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Results for “dynamic state estimation”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

The estimation of the constituent densities of the upper atmosphere by means of a recursive filtering algorithm.

The structure of the upper atmosphere can be indirectly probed by light in order to determine the global density structure of ozone, aerosols, and neutral atmosphere. Scattered and directly transmitted light is measured by a satellite and is shown to be a nonlinear function of the state which is defined to be a point-wise decomposition of the density profiles. Dynamics are imposed on the state vector and a structured estimation problem is developed. The estimation of these densities is then performed using a linearized Kalman-Bucy filter and a linearized Kushner-Stratonovich filter.

Mcgarty, T. P.↗
NASA NTRS2007

GPS-Based Reduced Dynamic Orbit Determination Using Accelerometer Data

Currently two gravity field satellite missions, CHAMP and GRACE, are equipped with high sensitivity electrostatic accelerometers, measuring the non-conservative forces acting on the spacecraft in three orthogonal directions. During the gravity field recovery these measurements help to separate gravitational and non-gravitational contributions in the observed orbit perturbations. For precise orbit determination purposes all these missions have a dual-frequency GPS receiver on board. The reduced dynamic technique combines the dense and accurate GPS observations with physical models of the forces acting on the spacecraft, complemented by empirical accelerations, which are stochastic parameters adjusted in the orbit determination process. When the spacecraft carries an accelerometer, these measured accelerations can be used to replace the models of the non-conservative forces, such as air drag and solar radiation pressure. This approach is implemented in a batch least-squares estimator of the GPS High Precision Orbit Determination Software Tools (GHOST), developed at DLR/GSOC and DEOS. It is extensively tested with data of the CHAMP and GRACE satellites. As accelerometer observations typically can be affected by an unknown scale factor and bias in each measurement direction, they require calibration during processing. Therefore the estimated state vector is augmented with six parameters: a scale and bias factor for the three axes. In order to converge efficiently to a good solution, reasonable a priori values for the bias factor are necessary. These are calculated by combining the mean value of the accelerometer observations with the mean value of the non-conservative force models and empirical accelerations, estimated when using these models. When replacing the non-conservative force models with accelerometer observations and still estimating empirical accelerations, a good orbit precision is achieved. 100 days of GRACE B data processing results in a mean orbit fit of a few centimeters with respect to high-quality JPL reference orbits. This shows a slightly better consistency compared to the case when using force models. A purely dynamic orbit, without estimating empirical accelerations thus only adjusting six state parameters and the bias and scale factors, gives an orbit fit for the GRACE B test case below the decimeter level. The in orbit calibrated accelerometer observations can be used to validate the modelled accelerations and estimated empirical accelerations computed with the GHOST tools. In along track direction they show the best resemblance, with a mean correlation coefficient of 93% for the same period. In radial and normal direction the correlation is smaller. During days of high solar activity the benefit of using accelerometer observations is clearly visible. The observations during these days show fluctuations which the modelled and empirical accelerations can not follow.

VanHelleputte, Tom↗
DOE OSTI2016

Enhanced Performance Controller Design for Stochastic Systems by Adding Extra State Estimation onto the Existing Closed Loop Control

To enhance the performance of the tracking property , this paper presents a novel control algorithm for a class of linear dynamic stochastic systems with unmeasurable states, where the performance enhancement loop is established based on Kalman filter. Without changing the existing closed loop with the PI controller, the compensative controller is designed to minimize the variances of the tracking errors using the estimated states and the propagation of state variances. Moreover, the stability of the closed-loop systems has been analyzed in the mean-square sense. A simulated example is included to show the effectiveness of the presented control algorithm, where encouraging results have been obtained.

Stochastic coupling attenuation↗
DOE OSTI2022

A Process‐Model Perspective on Recent Changes in the Carbon Cycle of North America

Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year —1 for the period 2000–2019 (0.31 and 0.44 PgC year —1 in each decade); split into 0.18 ± 0.12 PgC year —1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year —1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (—0.02 ± 0.46 PgC year —1 ). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

A Process-Model Perspective on Recent Changes in the Carbon Cycle of North America

Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year−1 for the period 2000–2019 (0.31 and 0.44 PgC year−1 in each decade); split into 0.18 ± 0.12 PgC year−1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year−1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (−0.02 ± 0.46 PgC year−1). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.

Guillermo Murray-Tortarolo↗
DOE OSTI2024

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

MC 2 : A Deeper Look at ZwCl 2341.1+0000 with Bayesian Galaxy Clustering and Weak Lensing Analyses

ZwCl 2341.1+0000, a merging galaxy cluster with disturbed X-ray morphology and widely separated (~3 Mpc) double radio relics, was thought to be an extremely massive (10 - 30 X 10 14 M⊙) and complex system with little known about its merger history. We present JVLA 2-4 GHz observations of the cluster, along with new spectroscopy from our Keck/DEIMOS survey, and apply Gaussian Mixture Modeling to the three-dimensional distribution of 227 con rmed cluster galaxies. After adopting the Bayesian Information Criterion to avoid over tting, which we discover can bias total dynamical mass estimates high, we nd that a three-substructure model with a total dynamical mass estimate of 9:39 ± 0:81 X 10 14 M⊙ is favored. We also present deep Subaru imaging and perform the rst weak lensing analysis on this system, obtaining a weak lensing mass estimate of 5:57±2:47X10 14 M⊙. This is a more robust estimate because it does not depend on the dynamical state of the system, which is disturbed due to the merger. Our results indicate that ZwCl 2341.1+0000 is a multiple merger system comprised of at least three substructures, with the main merger that produced the radio relics occurring near to the plane of the sky, and a younger merger in the North occurring closer to the line of sight. Dynamical modeling of the main merger reproduces observed quantities (relic positions and polarizations, subcluster separation and radial velocity difference), if the merger axis angle of ~10 +34 -6 degrees and the collision speed at pericenter is ~1900 +300 -200 km/s.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Large scale state estimation algorithms for DSN tracking station location determination

Estimation of precise tracking station locations for deep space navigation is based on combining state estimates derived from a multitude of planetary encounter missions with planet direction information provided by the planetary ephemeris. Procedures for reducing the dimensionality of the station location estimation problem and for analytically correcting estimates for ephemeris updates have been developed. Using Householder transforms the large scale state estimation problem is decomposed into a sequence of dynamically uncoupled problems of lower dimension. The effect of an ephemeris update is shown to be adequately approximated by Brouwer-Clemence Set III perturbations for the earth-moon barycenter and the target planet for each mission.

Ellis, J.↗
NASA NTRS1986

Control design for robust stability in linear regulators: Application to aerospace flight control

Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.

Yedavalli, R. K.↗
NASA NTRS1992

Design and evaluation of a robust dynamic neurocontroller for a multivariable aircraft control problem

The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.

Troudet, T.↗
NASA NTRS1992

Design and evaluation of a robust dynamic neurocontroller for a multivariable aircraft control problem

The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.

Troudet, T.↗
DOE OSTI2018

Projection-Based Constrained Fusion Performance with Link Loss and Measurement Bias

Sensor networks have been deployed in many real-world applications for tracking and monitoring of dynamic targets over large geographical areas. We consider a scenario where a number of ground and/or airborne sensors are used to jointly track a ground target with certain constraints on its motion dynamics, such as those defined by roadways. The state estimates from these sensors are sent over a lossy communications network to a remote fusion center for fusion. We propose both centralized and distributed projection-based methods to incorporate known constraints into the estimation and fusion process. In addition to presenting simple closed-form projected fusion solutions, we also show how to utilize knowledge of the constraints into the fusion process by two distance-based weighting methods. Wealso explore the effect of link loss and sensor measurement bias on tracking accuracy performance of constrained fusion using illustrative tracking examples. Performance evaluation results demonstrate the potential of adopting weighted average fusers in improving the overall tracking performance in the presenceof link loss and measurement bias.

Liu, Qiang↗
DOE OSTI2017

Estimating the Contribution of Dynamical Ejecta in the Kilonova Associated with GW170817

The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a kilonova. This Letter examines how the mass of the dynamical ejecta can be estimated without a direct electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to numerical simulations of mergers with dynamical ejecta. Specifically, we apply the model to the binary masses inferred from the GW measurements, and use the resulting mass of the dynamical ejecta to estimate its contribution (without the effects of wind ejecta) to the corresponding kilonova light curves from various models. The distributions of dynamical ejecta mass range between ${M}_{\mathrm{ej}}={10}^{-3}-{10}^{-2}\,{M}_{\odot }$ for various equations of state, assuming that the neutron stars are rotating slowly. In addition, we use our estimates of the dynamical ejecta mass and the neutron star merger rates inferred from GW170817 to constrain the contribution of events like this to the r-process element abundance in the Galaxy when ejecta mass from post-merger winds is neglected. We find that if ≳10% of the matter dynamically ejected from binary neutron star (BNS) mergers is converted to r-process elements, GW170817-like BNS mergers could fully account for the amount of r-process material observed in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

On-board estimation technology for space station - Current status and future developments.

Design considerations and projected solutions to on-board automated estimation techniques for advanced technology controls on a space station are described, with emphasis on the state estimator. The space station is modelled as a collection of rigid and flexible bodies connected at a finite number of hinges. The systems dynamics are characterized by angular velocities of the base body, gimbal angles, and deflections of the flexible appendages. The state estimator evolution is projected to occur in four generations, with the first being control logic in the Viking and Voyager spacecraft, the second in the Shuttle and Galileo probe, the third being large antennas and the prototype space station, the last, around the year 2000, for the actual space station. Considerations for attitude, ephemeris, shape determination, and position estimation through each generation are discussed.

Rodriguez, G.↗
DOE OSTI2014

Impact of network topology on synchrony of oscillatory power grids

Replacing conventional power sources by renewable sources in current power grids drastically alters their structure and functionality. In particular, power generation in the resulting grid will be far more decentralized, with a distinctly different topology. Here, we analyze the impact of grid topologies on spontaneous synchronization, considering regular, random, and small-world topologies and focusing on the influence of decentralization. We model the consumers and sources of the power grid as second order oscillators. First, we analyze the global dynamics of the simplest non-trivial (two-node) network that exhibit a synchronous (normal operation) state, a limit cycle (power outage), and coexistence of both. Second, we estimate stability thresholds for the collective dynamics of small network motifs, in particular, star-like networks and regular grid motifs. For larger networks, we numerically investigate decentralization scenarios finding that decentralization itself may support power grids in exhibiting a stable state for lower transmission line capacities. Decentralization may thus be beneficial for power grids, regardless of the details of their resulting topology. Regular grids show a specific sharper transition not found for random or small-world grids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Benchmarking Quantum Simulators Using Ergodic Quantum Dynamics

Here we propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentally prepared state and an ideal target state, applicable to a wide class of analog quantum simulators without advanced spatiotemporal control. Our protocol relies on universal fluctuations emerging from generic Hamiltonian dynamics, which we discover in the present work. It does not require fine-tuned control over state preparation, quantum evolution, or readout capability, while achieving near optimal sample complexity: a percent-level precision is obtained with ~103 measurements, independent of system size. Furthermore, the accuracy of our fidelity estimation improves exponentially with increasing system size. We numerically demonstrate our protocol in a variety of quantum simulator platforms, including quantum gas microscopes, trapped ions, and Rydberg atom arrays. We discuss applications of our method for tasks such as multiparameter estimation of quantum states and processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗