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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids

A spacecraft guidance, navigation, and control (GN&C) system is needed to enable a spacecraft to descend to a surface, take a sample using a touch-and-go (TAG) sampling approach, and then safely ascend. At the time of this reporting, a flyable GN&C system that can accomplish these goals is beyond state of the art. This article describes AutoGNC, which is a GN&C system capable of addressing these goals, which has recently been developed and demonstrated to a maturity TRL-5-plus. The AutoGNC solution matures and integrates two previously existing JPL capabilities into a single unified GN&C system. The two capabilities are AutoNAV and GREX. AutoNAV is JPL s current flight navigation system, and is fairly mature with respect to flybys and rendezvous with small bodies, but is lacking capability for close surface proximity operations, sampling, and contact. G-REX is a suite of low-TRL algorithms and capabilities that enables spacecraft operations in close surface proximity and for performing sampling/contact. The development and integration of AutoNAV and G-REX components into AutoGNC provides a single, unified GN&C capability for addressing the autonomy, close-proximity, and sampling/contact aspects of small-body sample return missions. AutoGNC is an integrated capability comprising elements that were developed separately. The main algorithms and component capabilities that have been matured and integrated are autonomy for near-surface operations, terrain-relative navigation (TRN), real-time image-based feedback guidance and control, and six degrees of freedom (6DOF) control of the TAG sampling event. Autonomy is achieved based on an AutoGNC Executive written in Virtual Machine Language (VML) incorporating high-level control, data management, and fault protection. In descending to the surface, the AutoGNC system uses camera images to determine its position and velocity relative to the terrain. This capability for TRN leverages native capabilities of the original AutoNAV system, but required advancements that integrate the separate capabilities for shape modeling, state estimation, image rendering, defining a database of onboard maps, and performing real-time landmark recognition against the stored maps. The ability to use images to guide the spacecraft requires the capability for image-based feedback control. In Auto- GNC, navigation estimates are fed into an onboard guidance and control system that keeps the spacecraft guided along a desired path, as it descends towards its targeted landing or sampling site. Once near the site, AutoGNC achieves a prescribed guidance condition for TAG sampling (position/orientation, velocity), and a prescribed force profile on the sampling end-effector. A dedicated 6DOF TAG control then implements the ascent burn while recovering from sampling disturbances and induced attitude rates. The control also minimizes structural interactions with flexible solar panels and disallows any part of the spacecraft from making contact with the ground (other than the intended end-effector).

Carson, John M.↗
NASA NTRS2005

NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. Also the propulsion systems required to enable the NASA (National Aeronautics and Space Administration) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch at NASA Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Source record↗
NASA NTRS1992

Expert systems for automated maintenance of a Mars oxygen production system

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Huang, Jen-Kuang↗
NASA NTRS2013

AGATE: Adversarial Game Analysis for Tactical Evaluation

AGATE generates a set of ranked strategies that enables an autonomous vehicle to track/trail another vehicle that is trying to break the contact using evasive tactics. The software is efficient (can be run on a laptop), scales well with environmental complexity, and is suitable for use onboard an autonomous vehicle. The software will run in near-real-time (2 Hz) on most commercial laptops. Existing software is usually run offline in a planning mode, and is not used to control an unmanned vehicle actively. JPL has developed a system for AGATE that uses adversarial game theory (AGT) methods (in particular, leader-follower and pursuit-evasion) to enable an autonomous vehicle (AV) to maintain tracking/ trailing operations on a target that is employing evasive tactics. The AV trailing, tracking, and reacquisition operations are characterized by imperfect information, and are an example of a non-zero sum game (a positive payoff for the AV is not necessarily an equal loss for the target being tracked and, potentially, additional adversarial boats). Previously, JPL successfully applied the Nash equilibrium method for onboard control of an autonomous ground vehicle (AGV) travelling over hazardous terrain.

Huntsberger, Terrance L.↗
NASA NTRS1992

Experiments in Nonlinear Adaptive Control of Multi-Manipulator, Free-Flying Space Robots

Sophisticated robots can greatly enhance the role of humans in space by relieving astronauts of low level, tedious assembly and maintenance chores and allowing them to concentrate on higher level tasks. Robots and astronauts can work together efficiently, as a team; but the robot must be capable of accomplishing complex operations and yet be easy to use. Multiple cooperating manipulators are essential to dexterity and can broaden greatly the types of activities the robot can achieve; adding adaptive control can ease greatly robot usage by allowing the robot to change its own controller actions, without human intervention, in response to changes in its environment. Previous work in the Aerospace Robotics Laboratory (ARL) have shown the usefulness of a space robot with cooperating manipulators. The research presented in this dissertation extends that work by adding adaptive control. To help achieve this high level of robot sophistication, this research made several advances to the field of nonlinear adaptive control of robotic systems. A nonlinear adaptive control algorithm developed originally for control of robots, but requiring joint positions as inputs, was extended here to handle the much more general case of manipulator endpoint-position commands. A new system modelling technique, called system concatenation was developed to simplify the generation of a system model for complicated systems, such as a free-flying multiple-manipulator robot system. Finally, the task-space concept was introduced wherein the operator's inputs specify only the robot's task. The robot's subsequent autonomous performance of each task still involves, of course, endpoint positions and joint configurations as subsets. The combination of these developments resulted in a new adaptive control framework that is capable of continuously providing full adaptation capability to the complex space-robot system in all modes of operation. The new adaptive control algorithm easily handles free-flying systems with multiple, interacting manipulators, and extends naturally to even larger systems. The new adaptive controller was experimentally demonstrated on an ideal testbed in the ARL-A first-ever experimental model of a multi-manipulator, free-flying space robot that is capable of capturing and manipulating free-floating objects without requiring human assistance. A graphical user interface enhanced the robot usability: it enabled an operator situated at a remote location to issue high-level task description commands to the robot, and to monitor robot activities as it then carried out each assignment autonomously.

Chen, Vincent Wei-Kang↗
NASA NTRS2017

Requirements for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service. Communications, Navigation and Surveillance (CNS) requirements must be developed in order to establish a CNS architecture supporting Unmanned Air Systems integration in the National Air Space (UAS in the NAS). These requirements must address cybersecurity, future communications, satellite-based navigation APNT, and scalable surveillance and situational awareness. CNS integration, consolidation and miniaturization requirements are also important to support the explosive growth in small UAS deployment. Air Traffic Management (ATM) must also be accommodated to support critical Command and Control (C2) for Air Traffic Controllers (ATC). This document therefore presents UAS CNS requirements that will guide the architecture.

Templin, Fred↗
NASA NTRS1983

A fault tolerant design for autonomous attitude control of the DSCS-III communication satellite

The first of a new series of satellites, which will provide the principal elements in the Defense Space Communications System (DSCS), was launched on Oct. 31, 1982. This satellite, DSCS-III, is part of a system which will consist of super-high frequency communications satellites in synchronous, equatorial orbits, continuously operating in four widely separate geographic regions. The DSCS-III is designed both to maintain critical communications in the presence of an electronic jamming threat and to survive nuclear radiation exposure. The results of the present investigation are to provide a basis for the design of a spacecraft tolerant of on-board failures, survivable against external threats, and capable of performing its mission autonomously for periods as long as six months.

Matijevic, J.↗
NASA NTRSDate not supplied

Autonomous Control for Arbitrary Thruster Configurations and Mass Properties in Special Euclidean Group SE(3)

Most current methods for determining maneuvers and thrust firing sequences depend on explicit and predetermined commands generated by a combination of on-board systems and ground-based human-in-the-loop methods. For spacecraft and space structures with changing mass properties and thruster configurations, such as the Deep Space Gateway as it changes configurations throughout its lifetime, determining these commands can be time-consuming and computationally intensive. However, recent work within the Lie GroupSE (3) has offered ways of autonomously determining the location, power, precision, and capabilities of thrusters in any arbitrary position. Furthermore, a method for determining thruster firing sequences based on an arbitrary control input (both translational and rotational in a coupled, 6-element vector) and arbitrary thruster configurations has also recently been developed. When combining these methods, any spacecraft with any mass properties and thruster configurations can be understood in terms of controllability limits and thruster firing sequences can be generated quickly and with low computational load, thus extending the autonomous capabilities of deep space missions. In this work, this method is presented and explored in terms of computational load, robustness in the presence of uncertainty, and overall performance. The capabilities of this method are also examined in the case of the Deep Space Gateway both in fully controllable configurations and uncontrollable configurations.

Control↗
NASA NTRS1990

Publications of the NASA Controlled Ecological Life Support System (CELSS) Program, 1979-1989

Publications of research sponsored by the NASA Controlled Ecological Life Support System (CELSS) Program from 1979 to 1989 are listed. The CELSS Program encompasses research and technology with the goal of developing an autonomous bioregenerative life support system that continually recycles the solid, liquid, and gaseous materials essential for human life. The bibliography is divided into four major subject areas: food production, nutritional requirements, waste management, and systems management and control.

Wallace, Janice S.↗
NASA NTRSDate not supplied

Autonomous Control for Arbitrary Thruster Configurations and Mass Properties in Special Euclidean Group SE(3)

Most current methods for determining maneuvers and thrust firing sequences depend on explicit and predetermined commands generated by a combination of on-board systems and ground-based human-in-the-loop methods. For spacecraft and space structures with changing mass properties and thruster configurations, such as the Deep Space Gateway as it changes configurations throughout its lifetime, determining these commands can be time-consuming and computationally intensive. However, recent work within the Lie group SE(3) has offered ways of autonomously determining the location, power, precision, and capabilities of thrusters in any arbitrary position. Furthermore, a method for determining thruster firing sequences based on an arbitrary control input (both translational and rotational in a coupled, 6-element vector) and arbitrary thruster configurations has also recently been developed. When combining these methods, any spacecraft with any mass properties and thruster configurations can be understood in terms of controllability limits and thruster firing sequences can be generated quickly and with low computational load, thus extending the autonomous capabilities of deep space missions. In this work, this method is presented and explored in terms of convergence time to the desired pose. The capabilities of this method are also examined in the case of the Deep Space Gateway both in fully controllable configurations and uncontrollable configurations.

SE(3)↗
DOE OSTI2018

Security Evaluation of Two Intrusion Detection Systems in Smart Grid SCADA Environment

The increased complexity and interconnectivity of SCADA infrastructure in the power system have exposed it to the multitude of vulnerabilities. There is a growing emphasis towards developing an efficient intrusion detection system (IDS) to strengthen the security of the SCADA control system. This is a research-in-progress paper which presents the application of two anomaly-based intrusion detection systems (AIDS) in detecting the stealthy cyber-attack on the SCADA control system. We have applied the IDS tools Snort and Bro, in designing the IDS and later, compared their performances in terms of detection rate and latency in the alert packets with a motive of selecting better IDS for the SCADA security. Specifically, the timing-based rule is applied to identify the malicious packets based on the high temporal frequency in the network traffic. For the case study, we have implemented the SCADA based protection scheme which performs an autonomous protection to mitigate the system disturbances. We first implemented the stealthy cyber-attack which compromised the SCADA controller followed by data integrity attack on the system generator. Next, we perform the impact analysis during the attack followed by performance evaluation of IDS tools. Our experimental results show that the IDS tools are efficient in detecting cyber-attacks within an acceptable time frame for different sizes of network packets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRS2011

A Multifunctional Coating for Autonomous Corrosion Control

Nearly all metals and their alloys are subject to corrosion that causes them to lose their structural integrity or other critical functionality. Protective coatings are the most commonly used method of corrosion control. However, progressively stricter environmental regulations have resulted in the ban of many commercially available corrosion protective coatings due to the harmful effects of their solvents or corrosion inhibitors. This work concerns the development of a multifunctional smart coating for the autonomous control of corrosion. This coating is being developed to have the inherent ability to detect the chemical changes associated with the onset of corrosion and respond autonomously to indicate it and control it. The multi-functionality of the coating is based on microencapsulation technology specifically designed for corrosion control applications. This design has, in addition to all the advantages of existing microcapsulation designs, the corrosion controlled release function that triggers the delivery of corrosion indicators and inhibitors on demand, only when and where needed. Microencapsulation of self-healing agents for autonomous repair of mechanical damage to the coating is also being pursued. Corrosion indicators, corrosion inhibitors, as well as self-healing agents, have been encapsulated and dispersed into several paint systems to test the corrosion detection, inhibition, and self-healing properties of the coating. Key words: Corrosion, coating, autonomous corrosion control, corrosion indication, corrosion inhibition, self-healing coating, smart coating, multifunctional coating, microencapsulation.

Calle, Luz M.↗
NASA NTRS2016

HSI in NASA: From Research to Implementation

As NASA plans to send human explorers beyond low Earth orbit, onward to Mars and other destinations in the solar system, there will be new challenges to address in terms of HSI. These exploration missions will be quite different from the current and past missions such as Apollo, Shuttle, and International Space Station. The exploration crew will be more autonomous from ground mission control with delayed, and at times, no communication. They will have limited to no resupply for much longer mission durations. Systems to deliver and support extended human habitation at these destinations are extremely complex and unique, presenting new opportunities to employ HSI practices. In order to have an effective and affordable HSI implementation, both research and programmatic efforts are required. Currently, the HSI-related research at NASA is primarily in the area of space human factors and habitability. The purpose is to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration beyond low Earth orbit, and update standards, requirements, and processes to verify and validate these requirements. In addition, HSI teams are actively engaged in technology development and demonstration efforts to influence the mission architecture and next-generation vehicle design. Finally, appropriate HSI references have been added to NASA' s systems engineering documentation, and an HSI Practitioner's Guide has been published to help design engineers consider HSI early and continuously in the acquisition process. These current and planned HSI-related activities at NASA will be discussed in this panel.

Whitmore, Mihriban↗
NASA NTRS2021

Part II: FY20 CIF Annual Report - LAPS: Lunar Autonomous Positioning System

This project concerns construction of an orbital and ground resource network that provides Position, Navigation, and Timing (PNT) services for lunar surface operations. While functionally similar to Global Navigation Satellite Systems (GNSS) for Earth, this system will instead build an automated PNT framework utilizing limited infrastructure on board orbiting assets along with a controlled number of highly accurate assets, or anchor nodes. The goal is to use advanced algorithms to autonomously coordinate on demand or as needed asset participation to achieve orbit determination and time synchronization of accuracy sufficient for end-user localization. Other proposed lunar PNT solutions, such as weak signal GPS, will not meet many mission localization requirements without additional user INS augmentation and a dedicated GNSS constellation would require prohibitive infrastructure development. This proposed effort, the Lunar Autonomous Positioning System (LAPS), instead offers a design that could be deployed in the near term and is facilitated by accessible hardware technology.

Kelley Hashemi↗
DOE OSTI2018

Coordinated Use of Smart Inverters with Legacy Voltage Regulating Devices in Distribution Systems with High Distributed PV Penetration — Increase CVR Energy Savings

This paper studies the coordinated use of smart inverters with legacy voltage regulating devices to help increase the energy savings from conservation voltage reduction (CVR) in distribution systems with high photovoltaic penetration. Two voltage optimization algorithms are developed to evaluate the CVR benefit by considering two types of smart inverter functions: aggregated reactive power control and autonomous volt/VAR control. In each algorithm, smart inverters are coordinately controlled with the operation of legacy voltage regulating devices including load tap changers and capacitor banks. Both algorithms are tested on representative utility distribution system models. In conclusion, simulation results demonstrate that the proposed algorithms can achieve around 1.8-3.6% energy savings when only using legacy voltage regulating devices and an additional 0.3-0.9% when adding smart inverters.

14 SOLAR ENERGY↗
DOE OSTI2016

Photovoltaic Impact Assessment of Smart Inverter Volt-VAR Control on Distribution System Conservation Voltage Reduction and Power Quality

This report presents an impact assessment study of distributed photovoltaic (PV) with smart inverter Volt-VAR control on conservation voltage reduction (CVR) energy savings and distribution system power quality. CVR is a methodology of flattening and lowering a distribution system voltage profile in order to conserve energy. Traditional CVR relies on operating utility voltage regulators and switched capacitors. However, with the increased penetration of distributed PV systems, smart inverters provide the new opportunity to control local voltage and power factor by regulating the reactive power output, leading to a potential increase in CVR energy savings. This report proposes a methodology to implement CVR scheme by operating voltage regulators, capacitors, and autonomous smart inverter Volt-VAR control in order to achieve increased CVR benefit. Power quality is an important consideration when operating a distribution system, especially when implementing CVR. It is easy to measure the individual components that make up power quality, but a comprehensive method to incorporate all of these values into a single score has yet to be undertaken. As a result, this report proposes a power quality scoring mechanism to measure the relative power quality of distribution systems using a single number, which is aptly named the 'power quality score' (PQS). Both the CVR and PQS methodologies were applied to two distribution system models, one obtained from the Hawaiian Electric Company (HECO) and another obtained from Pacific Gas and Electric (PG&E). These two models were converted to the OpenDSS platform using previous model conversion tools that were developed by NREL. Multiple scenarios including various PV penetration levels and smart inverter densities were simulated to analyze the impact of smart inverter Volt-VAR support on CVR energy savings and feeder power quality. In order to analyze the CVR benefit and PQS, an annual simulation was conducted for each scenario.

14 SOLAR ENERGY↗