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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 NTRS1977

Different approaches of spectral analysis

Several approaches to the problem of the calculation of spectral power density of a random function from an estimate of the autocorrelation function were studied. A comparative study was presented of these different methods. The principles on which they are based and the hypothesis implied were pointed out. Some indications on the optimization of the length of the estimated correlation function was given. An example of application of the different methods discussed in this paper was included.

Lacoume, J. L.↗
NASA NTRS1966

The variance of spectral estimates

Step function with more than two values for computing variance of energy distribution for flat and nonflat spectra

SPECTRAL ENERGY DISTRIBUTION↗
NASA NTRS1978

Minimal order observers for linear functions of the state vector

The problem of estimating linear functions of a state vector in a multi-input/output system is considered. A simple lower bound on the observer order with arbitrary eigenvalues is established. Algorithms to construct minimal-order stable (or arbitrary dynamics) observers are also outlined.

Srinathkumar, S.↗
NASA NTRS1980

Design of a recursive vector processor using polynomial splines

The problem of obtaining smoothed estimates of function values, particularly their derivatives, from a finite set of inaccurate measurements is considered. A recursive two-dimensional vector processor is introduced as an approximation to the nonrecursive constrained least-squares estimation. Here, piecewise bicubic Hermite polynomials are extensively used as approximating functions, and the smoothing integral is converted to a discrete quadratic form. This makes it possible to convert the problem of fitting an approximating function to one of estimating the function values and derivatives at the nodes.

Kim, C. S.↗
NASA NTRS1974

Classification by means of B-spline potential functions with applications to remote sensing

A method is presented for using B-splines as potential functions in the estimation of likelihood functions (probability density functions conditioned on pattern classes), or the resulting discriminant functions. The consistency of this technique is discussed. Experimental results of using the likelihood functions in the classification of remotely sensed data are given.

Bennett, J. O.↗
NASA NTRS1982

The computation of Laplacian smoothing splines with examples

Laplacian smoothing splines (LSS) are presented as generalizations of graduation, cubic and thin plate splines. The method of generalized cross validation (GCV) to choose the smoothing parameter is described. The GCV is used in the algorithm for the computation of LSS's. An outline of a computer program which implements this algorithm is presented along with a description of the use of the program. Examples in one, two and three dimensions demonstrate how to obtain estimates of function values with confidence intervals and estimates of first and second derivatives. Probability plots are used as a diagnostic tool to check for model inadequacy.

Wendelberger, J. G.↗
NASA NTRS1991

Cometary water-group ions in the region surrounding Comet Giacobini-Zinner - Distribution functions and bulk parameter estimates

The bulk parameters (number density and thermal energy density) of cometary water-group ions in the region surrounding Comet Giacobini-Zinner have been derived using data from the EPAS instrument on the ICE spacecraft. The derivation is based on the assumption that the pick-up ion distribution function is isotropic in the frame of the bulk flow, an approximation which has previously been shown to be reasonable within about 400,000 km of the comet nucleus along the spacecraft trajectory. The transition between the pick-up and mass-loaded regions occurs at the cometary shock, which was traversed at a cometocentric distance of about 100,000 km along the spacecraft track. Examination of the ion distribution functions in this region, transformed to the bulk flow frame, indicates the occurrence of a flattened distribution in the vicinity of the local pick-up speed, and a steeply falling tail at speeds above, which may be approximated as an exponential in ion speed.

Staines, K.↗
NASA NTRS1974

Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations

This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discussed in detail and methods for their solution are proposed. New results on the calculation of state sensitivity functions via reduced order models are given. Several methods for speeding convergence and reducing computation time are also discussed.

Gupta, N. K.↗
NASA NTRS1982

Sampling errors in the estimation of empirical orthogonal functions

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

North, G. R.↗
NASA NTRS1982

An identification algorithm for linear stochastic systems with time delays

Linear discrete stochastic control systems containing unknown multiple time delays, plant parameters and noise variances are considered. An algorithm is established which uses the maximum-likelihood technique to identify the unknown parameters. An estimated likelihood function is evaluated based on the previous parameter estimates, which in turn generates a new descent direction vector to update the unknown parameters. The delays and plant parameters are identified in their respective parameter spaces. An example of a second-order stochastic system has been implemented by digital simulation to demonstrate the applicability of the algorithm.

Leondes, C. T.↗
NASA NTRS1999

Detecting Controller Malfunctions in Electromagnetic Environments: Modeling and Estimation of Nominal System Function - Part 1

A strategy for detecting control law calculation errors in critical flight control computers during laboratory validation testing is presented. This paper addresses Part I of the detection strategy which involves the use of modeling of the aircraft control laws and the design of Kalman filters to predict the correct control commands. Part II of the strategy which involves the use of the predicted control commands to detect control command errors is presented in the companion paper.

Weinstein, Bernice↗
NASA NTRS2024

Shape Servoing of Deformable Objects Using Model Estimation and Barrier Lyapunov Function

An adaptive shape servoing control method is presented in this article to manipulate a deformable object into a desired shape in 3-D. A finite-point-based representation of the deformable object is used and the deformation Jacobian matrix is approximated using Fourier series basis functions. The unknown parameters of the deformation Jacobian are learned by using the velocity applied to a control point on the object and corresponding change of positions of the points describing the entire object. An integral concurrent learning (ICL)-based parameter update law is designed along with a constrained controller to satisfy the state constraints on the motion of the control point using Barrier Lyapunov function analysis. ICL-based parameter update law uses data history of velocity and corresponding positions of the points along with their current values. An efficient algorithm to update the history stack using singular value maximization is proposed based on the structure of the regressor matrix. Simulations using a physical simulator and experiments using a robot platform are performed to validate the performance of the proposed controller on two different deformable objects.

Vrithik Raj Guthikonda↗
NASA NTRS1979

Non-Maxwellian velocity distribution functions associated with steep temperature gradients in the solar transition region. Paper 1: Estimate of the electron velocity distribution functions

It was shown that, in the presence of the steep temperature gradients characteristic of EUV models of the solar transition region, the electron and proton velocity distribution functions are non-Maxwellian and are characterized by high energy tails. The magnitude of these tails are estimated for a model of the transition region and the heat flux is calculated at a maximum of 30 percent greater than predicted by collision-dominated theory.

Roussel-Dupre, R.↗