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At least 145 records · Page 8

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NASA NTRS1973

Parameter estimation in linear models of the human operator in a closed loop with application of deterministic test signals

Parameter estimation techniques are discussed with emphasis on unbiased estimates in the presence of noise. A distinction between open and closed loop systems is made. A method is given based on the application of external forcing functions consisting of a sun of sinusoids; this method is thus based on the estimation of Fourier coefficients and is applicable for models with poles and zeros in open and closed loop systems.

Vanlunteren, A.↗

NASA NTRS1990

Optimal input design for aircraft parameter estimation using dynamic programming principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Klein, Vladislav↗

NASA NTRS1990

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

Morelli, Eugene A.↗

NASA NTRS1980

User's manual for MMLE3, a general FORTRAN program for maximum likelihood parameter estimation

A user's manual for the FORTRAN IV computer program MMLE3 is described. It is a maximum likelihood parameter estimation program capable of handling general bilinear dynamic equations of arbitrary order with measurement noise and/or state noise (process noise). The theory and use of the program is described. The basic MMLE3 program is quite general and, therefore, applicable to a wide variety of problems. The basic program can interact with a set of user written problem specific routines to simplify the use of the program on specific systems. A set of user routines for the aircraft stability and control derivative estimation problem is provided with the program.

Maine, R. E.↗

NASA NTRS2002

Multi-Variable Model-Based Parameter Estimation Model for Antenna Radiation Pattern Prediction

A new procedure is presented to develop multi-variable model-based parameter estimation (MBPE) model to predict far field intensity of antenna. By performing MBPE model development procedure on a single variable at a time, the present method requires solution of smaller size matrices. The utility of the present method is demonstrated by determining far field intensity due to a dipole antenna over a frequency range of 100-1000 MHz and elevation angle range of 0-90 degrees.

Deshpande, Manohar D.↗

NASA NTRS1985

Doppler parameter estimation for spaceborne synthetic-aperture radars

Problems in the determination of Doppler parameters for spaceborne synthetic-aperture radar (SAR) data processing are examined. The degradations in image quality due to errors in these parameters are summarized. It is shown that these parameters can be estimated using accurate spacecraft ancillary data. In cases where such data are not available, two techniques are proposed to estimate these parameters using the coherent radar return. These techniques were tested with the Seasat SAR data and the test results demonstrate that the accuracies achieved exceed the system performance requirements. Possible applications of these techniques in other areas of SAR data utilization are briefly discussed.

Li, F.-K.↗

NASA NTRS1998

Application of Model Based Parameter Estimation for Fast Frequency Response Calculations of Input Characteristics of Cavity-Backed Aperture Antennas Using Hybrid FEM/MoM Technique

Model Based Parameter Estimation (MBPE) is presented in conjunction with the hybrid Finite Element Method (FEM)/Method of Moments (MoM) technique for fast computation of the input characteristics of cavity-backed aperture antennas over a frequency range. The hybrid FENI/MoM technique is used to form an integro-partial- differential equation to compute the electric field distribution of a cavity-backed aperture antenna. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency derivatives of the integro-partial-differential equation formed by the hybrid FEM/ MoM technique. Using the rational function approximation, the electric field is obtained over a frequency range. Using the electric field at different frequencies, the input characteristics of the antenna are obtained over a wide frequency range. Numerical results for an open coaxial line, probe-fed coaxial cavity and cavity-backed microstrip patch antennas are presented. Good agreement between MBPE and the solutions over individual frequencies is observed.

Reddy C. J.↗

NASA NTRS1979

Comparison of stability and control parameters for a light, single-engine, high-winged aircraft using different flight test and parameter estimation techniques

The longitudinal and lateral stability and control parameters for a high wing, general aviation, airplane are examined. Estimations using flight data obtained at various flight conditions within the normal range of the aircraft are presented. The estimations techniques, an output error technique (maximum likelihood) and an equation error technique (linear regression), are presented. The longitudinal static parameters are estimated from climbing, descending, and quasi steady state flight data. The lateral excitations involve a combination of rudder and ailerons. The sensitivity of the aircraft modes of motion to variations in the parameter estimates are discussed.

Suit, W. T.↗

NASA NTRS2005

Aerodynamic Parameter Estimation for the X-43A (Hyper-X) from Flight Data

Aerodynamic parameters were estimated based on flight data from the third flight of the X-43A hypersonic research vehicle, also called Hyper-X. Maneuvers were flown using multiple orthogonal phase-optimized sweep inputs applied as simultaneous control surface perturbations at Mach 8, 7, 6, 5, 4, and 3 during the vehicle descent. Aerodynamic parameters, consisting of non-dimensional longitudinal and lateral stability and control derivatives, were estimated from flight data at each Mach number. Multi-step inputs at nearly the same flight conditions were also flown to assess the prediction capability of the identified models. Prediction errors were found to be comparable in magnitude to the modeling errors, which indicates accurate modeling. Aerodynamic parameter estimates were plotted as a function of Mach number, and compared with estimates from the pre-flight aerodynamic database, which was based on wind-tunnel tests and computational fluid dynamics. Agreement between flight estimates and values computed from the aerodynamic database was excellent overall.

Morelli, Eugene A.↗

NASA NTRS1988

Parameter estimation in nonlinear distributed systems - Approximation theory and convergence results

An abstract approximation framework and convergence theory is described for Galerkin approximations applied to inverse problems involving nonlinear distributed parameter systems. Parameter estimation problems are considered and formulated as the minimization of a least-squares-like performance index over a compact admissible parameter set subject to state constraints given by an inhomogeneous nonlinear distributed system. The theory applies to systems whose dynamics can be described by either time-independent or nonstationary strongly maximal monotonic operators defined on a reflexive Banach space which is densely and continuously embedded in a Hilbert space. It is demonstrated that if readily verifiable conditions on the system's dependence on the unknown parameters are satisfied, and the usual Galerkin approximation assumption holds, then solutions to the approximating problems exist and approximate a solution to the original infinite-dimensional identification problem.

Banks, H. T.↗

NASA NTRSDate not supplied

Aerodynamic Parameter Estimation Using Reconstructed Turbulence Measurements

A classical method for reconstructing atmospheric turbulence from onboard measurements of airdata and inertial sensors was improved. The reconstructed turbulence was included in a system identification analysis to estimate nondimensional stability and control derivatives in a longitudinal short period model using the maximum likelihood equation-error method with Fourier transform data. Practical aspects of the approach are discussed, such as reconstruction accuracy, data collinearity, model structure, and real-time estimation. Results using simulation and flight test data for a subscale airplane indicated that accurate turbulence reconstructions and parameter estimates could be obtained from maneuvering flight in high levels of turbulence.

Jared A Grauer↗

NASA NTRS1976

Additional comments on 'Multistage least-squares parameter estimation'

The purpose of this correspondence is to call attention to other solutions to the problem addressed in the above paper, that of adding or deleting parameters or measurements from a given linear model. The solution algorithms proposed in the article are numerically ill-conditioned and are less efficient, in terms of both computational and storage requirements, than the methods described here. Several numerically stable, compact, flexible, and efficient algorithms for analyzing the parameter estimation problem are described and others are referenced.

Bierman, G. J.↗

NASA NTRS1979

Inclusion of unsteady aerodynamics in longitudinal parameter estimation from flight data

A simple vortex system, used to model unsteady aerodynamic effects into the rigid body longitudinal equations of motion of an aircraft, is described. The equations are used in the development of a parameter extraction algorithm. Use of the two parameter-estimation modes, one including and the other omitting unsteady aerodynamic modeling, is discussed as a means of estimating some acceleration derivatives. Computer generated data and flight data, used to demonstrate the use of the parameter-extraction algorithm are studied.

Queijo, M. J.↗

NASA NTRS1986

A methodology for airplane parameter estimation and confidence interval determination in nonlinear estimation problems

An algorithm for maximum likelihood (ML) estimation is developed with an efficient method for approximating the sensitivities. The ML algorithm relies on a new optimization method referred to as a modified Newton-Raphson with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. With the fitted surface, sensitivity information can be updated at each iteration with less computational effort than that required by either a finite-difference method or integration of the analytically determined sensitivity equations. MNRES eliminates the need to derive sensitivity equations for each new model, and thus provides flexibility to use model equations in any convenient format. A random search technique for determining the confidence limits of ML parameter estimates is applied to nonlinear estimation problems for airplanes. The confidence intervals obtained by the search are compared with Cramer-Rao (CR) bounds at the same confidence level. The degree of nonlinearity in the estimation problem is an important factor in the relationship between CR bounds and the error bounds determined by the search technique. Beale's measure of nonlinearity is developed in this study for airplane identification problems; it is used to empirically correct confidence levels and to predict the degree of agreement between CR bounds and search estimates.

Murphy, P. C.↗

NASA NTRS1983

Joint state and parameter estimation

Recent results are described concerning the problem of state reconstruction for a class of nonlinear distributed systems. The methods are then applied to the problem of joint state and parameter estimation. An example with the wave equation is presented.

Carmichael, N.↗

NASA NTRS1983

Cubic spline approximation techniques for parameter estimation in distributed systems

Approximation schemes employing cubic splines in the context of a linear semigroup framework are developed for both parabolic and hyperbolic second-order partial differential equation parameter estimation problems. Convergence results are established for problems with linear and nonlinear systems, and a summary of numerical experiments with the techniques proposed is given.

Banks, H. T.↗

NASA NTRS1977

A parameter estimation subroutine package

Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. FORTRAN subroutines have been developed to facilitate analyses of a variety of parameter estimation problems. Easy to use multipurpose sets of algorithms are reported that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used.

Bierman, G. J.↗

NASA NTRS2018

Real-Time Parameter Estimation for Flexible Aircraft

A method for estimating aeroelastic stability and control derivatives for flexible aircraft is developed and demonstrated using flight test data for the X-56A subscale demonstrator. The method uses the equation-error approach with frequency-domain data, and can be applied post-flight or in real time during flight. The non-dimensional aeroelastic forces and moments and the explanatory variables (including generalized displacement, rate, and acceleration states for the vibration modes) are estimated using a finite element model and onboard sensor measurements in both a least squares and Kalman filtering framework. The data are then transformed into the frequency domain for parameter estimation using equation error. This method can result in a more efficient analysis than with other iterative methods, and can leverage existing statistical tools for model structure determination, data collinearity detection, combining multiple maneuvers or prior information, and others to improve model quality.

Grauer, Jared A.↗