to meet launch vehicle dynamic loads. One of the major steps taken towards determining the dynamic loads is to correlate the finite element model of the spacecraft with the test results of a modal survey test. A test-verified finite element model of the spacecraft should possess the same spatial properties (stiffness, mass, and damping) and modal properties (frequencies and mode shapes) as the test hardware representing the spacecraft. The test-verified and correlated finite element model of the spacecraft is then coupled with the finite element model of the launch vehicle for analysis of loads and stress. Modal survey testing, verification of a finite element model, and modification of the finite element model to match the modal survey test results can easily be accomplished if the spacecraft structure is simple. However, this is rarely the case. A simple structure here is defined as a structure where the influence of nonlinearity between force and displacement (uncertainty in a test, for example, with errors in input and output), and the influence of damping (structural, coulomb, and viscous) are not pronounced. The objective of this study is to develop system identification and correlation methods with the focus on the structural systems that possess nonproportional damping. Two approaches to correct the nonproportional damping matrix of a truss structure were studied, and have been implemented on truss-like structures such as the National Aeronautics and Space Administration's space station truss. The results of this study showed nearly 100 percent improvement of the correlated eigensystem over the analytical eigensystem. The first method showed excellent results with up to three modes used in the system identification process. The second method could handle more modes, but required more computer usage time, and the results were less accurate than those of the first method.

Armand, Sasan↗
NASA NTRS1990

On-orbit system identification using active members

The capability to perform accurate on-orbit system identification for both open loop (passive) and closed loop (active) structural systems will be required for future NASA missions; especially those missions which require large precision structures. The information is required to accurately establish the dynamic characteristics of the operational structure in order to adjust the structure itself using the concepts of Adaptive Structures and/or the control system. This paper presents the test results of using Active Members in an adaptive structural system to excite a free-free structure to determine both open and closed loop dynamic characteristics.

Kuo, C. P.↗
NASA NTRS2001

System identification of dynamic closed-loop control of total peripheral resistance by arterial and cardiopulmonary baroreceptors

Prolonged exposure to microgravity in space flight missions (days) impairs the mechanisms responsible for defense of arterial blood pressure (ABP) and cardiac output (CO) against orthostatic stress in the post-flight period. The mechanisms responsible for the observed orthostatic intolerance are not yet completely understood. Additionally, effective counter measures to attenuate this pathophysiological response are not available. The aim of this study was to investigate the ability of our proposed system identification method to predict closed-loop dynamic changes in TPR induced by changes in mean arterial pressure (MAP) and right atrial pressure (RAP). For this purpose we designed and employed a novel experimental animal model for the examination of arterial and cardiopulmonary baroreceptors in the dynamic closed-loop control of total peripheral resistance (TPR), and applied system identification to the analysis of beat-to-beat fluctuations in the measured signals. Grant numbers: NAG5-4989. c 2001. Elsevier Science Ltd. All rights reserved.

Non-NASA Center↗
NASA NTRS1988

System identification in the microcomputer environment

An implementation of an algorithm for system identification, the eigenvalue realization algorithm (ERA), on a microcomputer is reported. Test results are presented to show that accurate structural identification can be performed in a microcomputer environment. It is also shown that the memory limits (640 K) of small machines are generally adequate for solving large scale problems (e.g., Hankel matrices with 15,000 elements), with run times being on the order of several minutes.

Garcia, Ephrahim↗
NASA NTRS2018

Practical Aspects of the Frequency Domain Approach for Aircraft System Identification

Practical aspects of the frequency-domain approach for aircraft system identification are explained and demonstrated. Topics related to experiment design, flight data analysis, and dynamic modeling are included. For demonstration purposes, simulated time series data and simulated flight data from an F-16 nonlinear simulation with realistic noise are used. This approach enables detailed evaluations of the techniques and results, because the true characteristics of the data and aircraft dynamics are known for the simulated data. Analytical techniques and practical considerations are examined for the finite Fourier transform, nonparametric frequency response estimation, parametric modeling in the frequency domain, experiment design for frequency-domain modeling, data analysis and modeling in the frequency domain, and real-time calculations. Flight data from a subscale jet transport aircraft are used to demonstrate some of the techniques and technical issues.

Morelli, Eugene A.↗