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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Surveillance system and method having parameter estimation and operating mode partitioning

A system and method for monitoring an apparatus or process asset including partitioning an unpartitioned training data set into a plurality of training data subsets each having an operating mode associated thereto; creating a process model comprised of a plurality of process submodels each trained as a function of at least one of the training data subsets; acquiring a current set of observed signal data values from the asset; determining an operating mode of the asset for the current set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a current set of estimated signal data values from the selected process submodel for the determined operating mode; and outputting the calculated current set of estimated signal data values for providing asset surveillance and/or control.

Bickford, Randall L.↗
NASA NTRS2008

Parameter Estimation of Lateral Spacecraft Fuel Slosh

Predicting the effect of fuel slosh on the attitude control system of a spacecraft or launch vehicle is a very important and challenging task. Whether the spacecraft is spinning or moving laterally, the dynamic effect of the fuel slosh helps determine whether the spacecraft will remain on its intended trajectory. Three categories of slosh can be caused by launch vehicle or spacecraft maneuvers when the fuel is in the presence of an acceleration field. These are bulk-fluid motion, subsurface wave motion (currents), and free-surface slosh. Each of these slosh types has a periodic component defined by either a spinning or a lateral motion. For spinning spacecraft, all three types of slosh can greatly affect stability. Bulk-fluid motion and free-surface slosh can affect the lateral-slosh characteristics. For either condition, an unpredicted coupled resonance between the spacecraft and its onboard fuel could threaten a mission. This ongoing research effort seeks to improve the accuracy and efficiency of modeling techniques used to predict these types of fluid motions for lateral motion. Particular efforts focus on analyzing the effects of viscoelastic diaphragms on slosh dynamics.

Sudermann, James E.↗
NASA NTRS2009

Parameter Estimation for a Hybrid Adaptive Flight Controller

This paper expands on the hybrid control architecture developed at the NASA Ames Research Center by addressing issues related to indirect adaptation using the recursive least squares (RLS) algorithm. Specifically, the hybrid control architecture is an adaptive flight controller that features both direct and indirect adaptation techniques. This paper will focus almost exclusively on the modifications necessary to achieve quality indirect adaptive control. Additionally this paper will present results that, using a full non -linear aircraft model, demonstrate the effectiveness of the hybrid control architecture given drastic changes in an aircraft s dynamics. Throughout the development of this topic, a thorough discussion of the RLS algorithm as a system identification technique will be provided along with results from seven well-known modifications to the popular RLS algorithm.

Campbell, Stefan F.↗
NASA NTRS2010

Parameter Estimation with Entangled Photons Produced by Parametric Down-Conversion

We explore the advantages offered by twin light beams produced in parametric down-conversion for precision measurement. The symmetry of these bipartite quantum states, even under losses, suggests that monitoring correlations between the divergent beams permits a high-precision inference of any symmetry-breaking effect, e.g., fiber birefringence. We show that the quantity of entanglement is not the key feature for such an instrument. In a lossless setting, scaling of precision at the ultimate "Heisenberg" limit is possible with photon counting alone. Even as photon losses approach 100% the precision is shot-noise limited, and we identify the crossover point between quantum and classical precision as a function of detected flux. The predicted hypersensitivity is demonstrated with a Bayesian simulation.

Cable, Hugo↗
NASA NTRS2008

Modeling, Simulation, and Parameter Estimation of Lateral Spacecraft Fuel Slosh

Predicting the effect of fuel slosh on a spacecraft and/or launch vehicle attitude control system is a very important and a challenging task. Whether the spacecraft is under spinning or lateral moving conditions, the dynamic effect of the fuel slosh will help determine whether the spacecraft will remain on its chosen trajectory. There are three categories of slosh that can be caused by launch vehicle and/or spacecraft maneuvers when the fuel is in the presence of an acceleration field. These include bulk fluid motion, subsurface wave motion, and free surface slosh. Each of these slosh types have a periodic component that is defined by either a spinning or lateral motion. For spinning spacecraft, all three types of slosh can play a major role in determining stability. Bulk fluid motion and free surface slosh can affect the lateral slosh characteristics. For either condition, the possibility for an unpredicted coupled resonance between the spacecraft and its on board fuel can have mission threatening affects. This on-going research effort aims at improving the accuracy and efficiency of modeling techniques used to predict these types of lateral fluid motions. In particular, efforts will focus on analyzing the effects of viscoelastic diaphragms on slosh dynamics.

Chatman, Yadira↗
NASA NTRS2017

Bayesian Treatment of Prospective LISA Parameter Estimation for Massive Black Hole Mergers

A full understanding of LISA (Laser Interferometer Space Antenna)'s science capability will require accurate models of incident waveform signals and the instrumental response. While Fisher matrix analysis is useful for some estimates, a full Bayesian treatment is needed for important cases at the limit of LISA's capability. We will apply fast analysis algorithms enabling accurate treatment with EOB (effective-one-body) waveforms and the full-featured LISA response to study the significance of higher spherical harmonics and mergers in LISA analysis.

Baker, John G.↗
NASA NTRSDate not supplied

PMSM Parameter Estimation using a Linear Unknown Input Interval Observer

In this paper, the problem of permanent magnet synchronous motor (PMSM) speed and unknown load torque estimation is addressed. For this purpose, a interval unknown input observer (UIO) for linear time-invariant (LTI) systems is used. First, the PMSM model is linearized in order to make it in a suitable form for the linear interval UIO. Then, the interval UIO is applied to allow the joint estimation of the motor speed and the unknown load torque disturbance. The main advantages of this approach is that it not only allows the joint state and unknown input estimation, but also to take the different uncertainty sources into account. Indeed, taking model and measurement uncertainty into account is crucial. Assuming that the measurement noise and disturbances are bounded, lower and upper bounds are first computed for the unmeasured state (motor speed) and then for the unknown input (load torque). The proposed approach and its limitations are demonstrated with the nonlinear PMSM model derived from its equivalent electrical circuit.

Elinirina I Robinson↗
NASA NTRSDate not supplied

Maximum-Likelihood Parameter Estimation for High-Contrast Wavefront Sensing & Control

Stellar coronagraphs use closed-loop focal-plane wavefront sensing and control algorithms to create high-contrast dark zones suitable for imaging exoplanets and exozodiacal dust clouds around nearby stars. At present, the deepest contrast has been achieved using model-based algorithms, which use the predicted focal-plane influence of the coronagraph's deformable mirrors to drive diffracted starlight toward zero over time in an optimal control framework. However, model-based algorithms are susceptible to model mismatch, wherein a departure of the coronagraph's true optical characteristics from the model predictions causes reduced control loop performance. Here, we report on a technique for maximum-likelihood estimation of the wavefront control Jacobian matrix and noise statistics of the coronagraph focal-plane electric field from data acquired in situ during closed-loop wavefront control operations. By empirically tuning the Jacobian and noise properties in a statistically rigorous fashion, the maximum-likelihood approach mitigates model mismatch and recovers near-optimal control loop performance.

coronagraphy↗
NASA NTRS1984

Maximum likelihood estimation of turbulence spectrum parameters

Estimation of the integral scale and intensity of a generic turbulence record is treated as a statistical problem of parameter estimation. Properties of parameter estimators and the method of maximum likelihood are reviewed. Likelihood equations are derived for estimation of the integral scale and intensity applicable to a general class of turbulence spectra that includes the von Karman and Dryden transverse and longitudinal spectra as special cases. The method is extended to include the Bullen transverse and longitudinal spectra. Coefficients of variation are given for maximum likelihood estimates of the integral scale and intensity of the von Karman spectra. Application of the method is illustrated by estimating the integral scale and intensity of an atmospheric turbulence vertical velocity record assumed to be governed by the von Karman transverse spectrum.

Mark, W. D.↗
NASA NTRS1988

Altimetry for non-Gaussian oceans - Height biases and estimation of parameters

The effects of a non-Gaussian ocean on satellite altimetry parameter estimation are discussed. The first part of this paper shows how non-Gaussian ocean parameters affect height estimation for satellites of the Seasat/Geosat/TOPEX type. In the second part, the estimation of the altimeter tracker bias and the non-Gaussian ocean parameters from the altimeter return signal is studied. A new convolution model that facilitates the deconvolution of the ocean surface specular point probability density function is introduced. Next, it is argued that it is not feasible in practice to estimate the electromagnetic bias from noisy altimeter returns. It is then shown that the least squares estimation of the surface parameters in the log-frequency domain has several advantages overestimating parameters in the time domain. The maximum likelihood estimation equations for the estimation of the waveform parameters are derived, and their solution is discussed.

Rodriguez, Ernesto↗
NASA NTRS2011

AMT-200S Motor Glider Parameter and Performance Estimation

Parameter and performance estimation of an instrumented motor glider was conducted at the National Aeronautics and Space Administration Dryden Flight Research Center in order to provide the necessary information to create a simulation of the aircraft. An output-error technique was employed to generate estimates from doublet maneuvers, and performance estimates were compared with results from a well-known flight-test evaluation of the aircraft in order to provide a complete set of data. Aircraft specifications are given along with information concerning instrumentation, flight-test maneuvers flown, and the output-error technique. Discussion of Cramer-Rao bounds based on both white noise and colored noise assumptions is given. Results include aerodynamic parameter and performance estimates for a range of angles of attack.

Taylor, Brian R.↗
NASA NTRS1985

Identification of dynamic systems, theory and formulation

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Maine, R. E.↗