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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probing Quantum Telecloning on Superconducting Quantum Processors

Quantum information cannot be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typically referred to as quantum cloning, and quantum teleportation. Quantum telecloning allows approximate copies of quantum information to be constructed by separate parties, using the classical results of a Bell measurement made on a prepared quantum telecloning state. Quantum telecloning can be implemented as a circuit on quantum computers using a classical coprocessor to compute classical feedforward instructions using if statements based on the results of a midcircuit Bell measurement in real time. We present universal symmetric optimal 1 → M telecloning circuits and experimentally demonstrate these quantum telecloning circuits for M = 2 up to M = 10, natively executed with real-time classical control systems on IBM Quantum superconducting processors, known as dynamic circuits. We perform the cloning procedure on many different message states across the Bloch sphere, on seven IBM Quantum processors, optionally using the error suppression technique X–X sequence digital dynamical decoupling. Two circuit optimizations are utilized: one that removes ancilla qubits for M = 2,3 , and one that reduces the total number of gates in the circuit but still uses ancilla qubits. Parallel single-qubit tomography with maximum likelihood estimation density matrix reconstruction is used in order to compute the mixed-state density matrices of the clone qubits, and clone quality is measured using quantum fidelity. These results present one of the largest and most comprehensive noisy intermediate-scale quantum computer experimental analyses on (single qubit) quantum telecloning to date. The clone fidelity sharply decreases to 0.5 for M > 5 , but for M = 2 , we are able to achieve a mean clone fidelity of up to 0.79 using dynamical decoupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1991

Application of modern control design methodology to oblique wing research aircraft

A Linear Quadratic Regulator synthesis technique was used to design an explicit model following control system for the Oblique Wing Research Aircraft (OWRA). The forward path model (Maneuver Command Generator) was designed to incorporate the desired flying qualities and response decoupling. The LQR synthesis was based on the use of generalized controls, and it was structured to provide a proportional/integral error regulator with feedforward compensation. An unexpected consequence of this design approach was the ability to decouple the control synthesis into separate longitudinal and lateral directional designs. Longitudinal and lateral directional control laws were generated for each of the nine design flight conditions, and gain scheduling requirements were addressed. A fully coupled 6 degree of freedom open loop model of the OWRA along with the longitudinal and lateral directional control laws was used to assess the closed loop performance of the design. Evaluations were performed for each of the nine design flight conditions.

Vincent, James H.↗
DOE OSTI2023

Active Fault Current Limiting Control for Half-Bridge MMC in HVDC Systems

DC faults of MMC can result in a significantly large fault current due to the discharge of submodule capacitors. The fault current not only risks damaging the MMC but also demands a considerable breaking capacity from the dc circuit breaker (DCCBs). This paper introduces two novel active fault current limiting methods (AFCLs), namely virtual impedance-based and energy control-based AFCL. The first method utilizes circulating current feedforward, which introduces a virtual arm impedance to suppress the rate of rise of the fault current. Meanwhile, the second method relies on the control of the internally stored energy of the MMC to automatically minimize the number of submodules that discharge during a dc-side fault. Therefore, both the dc-side current and the MMC arm current can be effectively suppressed after the occurrence of the fault. The proposed methods do not require fault detection and their response is proportional to the rate of rise in the fault current. Simulation case studies are presented to demonstrate the proposed methods.

active current limiting control↗
NASA NTRS1989

Design Of Feedforward Controllers For Multivariable Plants

Controllers based on simple low-order transfer functions. Mathematical criteria derived for design of feedforward controllers for class of multiple-input/multiple-output linear plants. Represented by simple low-order transfer functions, obtained without reconstruction of states of commands and disturbances. Enables plant to track command while remaining unresponsive to disturbance in steady state. Feedback controller added independently to stabilize plant or to make control system less susceptible to variations in parameters of plant.

Seraji, Homayoun↗
DOE OSTI2025

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Seedling Chloroplast Responses Induced by N-Linolenoylethanolamine Require Intact G-Protein Complexes

In animals, several long-chain N-acylethanolamines (NAEs) have been identified as endocannabinoids and are autocrine signals that operate through cell surface G-protein coupled, cannabinoid receptors. Despite the occurrence of N-acylethanolamines in land plants, including non-vascular plants, their precise signaling properties and molecular targets are not well defined. Here we show that the activity of N-linolenoylethanolamine (NAE 18:3) requires an intact G-protein complex. Specifically, genetic ablation of the Gβγ dimer or loss of the full set of atypical Gα subunits strongly attenuates an NAE 18:3-induced de-greening of cotyledons in Arabidopsis seedlings. This effect involves, at least in part, transcriptional regulation of chlorophyll biosynthesis and catabolism genes. In addition, there is feedforward transcriptional control of G-protein signaling components and G-protein interactors. These results are consistent with NAE 18:3 being a lipid signaling molecule in plants with a requirement for G-proteins to mediate signal transduction, a situation similar, but not identical, to the action of NAE endocannabinoids in animal systems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Performance constraints and compensation for teleoperation with delay

A classical control perspective is used to characterize performance constraints and evaluate compensation techniques for teleoperation with delay. Use of control concepts such as open and closed loop performance, stability, and bandwidth yield insight to the delay problem. Teleoperator performance constraints are viewed as an open loop time delay lag and as a delay-induced closed loop bandwidth constraint. These constraints are illustrated with a simple analytical tracking example which is corroborated by a real time, 'man-in-the-loop' tracking experiment. The experiment also provides insight to those controller characteristics which are unique to a human operator. Predictive displays and feedforward commands are shown to provide open loop compensation for delay lag. Low pass filtering of telemetry or feedback signals is interpreted as closed loop compensation used to maintain a sufficiently low bandwidth for stability. A new closed loop compensation approach is proposed that uses a reactive (or force feedback) hand controller to restrict system bandwidth by impeding operator inputs.

Mclaughlin, J. S.↗
NASA NTRS1992

Microgravity vibration isolation: Optimal preview and feedback control

In order to achieve adequate low-frequency vibration isolation for certain space experiments an active control is needed, due to inherent passive-isolator limitations. Proposed here are five possible state-space models for a one-dimensional vibration isolation system with a quadratic performance index. The five models are subsets of a general set of nonhomogeneous state space equations which includes disturbance terms. An optimal control is determined, using a differential equations approach, for this class of problems. This control is expressed in terms of constant, Linear Quadratic Regulator (LQR) feedback gains and constant feedforward (preview) gains. The gains can be easily determined numerically. They result in a robust controller and offers substantial improvements over a control that uses standard LQR feedback alone.

Hampton, R. D.↗
NASA NTRS1987

A combined stochastic feedforward and feedback control design methodology with application to autoland design

A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

Halyo, Nesim↗
DOE OSTI2026

Learned adaptive properties for mitigation of weight perturbations in embedded spiking networks

Recent years have seen an increased importance of neural network inference in edge-based scenarios, which impose size and power constraints requiring novel computing devices. These same edge scenarios may require operating over long periods of time, or exposure to extreme environments, resulting in a drift of neural network weights that cause degraded performance. In searching for ways to develop neural network approaches that perform robustly under these conditions, we propose a biologically-inspired mechanism for the dynamic adaptation of within-neuron parameters that is guided by a global context signal carrying information about perturbations and variability in incoming stimuli. Specifically, we demonstrate that adaptive voltage thresholds or neuronal time constants, when informed by a global context signal, can enable network-level mechanisms to recover from perturbed synaptic weights. Consistent with prior literature, the context-modulated approach is effective for recurrent, but not feedforward networks, by modulating network level dynamics. We demonstrate this approach successfully recovers performance in image classification tasks and spatiotemporal tracking tasks under idealized and Gaussian noise as well as for realistic perturbations from a memristive device when exposed to ionizing radiation. Finally, we discuss how this approach enables the design of robust and energy-efficient neuromorphic systems that perform well, even in resource-constrained scenarios with extreme environments such as edge processing.

context modulation↗
NASA NTRS1990

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Tarokh, M.↗
DOE OSTI2024

An Investigation of LES Wall Modeling for Rayleigh–Bénard Convection via Interpretable and Physics-Aware Feedforward Neural Networks with DNS

Abstract The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot. Significance Statement The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Does man always close the loop in trying to pilot a large ship?

Control of a slowly responding complex dynamic system such as a large supertanker poses special problems for the human. Experienced ship's crew members maneuvered a simulated ship in real time. The simulation was performed using a graphics display run by a DPD 11/40 minicomputer. The maneuvers consisted of piloting a large ship along a narrow waterway. Preliminary results suggest that the human operates as a feedforward controller utilizing the preview information for 'gross changes' in heading, and as a feedback controller for correcting small deviations. The instruments displayed on the deck do not seem to be helpful in all situations. In fact, evidence seems to indicate that some of the displays might even interfere with the pilot's attempt to form a good internal model.

Arnott, D. R.↗
NASA NTRS1990

An inverse dynamic method yielding flexible manipulator state trajectories

An inverse dynamic equation for a flexible manipulator is derived in a state form. By dividing the inverse system into the causal part and the anticausal part, torque is calculated in the time domain for a certain end point trajectory, as well as trajectories of all state variables. The open loop control of the inverse dynamic method shows an excellent result in simulation. For practical applications, a control strategy adapting feedback tracking control to the inverse dynamic feedforward control is illustrated, and its good experimental result is presented.

Kwon, Dong-Soo↗
NASA NTRS1990

An inverse dynamic method yielding flexible manipulator state trajectories

An inverse dynamic equation for a flexible manipulator is derived in a state form. By dividing the inverse system into the causal part and the anticausal part, one can calculate torque in the time domain for a certain end-point trajectory, as well as trajectories of all state variables. The open-loop control of the inverse dynamic method shows an excellent result in simulation. For practical applications, a control strategy adapting feedback tracking control to the inverse dynamic feedforward control is illustrated, and experimental results are presented.

Kwon, Dong-Soo↗
NASA NTRS1980

Effects of primary rotor parameters on flapping dynamics

The effects of flapping dynamics of four main rotor design features that influence the agility, stability, and operational safety of helicopters are studied. The parameters include flapping hinge offset, flapping hinge restraint, pitch-flap coupling, and blade lock number. First, the flapping equations of motion are derived that explicitly contain the design parameters. The dynamic equations are then developed for the tip-path plane, and the influence of individual and combined variations in the design parameters determined. The steady state flapping response is examined with respect to control input and aircraft angular rate which leads to a feedforward control law for control decoupling through cross feed, and a feedback control law to decouple the steady state flapping response. The condition for achieving perfect decoupling of the flapping response due to aircraft pitch and roll rates without using feedback control is also found for the hover case. It is indicated that the frequency of the regressing flapping mode of the rotor system can become low enough to require consideration in the assessment of handling characteristics.

Chen, R. T. N.↗
DOE OSTI2022

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

To improve the marketability of novel microreactor designs, there is a need for automated and optimal control of these reactors. This paper presents a methodology for performing multiobjective optimization of control drum operation for a microreactor under normal and off-nominal conditions. Here, two different case studies are used where the control drum configuration is optimized for the reactor to be critical with some desired power distribution that would satisfy peaking limits. A surrogate model for power distribution is developed based on a feedforward neural network. The process for determining weights for scalarization of the multiobjective optimization problem is also detailed. Six optimization algorithms: evolutionary strategies, differential evolution, grey wolf optimization, Harris hawks optimization, moth flame optimization and particle swarm optimization, are all applied to these cases and the results analyzed. Although all these algorithms will demonstrate optima-seeking behavior, for real-time control it is necessary to identify the best algorithm to efficiently provide reasonable optima without operator interference. The moth flame optimization algorithm was found to perform particularly well on both cases. Overall, it was found that the algorithms capable of supplying the best optima were also the most consistent. Finally, the found optima were verified with the original model used to train surrogates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1989

Design Of Combined Stochastic Feedforward/Feedback Control

Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

Halyo, Nesim↗