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All sources NASA NTRS DOE OSTI

NASA NTRS2017

Space Technology Game Changing Development: NASA Affordable Vehicle Avionics (AVA)

Common Modular Avionics System for Nanolaunchers Offering Affordable Access to Space Small satellites are becoming ever more capable of performing valuable missions for both government and commercial customers. However, currently these satellites can be launched affordably only as secondary payloads. This makes it difficult for the small satellite mission to launch when needed, to the desired orbit, and with acceptable risk. What is needed is a class of low-cost launchers, so that launch costs to low-Earth orbit (LEO) are commensurate with payload costs. Several private and government-sponsored launch vehicle developers are working toward just that—the ability to affordably insert small payloads into LEO. But until now, cost of the complex avionics remained disproportionately high. AVA solves this problem. Significant contributors to the cost of launching nanosatellites to orbit are the avionics and software systems that steer and control the launch vehicles, sequence stage separation, deploy payloads, and telemeter data. The high costs of these guidance, navigation and control (GNC) avionics systems are due in part to the current practice of developing unique, single use hardware and software for each launch. High-performance, high-reliability inertial sensors components with heritage from legacy launchers also contribute to costs—but can low-cost commercial inertial sensors work just as well?

Aquilina, Rudy↗

NASA NTRS1994

Graphic Server: A real time system for displaying and monitoring telemetry data of several satellites

Known as a Graphic Server, the system presented was designed for the control ground segment of the Telecom 2 satellites. It is a tool used to dynamically display telemetry data within graphic pages, also known as views. The views are created off-line through various utilities and then, on the operator's request, displayed and animated in real time as data is received. The system was designed as an independent component, and is installed in different Telecom 2 operational control centers. It enables operators to monitor changes in the platform and satellite payloads in real time. It has been in operation since December 1991.

Douard, Stephane↗

NASA NTRS1996

Facilities for Biological Research Aboard the International Space Station

A centrifuge designed as part of an integrated biological facility for installation onboard the International Space Station is presented. The requirements for the 2.5 m diameter centrifuge, which is designed for the support of biological experiments are discussed. The scientific objectives of the facility are to: provide a means of conducting fundamental studies in which gravitational acceleration is a controllable variable; provide a 1g control; determine the threshold acceleration for physiological response, and determine the value of centrifugation as a potential countermeasure for the biomedical problems associated with space flight. The implementation of the facility is reported on, and the following aspects of the facility are described: the host resources systems supply requirements such as power and data control; the habitat holding rack; the life sciences glove box; the centrifuge; the different habitats for cell culture, aquatic studies, plant research and insect research; the egg incubator, and the laboratory support equipment.

Souza, Kenneth A.↗

NASA NTRS1985

Pilot usage of decoupled flight path and pitch controls

Data from decoupled flight maneuvers have been collected and analyzed for four AFTI-F-16 pilots operating this aircraft's highly augmented fly-by-wire control system, in order to obtain spectral density, cross spectra, and Bode amplitude data, as well as coherences and phase angles for the two longitudinal axis control functions of each of 50 20-sec epochs. The analysis of each epoch yielded five distinct plotted parameters for the left hand twist grip and right hand sidestick controller output time series. These two control devices allow the left hand to generate vertical translation, direct lift, or pitch-pointing commands that are decoupled from those of the right hand. Attention is given to the control patterns obtained for decoupled normal flight, air-to-air gun engagement decoupled maneuvering, and decoupled air-to-surface bombing run maneuvering.

Berkhout, J.↗

NASA NTRS2019

Portable Laser Guided Robotic Metrology System

This paper introduces the new Portable Laser Guided Robotic antenna range (PLGR) at the National Aeronautics and Space Administration's (NASA) Glenn Research Center. Previous work used industrial robots in fixed facilities to characterize antennas and required fixtures that do not lend themselves to portable applications.NASA's PLGR system is designed for in-situ antenna measurements at a remote site. The system consists of a robot arm mounted on a vertical lift and a laser tracker, each on a portable base. The lift and laser tracker enable scanning a surface larger than the robot's reach. To accomplish this the robot first collects all points within its reach, then the system is moved and the laser tracker is used to relocate the robot before additional points are captured.The PLGR architecture will be discussed including how safety systems and path planning are combined to effectively characterize antennas. Software was written in high level languages for flexible integration of vector network analyzers and antenna controllers. Lastly, data will be shown to demonstrate the system functionality and accuracy.

Slater, Peter A.↗

DOE OSTI2025

A Risk-Informed Approach to Trustworthiness Assessment in Digital Twins-Based Autonomous Control

In autonomous control systems, digital twins (DTs) are used to perform diagnostic and prognostic functions. The trustworthiness of these DTs is dependent on quality and coverage of the training data, model accuracy and integrity of sensor data. This work introduces a methodology to determine the trustworthiness of a DT system given faulty sensor data using a risk informed approach. Bayesian Belief Networks (BBNs) are used to propagate uncertainties and determine the probability of trustable recommendations. The decision to trust the control action provided by the DT is based on the DT output, expert opinion, and severity of problems. The performance of DTs is reliant on the data they are trained on. When they encounter out of distribution data, the trustworthiness of the recommendations decreases. To address this issue, we include an expert component that provides input on sensor degradation. For this, we utilize a generative artificial intelligence (AI) model, such as Generative Pretrained Transformer (GPT). The GPT functions as an expert with broad knowledge. The GPT is fine-tuned to understand and discriminate sensor degradation scenarios using manufactured data. This methodology is demonstrated through a case study on a Nearly Autonomous Management and Control System (NAMAC) during a steady state scenario. Various sensor degradation types with different severity levels are considered. Degraded sensor data is processed by the DT system and the fine-tuned GPT. Finally, using the BBN, we combine the GPT information and the DT output with its sources of uncertainty. This provides an output regarding the trustworthiness of the DT recommendation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1991

A time delay controller for magnetic bearings

The control of systems with unknown dynamics and unpredictable disturbances has raised some challenging problems. This is particularly important when high system performance needs to be guaranteed at all times. Recently, the Time Delay Control has been suggested as an alternative control scheme. The proposed control system does not require an explicit plant model nor does it depend on the estimation of specific plant parameters. Rather, it combines adaptation with past observations to directly estimate the effect of the plant dynamics. A control law is formulated for a class of dynamic systems and a sufficient condition is presented for control systems stability. The derivation is based on the bounded input-bounded output stability approach using L sub infinity function norms. The control scheme is implemented on a five degrees of freedom high speed and high precision magnetic bearing. The control performance is evaluated using step responses, frequency responses, and disturbance rejection properties. The experimental data show an excellent control performance despite the system complexity.

Youcef-Toumi, K.↗

NASA NTRS2003

Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing

Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.

Brenner, Martin J.↗

NASA NTRSDate not supplied

Design, Instrumentation, and Data Analysis for the SLS Core Stage Green Run Test Series

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. The actuators are powered by a Shuttle-derived hydraulic Core Auxiliary Power Unit (CAPU), and integrated with an all-new Core Stage thrust structure. The actuators are interfaced to the SLS Vehicle Management (VM) software via an all-new TVC Actuator Control (TAC) avionics subsystem. Despite the significant test and flight experience of the Shuttle hardware, the SLS Green Run ambient and hot fire test activities revealed a number of new findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC system did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. This paper is the fifth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, the design of the TVC analyses conducted during the Core Stage Green Run test series are discussed in detail. Throughout the course of the test activities, the SLS flight control team worked diligently with the Core Stage contractor to revise test command profiles and ensure sufficient instrumentation was available to collect data. Post-test analysis combined the Green Run modal, ambient, and hot fire test data, MSFC 2- axis Core Stage TVC Inertial Load Simulator (ILS) data, Hardware-In-the-Loop (HWIL) Systems Integration Lab (SIL) results, and actuator Acceptance Testing Procedure (ATP) responses. These data were used to characterize the response, validate critical math models of the TVC subsystem, and isolate the probable cause of the unexpected responses. Through comprehensive analysis of the available test data sources, the integrated team identified the dominant contributors to the observed response and developed test-correlated rationale for vehicle flight control system performance, ultimately leading to a confident posture for the Artemis I mission.

John H. Wall↗

DOE OSTI2021

A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

14 SOLAR ENERGY↗

DOE OSTI2014

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatory system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1991

Summary report: A preliminary investigation into the use of fuzzy logic for the control of redundant manipulators

The Rice University Department of Mechanical Engineering and Materials Sciences' Robotics Group designed and built an eight degree of freedom redundant manipulator. Fuzzy logic was proposed as a control scheme for tasks not directly controlled by a human operator. In preliminary work, fuzzy logic control was implemented for a camera tracking system and a six degree of freedom manipulator. Both preliminary systems use real time vision data as input to fuzzy controllers. Related projects include integration of tactile sensing and fuzzy control of a redundant snake-like arm that is under construction.

Cheatham, John B., Jr.↗

NASA NTRS1979

Tracking and data relay satellite system - NASA's new spacecraft data acquisition system

This paper describes NASA's new spacecraft acquisition system provided by the Tracking and Data Relay Satellite System (TDRSS). Four satellites in geostationary orbit and a ground terminal will provide complete tracking, telemetry, and command service for all of NASA's orbital satellites below a 12,000 km altitude. Western Union will lease the system, operate the ground terminal and provide operational satellite control. NASA's network control center will be the focal point for scheduling user services and controlling the interface between TDRSS and the NASA communications network, project control centers, and data processing. TDRSS single access user spacecraft data systems will be designed for time shared data relay support, and reimbursement policy and rate structure for non-NASA users are being developed.

Schneider, W. C.↗

DOE OSTI2026

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗

NASA NTRS1982

Analysis of several glidepath and speed control autopilot concepts for a powered lift STOL aircraft

Longitudinal performance and control utilization data are compared for several different automatic approach autopilot implementations in a powered lift STOL aircraft. As few as two, to as many as four laws reflecting both backside and frontside control techniques. The data are developed from analysis and simulation, but represent configurations which were demonstrated in flight. Transient response characteristics from initial glidepath offsets are presented, along with system operation in turbulence. In furnishing quantitative data in controlled levels of simulated turbulence, these results provide a useful supplement to various flight investigations (including those employing manual control) that involved a comparison of control techniques in this type of aircraft.

Hindson, W. S.↗

NASA NTRS1985

PLTTER user's guide

The PLTTER graphics system, which is part of CDDMS is discussed. CDDMS is a comprehensive system for data basing and subsequent plotting of data acquired during wind tunnel tests or from computational flow analyses. The PLTTER is a system which creates report-quality plots of data which is stored on a CDDMS data base. The Requests file system allows plot-controlling information to be arranged in the way which is most appropriate for any application. The PLTTER system features many capabilities which are especially useful when plotting wind tunnel data. The PLTTER offers a variety of page formats, different grid options and parametric curve fitting algorithms, and a powerful legend capability to identify relevant information about individual curves. One or more plots on a page can be suppressed if desired so that an established page format can be maintained. Final plot output may be standard Versatec plots, QMS Laser printer plots, or microfiche.

Barlow, A.↗

DOE OSTI2014

A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity

The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However, the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.

big data↗