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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 109 records · Page 6
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NASA NTRS1985

On a variational approach to some parameter estimation problems

Examples (1-D seismic, large flexible structures, bioturbation, nonlinear population dispersal) in which a variation setting can provide a convenient framework for convergence and stability arguments in parameter estimation problems are considered. Some of these examples are 1-D seismic, large flexible structures, bioturbation, and nonlinear population dispersal. Arguments for convergence and stability via a variational approach of least squares formulations of parameter estimation problems for partial differential equations is one aspect of the problem considered.

Banks, H. T.↗
NASA NTRS1990

Efficient detection and signal parameter estimation with application to high dynamic GPS receiver

In a system for deriving position, velocity, and acceleration information from a received signal emitted from an object to be tracked wherein the signal comprises a carrier signal phase modulated by unknown binary data and experiencing very high Doppler and Doppler rate, this invention provides combined estimation/detection apparatus for simultaneously detecting data bits and obtaining estimates of signal parameters such as carrier phase and frequency related to receiver dynamics in a sequential manner. There is a first stage for obtaining estimates of the signal parameters related to phase and frequency in the vicinity of possible data transitions on the basis of measurements obtained within a current data bit. A second stage uses the estimates from the first stage to decide whether or not a data transition has actually occurred. There is a third stage for removing data modulation from the received signal when a data transition has occurred and a fourth stage for using the received signal with data modulation removed therefrom to update global parameters which are dependent only upon receiver dynamics and independent of data modulation. Finally, there is a fifth stage for using the global parameters to determine the position, velocity, and acceleration of the object.

Kumar, Rajendra↗
NASA NTRS1974

A square root formulation for the combined state-parameter estimator with application to the identification of sailplane performance

A square root formulation is presented for the discrete combined state parameter estimation problem with linear plant dynamics, Gaussian random disturbances, and constant but uncertain parameters. The estimator is a combination of the classical Kalman filter and a maximum likelihood algorithm which maximizes the parameter log-likelihood function using a first order search routine.

Froidevaux, M. R.↗
NASA NTRS2013

Parameter Estimation for Compact Binary Coalescence Signals with the First Generation Gravitational-Wave Detector Network

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a blind injection where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M25M and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

Aasi, J.↗
NASA NTRS2005

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Evaluation Studies↗
NASA NTRS1974

Parameter estimation using an a posteriori criterion

A procedure for system parameter estimation from noisy data is presented that is based on an a posteriori criterion. It is compared with a maximum likelihood approach for a process-noise case. Both methods yield identical results when the process noise is not modeled.

Bach, R. E., Jr.↗
NASA NTRS1988

Quasi-Newton methods for parameter estimation in functional differential equations

A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

Brewer, Dennis W.↗
NASA NTRS2010

Simulation and Flight Evaluation of a Parameter Estimation Input Design Method for Hybrid-Wing-Body Aircraft

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will make use of distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. Research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique and validating this technique through simulation and flight test of the X-48B aircraft. The X-48B aircraft is an 8.5 percent-scale hybrid wing body aircraft demonstrator designed by The Boeing Company (Chicago, Illinois, USA), built by Cranfield Aerospace Limited (Cranfield, Bedford, United Kingdom) and flight tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California, USA). Based on data from flight test maneuvers performed at Dryden Flight Research Center, aerodynamic parameter estimation was performed using linear regression and output error techniques. An input design technique that uses temporal separation for de-correlation of control surfaces is proposed, and simulation and flight test results are compared with the aerodynamic database. This paper will present a method to determine individual control surface aerodynamic derivatives.

Taylor, Brian R.↗
NASA NTRS1988

An investigation of new methods for estimating parameter sensitivities

Parameter sensitivity is defined as the estimation of changes in the modeling functions and the design variables due to small changes in the fixed parameters of the formulation. There are currently several methods for estimating parameter sensitivities requiring either difficult to obtain second order information, or do not return reliable estimates for the derivatives. Additionally, all the methods assume that the set of active constraints does not change in a neighborhood of the estimation point. If the active set does in fact change, than any extrapolations based on these derivatives may be in error. The objective here is to investigate more efficient new methods for estimating parameter sensitivities when the active set changes. The new method is based on the recursive quadratic programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RPQ algorithm. Inital testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity. To handle changes in the active set, a deflection algorithm is proposed for those cases where the new set of active constraints remains linearly independent. For those cases where dependencies occur, a directional derivative is proposed. A few simple examples are included for the algorithm, but extensive testing has not yet been performed.

Beltracchi, Todd J.↗
NASA NTRS1977

Parameter estimation in a human operator describing function model for a two-dimensional tracking task

A previously described parameter estimation program was applied to a number of control tasks, each involving a human operator model consisting of more than one describing function. One of these experiments is treated in more detail. It consisted of a two dimensional tracking task with identical controlled elements. The tracking errors were presented on one display as two vertically moving horizontal lines. Each loop had its own manipulator. The two forcing functions were mutually independent and consisted each of 9 sine waves. A human operator model was chosen consisting of 4 describing functions, thus taking into account possible linear cross couplings. From the Fourier coefficients of the relevant signals the model parameters were estimated after alignment, averaging over a number of runs and decoupling. The results show that for the elements in the main loops the crossover model applies. A weak linear cross coupling existed with the same dynamics as the elements in the main loops but with a negative sign.

Vanlunteren, A.↗
NASA NTRS1987

Effects of Structural Errors on Parameter Estimates

Paper introduces concept of near equivalence in probability between different parameters or mathematical models of physical system. One in series of papers, each establishes different part of rigorous theory of mathematical modeling based on concepts of structural error, identifiability, and equivalence. This installment focuses upon effects of additive structural errors on degree of bias in estimates parameters.

Hadaegh, F. Y.↗
NASA NTRS1974

Sequential parameter estimation using pseudoinverse

This correspondence presents a method for solution of the parameter estimation problem in an entirely sequential fashion. In this procedure each measurement is processed as it is received, without regard to whether it and the prior measurements have established a minimal observable data set, or without the assumption a priori of a covariance matrix in the manner of the Kalman filter. During the period prior to the establishment of the minimal data set the estimate maintains the character of the pseudoinverse constraint, that of minimum norm. In addition at each measurement, a parameter is available for deciding whether this measurement has increased the observability of the system.

Nayak, R. P.↗
NASA NTRS1983

Space Shuttle propulsion parameter estimation using optimal estimation techniques, volume 1

The mathematical developments and their computer program implementation for the Space Shuttle propulsion parameter estimation project are summarized. The estimation approach chosen is the extended Kalman filtering with a modified Bryson-Frazier smoother. Its use here is motivated by the objective of obtaining better estimates than those available from filtering and to eliminate the lag associated with filtering. The estimation technique uses as the dynamical process the six degree equations-of-motion resulting in twelve state vector elements. In addition to these are mass and solid propellant burn depth as the ""system'' state elements. The ""parameter'' state elements can include aerodynamic coefficient, inertia, center-of-gravity, atmospheric wind, etc. deviations from referenced values. Propulsion parameter state elements have been included not as options just discussed but as the main parameter states to be estimated. The mathematical developments were completed for all these parameters. Since the systems dynamics and measurement processes are non-linear functions of the states, the mathematical developments are taken up almost entirely by the linearization of these equations as required by the estimation algorithms.

Source record↗
NASA NTRS1986

Application of parameter estimation to highly unstable aircraft

This paper discusses the application of parameter estimation to highly unstable aircraft. It includes a discussion of the problems in applying the output error method to such aircraft and demonstrates that the filter error method eliminates these problems. The paper shows that the maximum likelihood estimator with no process noise does not reduce to the output error method when the system is unstable. It also proposes and demonstrates an ad hoc method that is similar in form to the filter error method, but applicable to nonlinear problems. Flight data from the X-29 forward-swept-wing demonstrator is used to illustrate the problems and methods discussed.

Maine, R. E.↗
NASA NTRS2021

Constraining the Neutron Star Mass–Radius Relation and Dense Matter Equation of State with NICER. III. Model Description and Verification of Parameter Estimation Codes

We describe the X-ray pulse profile models we use and how we use them to analyze Neutron Star Interior Composition Explorer(NICER)observations of rotation-powered millisecond pulsars to obtain information about the mass–radius relation of neutron stars and the equation of state of the dense matter in their cores. Here we detail our modeling of the observed profile of PSR J0030+0451 that we analyzed in Miller et al. and Riley et al. and describe a cross-verification of computations of the pulse profiles of a star with R/M 3, in case stars this compact need to be considered in future analyses. We also present our early cross-verification efforts of the parameter estimation procedures used by Miller et al. and Riley et al. by analyzing two distinct synthetic data sets. Both codes yielded credible regions in the mass–radius plane that are statistically consistent with one another, and both gave posterior distributions for model parameter values consistent with the values that were used to generate the data. We also summarize the additional tests of the parameter estimation procedure of Miller et al. that used synthetic pulse profiles and the NICER pulse profile of PSR J0030+0451. We then illustrate how the precision of mass and radius estimates depends on the pulsar’s spin rate and the size of its hot spot by analyzing four different synthetic pulse profiles. Finally, we assess possible sources of systematic error in the estimates made using this technique, some of which may warrant further investigation.

Slavko Bogdanov↗
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

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.↗