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At least 397 records · Page 22

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NASA NTRS2000

Parametric Modeling and Fault Tolerant Control

Fault tolerant control is considered for a nonlinear aircraft model expressed as a linear parameter-varying system. By proper parameterization of foreseeable faults, the linear parameter-varying system can include fault effects as additional varying parameters. A recently developed technique in fault effect parameter estimation allows us to assume that estimates of the fault effect parameters are available on-line. Reconfigurability is calculated for this model with respect to the loss of control effectiveness to assess the potentiality of the model to tolerate such losses prior to control design. The control design is carried out by applying a polytopic method to the aircraft model. An error bound on fault effect parameter estimation is provided, within which the Lyapunov stability of the closed-loop system is robust. Our simulation results show that as long as the fault parameter estimates are sufficiently accurate, the polytopic controller can provide satisfactory fault-tolerance.

Wu, N. Eva↗

NASA NTRSDate not supplied

Updating High-Order Aeroservoelastic Models from Low-Order System Identification Results

Estimating aircraft models from test data requires several simplifying assumptions that introduce biases into the parameter estimates. In this paper, these biases are defined and a method for estimating the biases is discussed. Having an estimate of the bias allows the parameters estimated from test to be integrated into a high-order model. The Integrated Adaptive Wing Technology Maturation (IAWTM) wind tunnel model is discussed and the bias is demonstrated for one of the testing configurations. The methodology was able to estimate these biases and apply corrections to high-order aeroelastic models to improve the fit to test data. The consideration of the biases allows more meaningful comparisons and avoids the erroneous differences between pretest predictions and the fitted model.

Jeffrey Ouellette↗

NASA NTRSDate not supplied

Updating High-Order Aeroservoelastic Models from Low-Order System Identification Results

Jeffrey Ouellette↗

NASA NTRS1969

Estimation of solubility parameters from refractive index data.

Model compounds and polymers solubility parameters correlated with refractive index data

Ingham, J. D.↗

NASA NTRS1974

Parameter estimation using an a posteriori criterion

A procedure for estimating noise statistics as well as system model parameters, based on a maximum likelihood criterion, has been successfully applied to a number of aircraft parameter-identification problems. In the present investigation, an a posteriori criterion is examined for use in such an application, when it is desired to model process noise. The criteria lead to identical results when there is no process noise.

Bach, R. E., Jr.↗

NASA NTRS1984

Biophysical and spectral modeling for crop identification and assessment

The development of a technique for estimating all canopy parameters occurring in a canopy reflectance model from the measured canopy reflectance data is summarized. The Suits and the SAIL model for a uniform and homogeneous crop canopy were used to determine if the leaf area index and the leaf angle distribution could be estimated. Optimal solar/view angles for measuring CR were also investigated. The use of CR in many wavelengths or spectral bands and of linear and nonlinear transforms of CRs for various solar/view angles and various spectral bands is discussed as well as the inversion of rediance data inside the canopy, angle transforms for filtering out terrain slope effects, and modification of one dimensional models.

Goel, N. S.↗

NASA NTRS2012

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗

NASA NTRS1992

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Houlahan, Padraig↗

NASA NTRS1994

(abstract) Asteroid 4769 Casalia: Intrepretation of Optical Lightcurves Using a Radar-Derived Shape Model

A 167-parameter, 3-D shape model of Castalia, obtained from inversion of delay-Doppler images, constrained the object's subradar latitude on the date of the observations by defining an annular sky region that contains Castalia's pole. We have used the shape model and nominal Hapke parameters for S asteroids to model Castalia lightcurves obtained at Table Mountain Observatory on August 23-25, 1989, at solar phase angles ranging from 58(deg) to 90(deg). This investigation defines the projected pole's azimuthal orientation around the radar line of sight and therefore yields a least-squares estimate of the orientation of Castalia's north or south pole; there is insufficient geometric leverage to distinguish the rotation sense or to estimate values of Hapke parameters. The model lightcurves match the TMO data surprisingly well, given the modest number of shape parameters in the model and the fact that part of the asteroid was not seen by the radar.

asteroid Castalia shape radar 3-D model optical li↗

NASA NTRS2000

Results From F-18B Stability and Control Parameter Estimation Flight Tests at High Dynamic Pressures

A maximum-likelihood output-error parameter estimation technique has been used to obtain stability and control derivatives for the NASA F-18B Systems Research Aircraft. This work has been performed to support flight testing of the active aeroelastic wing (AAW) F-18A project. The goal of this research is to obtain baseline F-18 stability and control derivatives that will form the foundation of the aerodynamic model for the AAW aircraft configuration. Flight data have been obtained at Mach numbers between 0.85 and 1.30 and at dynamic pressures ranging between 600 and 1500 lbf/sq ft. At each test condition, longitudinal and lateral-directional doublets have been performed using an automated onboard excitation system. The doublet maneuver consists of a series of single-surface inputs so that individual control-surface motions cannot be correlated with other control-surface motions. Flight test results have shown that several stability and control derivatives are significantly different than prescribed by the F-18B aerodynamic model. This report defines the parameter estimation technique used, presents stability and control derivative results, compares the results with predictions based on the current F-18B aerodynamic model, and shows improvements to the nonlinear simulation using updated derivatives from this research.

Moes, Timothy R.↗

NASA NTRS1987

A new method of boundary parameter estimation for a two-dimensional diffusion system under noisy observations

The purpose of this paper is to establish a method for identifying unknown parameters involved in the boundary state of a class of diffusion systems under noisy observations. A mathematical model of the system dynamics is given by a two-dimensional diffusion equation. Noisy observations are made by sensors allocated on the system boundary. Starting with the mathematical model mentioned above, an online parameter estimation algorithm is proposed within the framework of the maximum likelihood estimation. Existence of the optimal solution and related necessary conditions are discussed. By solving a local variation of the cost functional with respect to the perturbation of parameters, the estimation mechanism is proposed in a form of recursive computations. Finally, the feasibility of the estimator proposed here is demonstrated through results of digital simulation experiments.

Sunahara, Y.↗

NASA NTRS1988

A method of boundary parameter estimation for a two-dimensional diffusion system under noisy observations

Sunahara, Y.↗

NASA NTRS1999

The Error Distribution of BATSE Gamma-Ray Burst Locations

Empirical probability models for BATSE gamma-ray burst (GRB) location errors are developed via a Bayesian analysis of the separations between BATSE GRB locations and locations obtained with the Interplanetary Network (IPN). Models are compared and their parameters estimated using 392 GRBs with single IPN annuli and 19 GRBs with intersecting IPN annuli. Most of the analysis is for the 4Br BATSE catalog; earlier catalogs are also analyzed. The simplest model that provides a good representation of the error distribution has 78% of the probability in a "core" term with a systematic error of 1.85 deg and the remainder in an extended tail with a systematic error of 5.1 deg, which implies a 68% confidence radius for bursts with negligible statistical uncertainties of 2.2 deg. There is evidence for a more complicated model in which the error distribution depends on the BATSE data type that was used to obtain the location. Bright bursts are typically located using the CONT data type, and according to the more complicated model, the 68% confidence radius for CONT-located bursts with negligible statistical uncertainties is 2.0 deg.

Briggs, Michael S.↗

NASA NTRS1994

Parameter estimation in a structural acoustic system with fully nonlinear coupling conditions

A methodology for estimating physical parameters in a class of structural acoustic systems is presented. The general model under consideration consists of an interior cavity which is separated from an exterior noise source by an enclosing elastic structure. Piezoceramic patches are bonded to or embedded in the structure; these can be used both as actuators and sensors in applications ranging from the control of interior noise levels to the determination of structural flaws through nondestructive evaluation techniques. The presence and excitation of patches, however, changes the geometry and material properties of the structure as well as involves unknown patch parameters, thus necessitating the development of parameter estimation techniques which are applicable in this coupled setting. In developing a framework for approximation, parameter estimation and implementation, strong consideration is given to the fact that the input operator is unbonded due to the discrete nature of the patches. Moreover, the model is weakly nonlinear. As a result of the coupling mechanism between the structural vibrations and the interior acoustic dynamics. Within this context, an illustrating model is given, well-posedness and approximations results are discussed and an applicable parameter estimation methodology is presented. The scheme is then illustrated through several numerical examples with simulations modeling a variety of commonly used structural acoustic techniques for systems excitations and data collection.

Banks, H. T.↗

NASA NTRS1998

The Error Distribution of BATSE GRB Location

We develop empirical probability models for BATSE GRB location errors by a Bayesian analysis of the separations between BATSE GRB locations and locations obtained with the InterPlanetary Network (IPN). Models are compared and their parameters estimated using 394 GRBs with single IPN annuli and 20 GRBs with intersecting IPN annuli. Most of the analysis is for the 4B (rev) BATSE catalog; earlier catalogs are also analyzed. The simplest model that provides a good representation of the error distribution has 78% of the locations in a 'core' term with a systematic error of 1.85 degrees and the remainder in an extended tail with a systematic error of 5.36 degrees, implying a 68% confidence region for bursts with negligible statistical errors of 2.3 degrees. There is some evidence for a more complicated model in which the error distribution depends on the BATSE datatype that was used to obtain the location. Bright bursts are typically located using the CONT datatype, and according to the more complicated model, the 68% confidence region for CONT-located bursts with negligible statistical errors is 2.0 degrees.

Briggs, Michael S.↗

NASA NTRS2009

A Cell Kinetic Model of Granulocytopoiesis Under Radiation Exposure: Extension from Murines to Canines and Humans

Space radiation poses significant challenges to space travel, and it is essential to understand the possible adverse effects from space radiation exposure to the radiosensitive organ systems that are important for immediate survival of human, e.g., the hematopoietic system. In this presentation a biomathematical model of granulocytopoiesis is described and used to analyze the blood granulocyte changes seen in the blood of mammalians under continuous and acute radiation exposure. This is one of a set of hematopoietic models that have been successfully utilized to simulate and interpret the experimental data of acute and chronic radiation on rodents. We discuss the underlying implicit regulation mechanism and the biological relevance of the kinetic parameters estimation method. Extension of the model to predictions in dogs and humans systems indicates that the modeling results are consistent with the cumulative experimental and empirical data from various sources. This implies the potential to integrate the models into one united system for monitoring the hematopoietic response of various species under irradiation. Based on the evidence of threshold responses of dogs to extended periods of low daily dose exposures, we discuss the potential health risks of the space traveler under chronic stress of low-dose irradiation and the possibly encountered Solar Particle Events.

Hu, Shaowen↗

NASA NTRS1987

An algorithmic approach to crustal deformation analysis

In recent years the analysis of crustal deformation measurements has become important as a result of current improvements in geodetic methods and an increasing amount of theoretical and observational data provided by several earth sciences. A first-generation data analysis algorithm which combines a priori information with current geodetic measurements was proposed. Relevant methods which can be used in the algorithm were discussed. Prior information is the unifying feature of this algorithm. Some of the problems which may arise through the use of a priori information in the analysis were indicated and preventive measures were demonstrated. The first step in the algorithm is the optimal design of deformation networks. The second step in the algorithm identifies the descriptive model of the deformation field. The final step in the algorithm is the improved estimation of deformation parameters. Although deformation parameters are estimated in the process of model discrimination, they can further be improved by the use of a priori information about them. According to the proposed algorithm this information must first be tested against the estimates calculated using the sample data only. Null-hypothesis testing procedures were developed for this purpose. Six different estimators which employ a priori information were examined. Emphasis was put on the case when the prior information is wrong and analytical expressions for possible improvements under incompatible prior information were derived.

Iz, Huseyin Baki↗

NASA NTRS2008

Wake Vortex Inverse Model User's Guide

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B.

Lai, David↗