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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Oscillatory Power Control and Consensus in Unbalanced Networks Using Grid Forming Inverters

In this paper, a state-space nonlinear control previously designed for balanced operation of grid-forming (GFM) inverters is extended to unbalanced operations. Unbalanced voltages and currents are analyzed, and their time-varying direct, quadrature, and zero components are parameterized in terms of six constant parameters. These parameters provide primary control design choices for not only an inverter’s terminal voltage but also its injections of both real and oscillatory power. It is shown that the proposed GFM control can precisely achieve a desired balanced terminal voltage under unbalanced loads. It is also shown that, by allowing the terminal voltage to be slightly unbalanced, oscillatory power can be adaptively minimized. Lastly, it is illustrated that oscillatory power can also be shared among multiple GFM inverters. Case studies and their simulations demonstrate that the proposed GFM control is effective in meeting the aforementioned objectives.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2016

Smart Congestion Control for Delay- and Disruption Tolerant Networks

In this paper, we propose a novel congestion control framework for delay- and disruption tolerant networks (DTNs). The proposed framework, called Smart-DTN-CC, adjusts its operation automatically as a function of the dynamics of the underlying network. It employs reinforcement learning, a machine learning technique known to be well suited to problems in which the environment, in this case the network, plays a crucial role; yet, no prior knowledge about the target environment can be assumed, i.e., the only way to acquire information about the environment is to interact with it through continuous online learning. Smart-DTN-CC nodes get input from the environment (e.g., its buffer occupancy, set of neighbors, etc), and, based on that information, choose an action to take from a set of possible actions. Depending on an action’s effectiveness in controlling congestion, it will be given a reward. Smart-DTN-CC’s goal is to maximize the overall reward which translates to minimizing congestion. To our knowledge, Smart-DTN-CC is the first DTN congestion control framework that has the ability to automatically and continuously adapt to the dynamics of the target environment which allows Smart-DTNCC to deliver adequate performance in a variety of DTN applications and scenarios. As demonstrated by our experimental evaluation, Smart-DTN-CC is able to consistently outperform existing DTN congestion control mechanisms under a wide range of network conditions and characteristics.

Hirata, Celso M.↗
NASA NTRS1976

Viking mission support

On April 26, 1976, the network operations control center was declared available for planetary operations in support of the Viking project. This final capability in the network configuration for Viking had been delayed since February with hardware and software problems both in the control center and at the Deep Space stations. The effect of these problems, particularly insofar as they affected production of intermediate data records, the resolution of the problems, and the current status of the network operations control center in the Viking environment, are given in this article. Also discussed are the operational verification tests performed to check out the new capabilities and associated procedures. The Viking project tests supported by the DSN and finally the DSN support of Viking cruise operations, along with some statistics on performance, are included.

Mudgway, D. J.↗
NASA NTRS1991

Towards practical control design using neural computation

The objective is to develop neural network based control design techniques which address the issue of performance/control effort tradeoff. Additionally, the control design needs to address the important issue if achieving adequate performance in the presence of actuator nonlinearities such as position and rate limits. These issues are discussed using the example of aircraft flight control. Given a set of pilot input commands, a feedforward net is trained to control the vehicle within the constraints imposed by the actuators. This is achieved by minimizing an objective function which is the sum of the tracking errors, control input rates and control input deflections. A tradeoff between tracking performance and control smoothness is obtained by varying, adaptively, the weights of the objective function. The neurocontroller performance is evaluated in the presence of actuator dynamics using a simulation of the vehicle. Appropriate selection of the different weights in the objective function resulted in the good tracking of the pilot commands and smooth neurocontrol. An extension of the neurocontroller design approach is proposed to enhance its practicality.

Troudet, Terry↗
DOE OSTI2020

Lighting controls: not just for lighting anymore!

For the last few years, networked lighting controls (NLCs) have promised significant energy savings beyond what is achieved through a basic LED retrofit. At the same time, NLCs can substantially increase the cost and complexity of the lighting retrofit. And as lighting system wattage declines because of the increasing efficiency of LEDs, advanced controls have less lighting energy to save and the cost-effectiveness of the NLC investment decreases. But NLCs can be leveraged to achieve significant energy savings and value by enhancing control of other building systems. Integrating NLC with control of heating, ventilation and air conditioning (HVAC), plug load control, space utilization, and grid services all enhance the value of your NLC investment. There are already a few NLC products on the market that are capable of providing these enhanced benefits. Manufacturers and entrepreneurs are working hard to expand the impact of these products. But does system interoperability work? Can it be deployed at scale? Slipstream, NEEA and Pacific Northwest National Laboratory (PNNL) have all been attempting to answer these questions in recent pilot projects and describe the outcomes in this paper.

Hackel, Scott↗
DOE OSTI2020

Multi-Commodity Traffic Signal Control and Routing With Connected Vehicles

We report a real-time traffic management policy that integrates traffic signal control and multi-commodity routing of connected vehicles in networks with multiple destinations is developed. The proposed policy is based on a multi-commodity formulation of the store-and-forward model and assumes all vehicles are able to exchange information with the infrastructure. Vehicles share information about their current location and final destination. Based on this information, the strategy determines both optimized signal timings at every intersection and vehicle-specific routing information at every link of the network. The control actions, i.e., signal times and routing information, are updated at every cycle and delivered by a finite horizon optimal control problem cast into a rolling horizon framework. The underlying optimization problem is convex, and thus the method is suitable for real-time operation in large networks. The method is validated via a micro-simulation study in networks with up to twenty intersections and, in all simulations, outperforms a real-time traffic-responsive signal control strategy that is based on a single-commodity store-and-forward model. The scalable computation effort for increasing network sizes and prediction horizon confirms the computational efficiency of the method.

42 ENGINEERING↗
DOE OSTI2016

Isolation of three B-box zinc finger proteins that interact with STF1 and COP1 defines a HY5/COP1 interaction network involved in light control of development in soybean

LONG HYPOCOTYL5 (HY5) and STF1 (Soybean TGACG-motif binding Factor 1) are two related bZIP transcription factors that play a positive role in photomorphogenesis and hormonal signaling. In this study, we compared full length STF1 and truncated STF1 overexpression lines and found that the C-terminal 133 amino acids (194–306) possess all the HY5-like function in Arabidopsis. The STF1-DC1 mutant (1–306), with a 20 amino acid deletion at the carboxy terminus, failed to complement the hy5 mutant phenotype, which suggests an intact C-terminus is required for STF1 function. To understand the role of the C-terminal domain in photomorphogenesis we used a yeast two-hybrid screen to isolate proteins that bind to the STF1 C-terminus. We isolated three soybean cDNAs encoding the zinc-finger proteins GmSTO, GmSTH, and GmSTH2, which interact with STF1. These proteins belong to a family of B-box zinc finger proteins that include Arabidopsis SALT TOLERANCE (STO) and STO HOMOLOG (STH) and STH2, which play a role in light-dependent development and gene expression. The C-terminal 63 amino acids of STF1, containing a leucine zipper and the two N-terminal B-boxes, contains the domain involved in interactions between STF1 and GmSTO. In addition, we identified an interaction between soybean COP1 (GmCOP1) and GmSTO and GmSTH, as well as STF1, which strongly suggests the presence of a similar regulatory circuit for light signaling in soybean as in Arabidopsis. This study shows that photomorphogenic control requires complex molecular interactions among several different classes of transcription factors such as bZIP, B-box factors, and COP1, a ubiquitin ligase. - Highlights: • STF1 interact with GmSTO, GmSTH and GmSTH2. • The bZIP transcription factor STF1 requires an intact C-terminal domain for STF1 function. • STF1 and GmSTO are nuclear proteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Impact of Open Communication Networks on Load Frequency Control with Plug-In Electric Vehicles by Cyber-Physical Dynamic Co-Simulation

With the increasing electrification of the transportation sector to achieve the carbon neutrality objective, despite the challenges of charging electric vehicles (EV), there are also opportunities through smart charging EVs to improve system frequency stability; however, EV control technologies might require nontraditional communication support. This paper investigates the impacts of communication variations of EV on power system load frequency control through a cyber-physical dynamic system (CPDS) co-simulation. Here, the CPDS is built upon our previously developed transmission-and-distribution dynamic co-simulation model with the added communication variation functions (i.e., delay and packet loss). The case studies consider multiple communication variation scenarios when the system experiences an N-1 generation trip contingency. The scenarios include communication delays and packet loss using both homogeneous and heterogeneous assumptions. The outcomes of this work can help improve EV frequency regulation services and provide robust and effective tests for different load frequency control algorithms of the future power systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Neural network accelerator for quantum control

Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outside of the simulation. Existing hardware solutions structured as lookup tables are imprecise and costly. By designing a machine learning model to approximate the results of traditional tools, a more efficient method can be produced. Such a model can then be synthesized into a hardware accelerator for use in quantum systems. In this study, we demonstrate a machine learning algorithm for predicting optimal pulse parameters. This algorithm is lightweight enough to fit on a low-resource FPGA and perform inference with a latency of 175 ns and pipeline interval of 5 ns with > 0.99 gate fidelity. In the long term, such an accelerator could be used near quantum computing hardware where traditional computers cannot operate, enabling quantum control at a reasonable cost at low latencies without incurring large data bandwidths outside of the cryogenic environment.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Trapped-ion Quantum Network Real-time Control Software (QuantNet Real-time Control) v0.1.0

This real-time control software for the QUANT-NET testbed is built upon the ARTIQ (Advanced Real-Time Infrastructure for Quantum physics) ecosystem. A central contribution of this work is the software's modular and reusable architecture, which facilitates the creation of hierarchical experimental control sequences by combining precomposed sequences and subsequences as building blocks within the framework.

Cheah, You-Wei [Lawrence Berkeley National Laborat↗