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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hybrid Symbolic-Numerical Modeling and Parametric Stability Analysis of DC–AC Power Systems

Hybrid DC-AC power systems integrating diverse inverter-based resources (IBRs) and multi-terminal high-voltage direct current (MTDC) networks represent a promising architecture for future power grids, while introducing challenges for modeling, stability analysis, and control design. This paper develops a hybrid symbolic-numerical modeling framework and tool to characterize the parametric small-signal stability of DC-AC coupled power systems. The proposed approach constructs parametric state-space models to enable efficient representation of system dynamics under varying control parameters and network configurations, with target parameters retained as symbolic variables and the remainder treated numerically. The stability analysis framework covers eigenvalue, sensitivity, and stability boundary and region characterization. Enhanced linear matrix inequality (LMI) techniques are proposed to directly certify small-signal stability over regions of parameter space while also reducing the conservativeness and computational burden. The resulting tools and frameworks enable rapid parametric model construction across diverse grid conditions, thereby facilitating stability-informed control and operation in complex DC–AC power systems.

DC–AC power systems↗
NASA NTRS2017

Meteorological Support Interface Control Working Group (MSICWG) Instrumentation, Data Format, and Networks Document

The purpose of this document is to provide an overview of instrumentation discussed at the Meteorological Interface Control Working Group (MSICWG), a reference for data formats currently used by members of the group, a summary of proposed formats for future use by the group, an overview of the data networks of the group's members. This document will be updated as new systems are introduced, old systems are retired, and when the MSICWG community necessitates a change to the formats. The MSICWG consists of personnel from the National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC), NASA Marshall Space Flight Center (MSFC), NASA Johnson Space Center (JSC), National Oceanic and Atmospheric Administration National Weather Service Spaceflight Meteorology Group (SMG), and the United States Air Force (USAF) 45th Space Wing and Weather Squadron. The purpose of the group is to coordinate the distribution of weather related data to support NASA space launch related activities.

Brenton, James↗
NASA NTRS2003

Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

Gundy-Burlet, Karen↗
DOE OSTI2019

Laboratory-Scale Microgrid System for Control of Power Distribution in Local Energy Networks - Part II: Implementation and Case Study

In this chapter, we provide the detailed implementation of the proposed microgrid framework in part I. As a case study, a droop-based load sharing algorithm with the capability of controlling the active and reactive power have been implemented. Several load sharing scenarios have been studied to verify the capability of the suggested prototype in performance evaluation and verification of different control strategies in microgrid systems. The performed experiments confirm the capacity of the proposed structure in microgrid research and development (R&D), as well as education.

design↗
NASA NTRS1993

Parametric motion control of robotic arms: A biologically based approach using neural networks

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.

Bock, O.↗
DOE OSTI2023

Decentralized Voltage Control with Peer-to-peer Energy Trading in a Distribution Network

Utilizing distributed renewable and energy storage resources via peer-to-peer (P2P) energy trading has long been touted as a solution to improve energy system’s resilience and sustainability. Consumers and prosumers (those who have energy generation resources), however, do not have expertise to engage in repeated P2P trading, and the zero-marginal costs of renewables present challenges in determining fair market prices. To address these issues, we propose a multi-agent reinforcement learning (MARL) framework to help automate consumers’ bidding and management of their solar PV and energy storage resources, under a specific P2P clearing mechanism that utilizes the so-called supply-demand ratio. In addition, we show how the MARL framework can integrate physical network constraints to realize decentralized voltage control, hence ensuring physical feasibility of the P2P energy trading and paving ways for real-world implementations.

Feng, Chen↗
NASA NTRS1998

The Application of Dedicated Controllers to Parallel/Serial Exhauster Trains

Twenty new dedicated controllers were interfaced to the Distributed Control System (DCS) at NASA Lewis Research Center. Better surge avoidance, improved energy savings, interface intricacies, and plant complexities are the subjects of this paper. Problems with the existing Programmable Logic Controller (PLC) control logic are described as well as the solutions implemented with the new controllers. The complexity of the new communication network between the dedicated controllers, Multipurpose Micro-Processor (MMPs), and the operator workstations are illustrated. The complicated nature of the plant and methods of controlling the associated processes are also discussed.

Sadhukhan, Debashis↗
DOE OSTI2015

SBIR Phase II Final Report - Multi-Protocol Energy Management Gateway for Home-Area Networks

Significant amounts of electricity, natural gas, and heating oil are wasted by homeowners due to inefficient operation and inadequate maintenance of heating, ventilation, and air conditioning (HVAC) equipment. Coincident’s work under this award reduces energy waste, saves consumers money, and reduces carbon emissions. It does so in three ways: First, Coincident’s approach replaces the traditional thermostat with a wireless network of sensors and controllers that measure temperature, humidity and occupancy in multiple rooms in the house. The “Internet of Things” is a technology trend holding the promise of ubiquitous inexpensive sensors. The reality, however, is that energy and HVAC monitoring and management is a patchwork of incompatible protocols and expensive proprietary technologies. Coincident’s multi-protocol architecture, developed in part under this award tackles this problem and brings low cost interoperable sensor and control devices to market. Second, the Coincident system eliminates hard-to-program and rigid thermostat schedules and instead provides automatic operation of heating and cooling by combining individual temperature and comfort preferences with energy-saving targets, real-time utility use information, weather data, and room utilization patterns. Energy efficiency technology must be appealing to consumers otherwise it will not be used. The Coincident user interface has engaging features such as remote control from any smart phone or web browser and per-room performance breakdowns. Expected energy savings resulting from more efficient operation of heating and air conditioning equipment are in the range of 10-20%. Third, the Coincident system provides heating and air-conditioning contractors with fine-grained performance data for every residence they support (subject to customer privacy controls). This data is integrated from diverse networks within the residence and includes HVAC performance and fuel use data. This information allows the partner to validate energy savings and identify potential system faults (whether from installation problems or maintenance issues). When combined with professional installation as part of high-efficiency HVAC upgrade, energy savings levels of 20-30% can be achieved. Economic feasibility of energy efficiency technology is one of the key challenges addressed in this award. The Coincident system is engineered to be delivered at a disruptive price point, making the system financially feasible for new and retrofit homes of all types and sizes. The Coincident system is intended to be sold through the HVAC professional—the industry most capable of improving HVAC efficiency. Providing HVAC contractors with detailed home performance data motivates them to sell the product, provides them with maintenance and upgrade revenue opportunities, and therefore delivers customer savings and environmental benefits. Having demonstrated technical and financial feasibility, Coincident has won additional grants and awards, participated in pilot projects, started partnership discussions with several HVAC equipment vendors, and has lined up several large channel partners ready to participate in large pilot rollouts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Evaluating Function-as-a-Service (FaaS) frameworks for the Accelerator Control System

As particle accelerator control systems evolve in complexity and scale, the need for responsive, scalable, and cost-effective computational infrastructure becomes increasingly critical. Function-as-a-Service (FaaS) offers an alternative to traditional monolithic architecture by enabling event-driven execution, automatic scaling, and fine-grained resource utilization. This paper explores the applicability and performance of FaaS frameworks in the context of a modern particle accelerator control system, with the objective of evaluating their suitability for short lived and triggered workloads. In this paper, we evaluate prominent open-source FaaS platforms in executing functional logic, triggers, and diagnostics routines. Evaluation metrics consist of cold-start latency, scalability, performance, integration with other open-source tools like Kafka. Experimental workloads were designed to simulate real-world control tasks when implemented as stateless FaaS functions. These workloads were benchmarked under various invocation loads and network conditions. Self-hosted FaaS platforms, when deployed within accelerator networks, offer greater control over execution environment, better integration with legacy systems, and support for real-time guarantees when paired with message queues. Based on lessons learned and evaluation metrics, this paper describes reliability of the FaaS framework for the Accelerator Control Systems (ACS).

Jaikar, A. [Fermilab] (ORCID:0000000332046217)↗
DOE OSTI2023

Control Systems Design for STS Accelerator

The Second Target Station (STS) Project will expand the capabilities of the existing Spallation Neutron Source (SNS), with a suite of neutron instruments optimized for long wavelengths. A new accelerator transport line will be built to deliver one out of four SNS pulses to the new target station. The Integrated Control Systems (ICS) will provide remote control, monitoring, OPI, alarms, and archivers for the accelerator systems, such as magnets power supply, vacuum devices, and beam instrumentation. The ICS will upgrade the existing Linac LLRF controls to allow independent operation of the FTS and STS and support different power levels of the FTS and STS proton beam. The ICS accelerator controls are in the phase of preliminary design for the control systems of magnet power supply, vacuum, LLRF, Timing, Machine protection system (MPS), and computing and machine network. The accelerator control systems build upon the existing SNS Machine Control systems, use the SNS standard hardware and EPICS software, and take full advantage of the performance gains delivered by the PPU Project at SNS.

Yan, Jay↗
DOE OSTI2023

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems

This paper studies the trade-off between the degree of decentralization and the performance of a distributed controller in a linear-quadratic control setting. We study a system of interconnected agents over a graph and a distributed controller, called k-distributed control, which lets the agents make control decisions based on the state information within distance k on the underlying graph. This controller can tune its degree of decentralization using the parameter k and thus allows a characterization of the relationship between decentralization and performance. We show that under mild assumptions, including stabilizability, detectability, and a subexponentially growing graph condition, the performance difference between k-distributed control and centralized optimal control becomes exponentially small in k. Finally, this result reveals that distributed control can achieve near-optimal performance with a moderate degree of decentralization, and thus it is an effective controller architecture for large-scale networked systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

An OSI Architecture for the Deep Space Network

The flexibility and robustness of a monitor and control system are a direct result of the underlying inter-processor communications architecture. A new architecture for monitor & control at the Deep Space Network Communications Complexes has been developed based on the Open System Interconnection (OSI) standards. The suitability of OSI standards for DSN M&C has been proven in the laboratory. The laboratory success has resulted in choosing an OSI-based architecture for DSS-13 M&C. DSS-13 is the DSN experimental station and is not part of the "operational" DSN; it's role is to provide an environment to test new communications concepts can be tested and conduct unique science experiments. Therefore, DSS-13 must be robust enough to support operational activities, while also being flexible enough to enable experimentation. This paper describes the M&C architecture developed for DSS-13 and the results from system and operational testing.

OSI↗
DOE OSTI2019

Heuristic Dynamic Programming for Adaptive Virtual Synchronous Generators

In this paper a neural network heuristic dynamic programing (HDP) is used for optimal control of the virtual inertia-based control of grid connected three-phase inverters. It is shown that the conventional virtual inertia controllers are not suited for non-inductive grids. A neural network-based controller is proposed to adapt to any impedance angle. Applying an adaptive dynamic programming controller instead of a supervised controlled method enables the system to adjust itself to different conditions. The proposed HDP consists of two subnetworks: critic network and action network. These networks can be trained during the same training cycle to decrease the training time. The simulation results confirm that the proposed neural network HDP controller performs better than the traditional direct-fed voltage and/or reactive power controllers in virtual inertia control schemes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

On Expected Value Strong Controllability

The Probabilistic Simple Temporal Network (PSTN) generalizes Simple Temporal Networks with Uncertainty (STNUs) by introducing probability distributions over the timing of uncontrollable timepoints. PSTNs are controllable if there is a strategy to execute the controllable timepoints while bounding the risk of violating any constraint to a small value. If this risk bound can't be satisfied, PSTNs are not considered controllable. We introduce the Expected Value Probabilistic SimpleTemporal Network (EPSTN), which extends PSTNs by including a benefit to the satisfaction of temporal constraints. We study the problem of Expected Value Strong Controllability (EvSC) of EPSTNs, which seeks a schedule maximizing the expected value of satisfied constraints. We solve the EvSC problem by extending a previously developed linear program, combined with search over constraints to violate at execution time. We describe conditions under which the solution to this linear program is the maximum expected value schedule. We then show how to search for constraints to discard, using the linear program at the core of the search. While the general problem is shown to be exponential, we conclude by providing several methods to bound the complexity of search.

Planning↗
NASA NTRS1993

Model reduction for the dynamics and control of large structural systems via neutral network processing direct numerical optimization

Three neural network processing approaches in a direct numerical optimization model reduction scheme are proposed and investigated. Large structural systems, such as large space structures, offer new challenges to both structural dynamicists and control engineers. One such challenge is that of dimensionality. Indeed these distributed parameter systems can be modeled either by infinite dimensional mathematical models (typically partial differential equations) or by high dimensional discrete models (typically finite element models) often exhibiting thousands of vibrational modes usually closely spaced and with little, if any, damping. Clearly, some form of model reduction is in order, especially for the control engineer who can actively control but a few of the modes using system identification based on a limited number of sensors. Inasmuch as the amount of 'control spillover' (in which the control inputs excite the neglected dynamics) and/or 'observation spillover' (where neglected dynamics affect system identification) is to a large extent determined by the choice of particular reduced model (RM), the way in which this model reduction is carried out is often critical.

Becus, Georges A.↗
DOE OSTI2016

Designing of smart home automation system based on Raspberry Pi

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

42 ENGINEERING↗
NASA NTRS2007

F-15 837 IFCS Intelligent Flight Control System Project

This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.

Bosworth, John T.↗