Multi-Output Approximate Control Variate Estimation for Enhanced Variance Reduction
Explore the source record for details and available documents.
Thomas Dixon↗
SEARCH · Engineering Papers
Results for “Control variates”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Exploring A Two-Level, Control-Variate Monte Carlo Method for Uncertainty Quantification in Criticality Safety
Explore the source record for details and available documents.
Elzohery, Rabab [ORNL] (ORCID:0000000160043633)↗
Differential games and manual control
Variational methods used to solve pursuit-evasion differential game and manual control
GAME THEORY↗
Controls on Variations of Surface Energy, Water, and Carbon Budgets within Large-Scale Amazon Basin
A key research focus of the LBA Research Program is understanding the space-time variations in interlinked surface energy, water, and carbon budgets, the controls on these variations, and the implications of these controls on the carbon sequestering capacity of the large scale forest-pasture system that dominates the Amaz6nia landscape. Quantification of these variations and controls are investigated by a combination of in situ measurements, remotely sensed measurements from space, and a realistically forced hydrometeorological model coupled to a carbon assimilation model, capable of simulating details within the surface energy and water budgets along with the principle processes of photosynthesis and respiration. Herein we describe the results of an investigation concerning the space-time controls of carbon sources and sinks distributed over the large scale Amazon basin. The results are derived from a carbon-water-energy budget retrieval system for the large scale Amazon basin, which uses a coupled carbon assimilation-hydrometeorological model as an integrating system, forced by both in situ meteorological measurements and remotely sensed radiation and precipitation fluxes obtained from a combination of GOES, SSM/I, TOMS, and TRh4M satellite measurements. Results include validation of (a) retrieved surface radiation and precipitation fluxes based on 30-min averaged surface measurements taken at Ji-Parani in Rondania and Manaus in Amazonas, and (b) modeled sensible, latent, and C02 fluxes based on tower measurements taken at Reserva Jaru, Manaus and Fazenda Nossa Senhora. The space-time controls on carbon sequestration are partitioned into sets of factors classified by: (1) above canopy meteorology, (2) incoming surface radiation, (3) precipitation interception, and (4) indigenous stomatal processes varied over the different land covers of pristine rainforest, partially, and fully logged rainforests, and pasture lands. These are the principle meteorological, thermodynamical, hydrological, and biophysical control paths which perturb net carbon fluxes and sequestration, produce time-space switching of carbon sources and sinks, undergo modulation through atmospheric boundary layer feedbacks, and respond to any discontinuous intervention on the landscape itself such as produced by human intervention in converting rainforest to pasture or conducting selective/clearcut logging operations. The results demonstrate how relative carbon sequestration capacity of the Amazonian ecosystem responds to these controls, and how interpretation of space-time heterogeneities in carbon sequestration depends on a fairly exact quantification of the interacting non-linear properties of photosynthesis in response to incoming solar flux, air-canopy temperatures, and leaf water interception -- and soil respiration in response to upper layer soil temperature and water content. The results also show how the interpretation of the control processes is highly sensitive to the scales at which the surface fluxes are analyzed.
Smith, Eric A.↗
Applications of low lift to drag ratio aerobrakes using angle of attack variation for control
Several applications of low lift to drag ratio aerobrakes are investigated which use angle of attack variation for control. The applications are: return from geosynchronous or lunar orbit to low Earth orbit; and planetary aerocapture at Earth and Mars. A number of aerobrake design considerations are reviewed. It was found that the flow impingement behind the aerobrake and the aerodynamic heating loads are the primary factors that control the sizing of an aerobrake. The heating loads and other loads, such as maximum acceleration, are determined by the vehicle ballistic coefficient, the atmosphere entry conditions, and the trajectory design. Several formulations for defining an optimum trajectory are reviewed, and the various performance indices that can be used are evaluated. The 'nearly grazing' optimal trajectory was found to provide the best compromise between the often conflicting goals of minimizing the vehicle propulsive requirements and minimizing vehicle loads. The relationship between vehicle and trajectory design is investigated further using the results of numerical simulations of trajectories for each aerobrake application. The data show the sensitivity of the trajectories to several vehicle parameters and atmospheric density variations. The results of the trajectory analysis show that low lift to drag ratio aerobrakes, which use angle of attack variation for control, can potentially be used for a wide range of aerobrake applications.
Mulqueen, J. A.↗
Diagnosing Barren Plateaus with Tools from Quantum Optimal Control
Variational Quantum Algorithms (VQAs) have received considerable attention due to their potential for achieving near-term quantum advantage. However, more work is needed to understand their scalability. One known scaling result for VQAs is barren plateaus, where certain circumstances lead to exponentially vanishing gradients. It is common folklore that problem-inspired ansatzes avoid barren plateaus, but in fact, very little is known about their gradient scaling. In this work we employ tools from quantum optimal control to develop a framework that can diagnose the presence or absence of barren plateaus for problem-inspired ansatzes. Such ansatzes include the Quantum Alternating Operator Ansatz (QAOA), the Hamiltonian Variational Ansatz (HVA), and others. With our framework, we prove that avoiding barren plateaus for these ansatzes is not always guaranteed. Specifically, we show that the gradient scaling of the VQA depends on the degree of controllability of the system, and hence can be diagnosed through the dynamical Lie algebra $\mathfrak{g}$ obtained from the generators of the ansatz. We analyze the existence of barren plateaus in QAOA and HVA ansatzes, and we highlight the role of the input state, as different initial states can lead to the presence or absence of barren plateaus. Taken together, our results provide a framework for trainability-aware ansatz design strategies that do not come at the cost of extra quantum resources. Moreover, we prove no-go results for obtaining ground states with variational ansatzes for controllable system such as spin glasses. Our work establishes a link between the existence of barren plateaus and the scaling of the dimension of $\mathfrak{g}$.
97 MATHEMATICS AND COMPUTING↗
Active flutter suppression using optical output feedback digital controllers
A method for synthesizing digital active flutter suppression controllers using the concept of optimal output feedback is presented. A convergent algorithm is employed to determine constrained control law parameters that minimize an infinite time discrete quadratic performance index. Low order compensator dynamics are included in the control law and the compensator parameters are computed along with the output feedback gain as part of the optimization process. An input noise adjustment procedure is used to improve the stability margins of the digital active flutter controller. Sample rate variation, prefilter pole variation, control structure variation and gain scheduling are discussed. A digital control law which accommodates computation delay can stabilize the wing with reasonable rms performance and adequate stability margins.
Source record↗
Robot arm dynamics and control
Variations in total inertia and gravity loads at the joint outputs are treated along with the relative importance of gravity and acceleration-generated reaction torques or forces versus inertia torques or forces. The relation between the dynamical state equations in explicit terms and servoing the manipulator is briefly discussed in the framework of state variable feedback control which also forms the basis of adaptive manipulator control. Exact state equations were determined for total inertia and gravity loads at the joint outputs as a function of joint variables, using the constant inertial and geometric parameters of the individual links defined in the respective link coordinate frames. The range of maximum variations in total inertia and gravity loads at the joint outputs was calculated for both no load and load in the hand. The main result is the construction of a set of greatly simplified state equations which describe the total inertia and gravity load variations at the output of the six joints with an average error of less than 5%.
Bejczy, A. K.↗
Efficiency and Output Power Sensitivity to Control Parameter Variations in an LCC-Series Wireless Power Transfer System
In wireless power transfer (WPT) systems, output power (Pout) can be controlled through input parameters such as, input voltage (Vin) , duty cycle (d) , and switching frequency (fsw) . The impact of these control parameters on the overall system efficiency has not been explored in previous studies. This paper focuses on the efficiency (η) and Pout sensitivity to these control parameter variations in an LCC-Series tuned WPT system. There are multiple combinations of Vin, d , and fsw that can achieve a specified target Pout . However, it is important to determine the optimal combination of these control variables that will yield the maximum η for a target Pout . A MATLAB/Simulink model is built to calculate and measure η and Pout . In order to achieve this result, several simulations are run where Vin,d , and fsw are swept across a wide range to cover all possible combinations. MATLAB's Sensitivity Analysis toolbox is used to evaluate how the parameters influence the model's output. Finally, an experimental prototype is implemented. The optimal values acquired using the sensitivity analysis is then plugged into the hardware prototype and compared with the simulation. The results obtained confirm the validity of the proposed method.
Harave, Sudarshan↗
The effect of variations in controls and displays on helicopter instrument approach capability
A flight investigation was conducted with a variable stability helicopter to determine the effects of variations in controls and displays on helicopter instrument approach capabilities. The baseline instrument approach task was a decelerating approach to a hover along a 6 deg glide slope. Pilot evaluations were obtained for both the constant speed part of the task and the deceleration and hover part of the task. The attitude stability augmentation system (SAS) was strongly preferred over the rate SAS because the aircraft had a divergent pitch response. From a display variation standpoint, it was not possible to decelerate to a hover in a consistent manner, regardless of the control system employed, with situation information only. In particular, the deceleration and hover part of the task was unacceptable without flight director command information.
Niessen, F. R.↗
Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise
Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.
NASA Discipline Space Human Factors↗
Differential games and manual control
Variational methods to solve pursuit-evasion differential game
VARIATION METHOD↗
Grid spacing control with variation diminishing splines
Methods used to specify and control two and three dimensional grids on which numerical solutions of partial differential equations may be obtained were studied. While initially focusing on grid generation, the research will evolve into a consideration of the interaction of grid generation with the solution of a partial differential equation. The multisurface method of grid generation was used to continuously patch a grid onto an existing grid. In the resulting grid the elements of the Jacobian matrix must be continuous across the boundary between the original grid and the patched grid. Programs were written which accept as input the coordinates of the original grid and the desired new boundary, and then use the three-surface or four-surface version of the multisurface method to extend the original grid out to a new boundary.
Smith, P. W.↗
MFNets: Multifidelity data-driven networks for Bayesian learning and prediction
This paper presents a multifidelity uncertainty quantification framework called MFNets. We seek to address three existing challenges that arise when experimental and simulation data from different sources are used to enhance statistical estimation and prediction with quantified uncertainty. Specifically, we demonstrate that MFNets can (1) fuse heterogeneous data sources arising from simulations with different parameterizations, e.g simulation models with different uncertain parameters or data sets collected under different environmental conditions; (2) encode known relationships among data sources to reduce data requirements; and (3) improve the robustness of existing multi-fidelity approaches to corrupted data. MFNets construct a network of latent variables (LVs) to facilitate the fusion of data from an ensemble of sources of varying credibility and cost. These LVs are posited as explanatory variables that provide the source of correlation in the observed data. Furthermore, MFNets provide a way to encode prior physical knowledge to enable efficient estimation of statistics and/or construction of surrogates via conditional independence relations on the LVs. We highlight the utility of our framework with a number of theoretical results which assess the quality of the posterior mean as a frequentist estimator and compare it to standard sampling approaches that use single fidelity, multilevel, and control variate Monte Carlo estimators. We also use the proposed framework to derive the Monte Carlo-based control variate estimator entirely from the use of Bayes rule and linear-Gaussian models -- to our knowledge the first such derivation. Finally, we demonstrate the ability to work with different uncertain parameters across different models.
97 MATHEMATICS AND COMPUTING↗
Robustness
Robustness is a buzz word common to all newly proposed space systems design as well as many new commercial products. The image that one conjures up when the word appears is a 'Paul Bunyon' (lumberjack design), strong and hearty; healthy with margins in all aspects of the design. In actuality, robustness is much broader in scope than margins, including such factors as simplicity, redundancy, desensitization to parameter variations, control of parameter variations (environments flucation), and operational approaches. These must be traded with concepts, materials, and fabrication approaches against the criteria of performance, cost, and reliability. This includes manufacturing, assembly, processing, checkout, and operations. The design engineer or project chief is faced with finding ways and means to inculcate robustness into an operational design. First, however, be sure he understands the definition and goals of robustness. This paper will deal with these issues as well as the need for the requirement for robustness.
Ryan, R.↗
Robustness
The concept of rubustness includes design simplicity, component and path redundancy, desensitization to the parameter and environment variations, control of parameter variations, and punctual operations. These characteristics must be traded with functional concepts, materials, and fabrication approach against the criteria of performance, cost, and reliability. The paper describes the robustness design process, which includes the following seven major coherent steps: translation of vision into requirements, definition of the robustness characteristics desired, criteria formulation of required robustness, concept selection, detail design, manufacturing and verification, operations.
Ryan, Robert↗
Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey
Uncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling-based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time-consuming if the simulation-based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. Finally, an algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.
97 MATHEMATICS AND COMPUTING↗
Accurate predictions from small boxes: variance suppression via the Zel'dovich approximation
Simulations have become an indispensable tool for accurate modelling of observables measured in galaxy surveys, but can be expensive if very large dynamic range in scale is required. We describe how to combine Lagrangian perturbation theory models with N-body simulations to reduce the effects of finite computational volume in the prediction of ensemble average properties in the simulations within the context of control variates. In particular we use the fact that Zel'dovich displacements, computed during initial condition generation for any simulation, correlate strongly with the final density field. Since all the correlators of biased tracers can be computed with arbitrary precision for these displacements, pairing the Zel'dovich `simulation' with the N-body realization allows hundredfold reductions in sample variance for power spectrum or correlation function estimation. Additionally, Zel'dovich control variates can accurately extend matter or tracer field emulators to larger scales than previously possible, as well as improving measurements of statistics in simulations which are inherently limited to small volumes, such as hydrodynamical simulations of galaxy formation and reionization.
79 ASTRONOMY AND ASTROPHYSICS↗