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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

The control networks of Tethys and Dione

Control networks of the Saturnian satellites Tethys and Dione have been established photogrammetrically from pictures taken by the two Voyager spacecraft during their flybys. Coordinates of 110 points on Tethys and 126 points on Dione are listed; selected points are identified on U.S. Geological Survey maps of the satellites, and many are identified by name. Measurements of these points were made on six pictures from Voyager 1 and 21 from Voyager 2 for Tethys, and on 27 pictures from Voyager 1 and one from Voyager 2 for Dione. The longitude systems on the satellites have been defined by craters on their surfaces. The mean radii have been determined as 524 + or - 5 km for Tethys and 559 + or - 5 km for Dione.

Davies, M. E.↗
DOE OSTI2022

Resilient Hierarchical Networked Control Systems: Secure Controls for Critical Locations and at Edge

Integration of information and communication technology (ICT) offers new opportunities in improving the management and operation of critical infrastructures such as power systems as it allows connection of different sensors and control components via a communication network, leading to the so-called networked control systems (NCS). However, the use of open and pervasive ICT such as the Internet or wireless communication technologies comes at a price of making NCS vulnerable to cyber intrusions/attacks which may cause physical damage. Here, this chapter presents control algorithms to ensure resilient and safe operation of NCS under unknown cyberattacks. Specifically, a variant of dynamic watermarking strategies is presented by embedding encoding/decoding components of chaotic signals into the NCS for secure control for critical locations where the measurement/control signals are transmitted to/from the control center via a communication network. In addition, resilient cooperative control algorithms are discussed to ensure safe operation at edge of the NCS which consists of a large number of distributed controllable devices. Several numerical examples are provided to illustrate the proposed control strategies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1994

NCC simulation model. Phase 2: Simulating the operations of the Network Control Center and NCC message manual

The network control center (NCC) provides scheduling, monitoring, and control of services to the NASA space network. The space network provides tracking and data acquisition services to many low-earth orbiting spacecraft. This report describes the second phase in the development of simulation models for the FCC. Phase one concentrated on the computer systems and interconnecting network.Phase two focuses on the implementation of the network message dialogs and the resources controlled by the NCC. Performance measures were developed along with selected indicators of the NCC's operational effectiveness.The NCC performance indicators were defined in terms of the following: (1) transfer rate, (2) network delay, (3) channel establishment time, (4) line turn around time, (5) availability, (6) reliability, (7) accuracy, (8) maintainability, and (9) security. An NCC internal and external message manual is appended to this report.

Benjamin, Norman M.↗
NASA NTRS1992

Robustness of a distributed neural network controller for locomotion in a hexapod robot

A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

Chiel, Hillel J.↗
NASA NTRS1987

The control network of Mars: October 1986

The control network of Mars is composed of Mariner 9 frames which essentially give full coverage of the planet at low resolution. Superimposed on and tied to this network are strips of Viking mapping frames (resolution 100 to 250 m per pixel) which encircle the equator and 60 deg north latitude and multiple longitude ties between these latitude strips. There are multiple ties between these strips and the Viking 1 lander site. In the future another strip will be established at 60 deg south latitude. Because the Viking 1 lander site has been accurately located, the coordinates of points in its vicinity can be determined with an error of less than 100 m relative to an inertial coordinate system.

Davies, Merton E.↗
NASA NTRS1989

Phoebe: A preliminary control network and rotational elements

A preliminary control network for the Saturnian satellite Phoebe was determined based upon 6 distinct albedo features mapped on 16 Voyager 2 images. Using an existing map and an analytical triangulation program which minimized the measurement error, the north pole of Phoebe was calculated to be alpha sub 0 = 355.0 deg + or - 9.6 deg, delta sub 0 = 68.7 deg + or - 7.9 deg, where alpha sub 0, delta sub 0 are standard equatorial coordinates with equinox J2000 at epoch J2000. The prime meridian of Phoebe was computed to be W = 304.7 deg + 930.833872d, where d is the interval in days from JD 2451545.0 TDB.

Colvin, Tim R.↗
NASA NTRS1987

The control networks of the satellites of Jupiter

Geodetic control networks are being computed photogrammetrically for the large satellites of Jupiter, using pictures from the Voyager 1 and 2 encounters. Control points have been identified on the satellites and their coordinates computed by single-block analytical triangulation. The data sets have been converted from the B1950 to the J2000 inertial coordinate system to be compatible with future flight missions.

Davies, Merton E.↗
NASA NTRS1992

NCC Simulation Model: Simulating the operations of the network control center, phase 2

The simulation of the network control center (NCC) is in the second phase of development. This phase seeks to further develop the work performed in phase one. Phase one concentrated on the computer systems and interconnecting network. The focus of phase two will be the implementation of the network message dialogues and the resources controlled by the NCC. These resources are requested, initiated, monitored and analyzed via network messages. In the NCC network messages are presented in the form of packets that are routed across the network. These packets are generated, encoded, decoded and processed by the network host processors that generate and service the message traffic on the network that connects these hosts. As a result, the message traffic is used to characterize the work done by the NCC and the connected network. Phase one of the model development represented the NCC as a network of bi-directional single server queues and message generating sources. The generators represented the external segment processors. The served based queues represented the host processors. The NCC model consists of the internal and external processors which generate message traffic on the network that links these hosts. To fully realize the objective of phase two it is necessary to identify and model the processes in each internal processor. These processes live in the operating system of the internal host computers and handle tasks such as high speed message exchanging, ISN and NFE interface, event monitoring, network monitoring, and message logging. Inter process communication is achieved through the operating system facilities. The overall performance of the host is determined by its ability to service messages generated by both internal and external processors.

Benjamin, Norman M.↗
NASA NTRS1974

Phobos - Control network analysis

Initial analysis of the Mariner 9 high resolution pictures of Phobos surface features has been completed. A control network of 38 landmarks has been established and used to determine the physical size, shape, orientation, libration, and topography properties of Phobos. The results verified the synchronous rotation of Phobos and revealed a libration of approximately 5 deg in the orbit plane of Phobos. A preliminary map of Phobos, based on the control network analysis, is given.

Duxbury, T. C.↗
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
NASA NTRS1985

The Control Networks of the Satellites of Jupiter and Saturn

Geodetic control networks are being computed photogrammetrically for the large satellites of Jupiter and many of the satellites of Saturn using pictures from the Voyager 1 and 2 encounters. Control points have been identified on the satellites and their coordinates computed by single-block analytical triangulations. Contents of data sets for Io, Europa, Ganymede, Callisto, and Rhea are summarized.

Davies, M. E.↗
NASA NTRS1982

A network control concept for the 30/20 GHz communication system baseband processor

The architecture and system design for a satellite-switched TDMA communication system employing on-board processing was developed by Motorola for NASA's Lewis Research Center. The system design is based on distributed processing techniques that provide extreme flexibility in the selection of a network control protocol without impacting the satellite or ground terminal hardware. A network control concept that includes system synchronization and allows burst synchronization to occur within the system operational requirement is described. This concept integrates the tracking and control links with the communication links via the baseband processor, resulting in an autonomous system operational approach.

Sabourin, D. J.↗
NASA NTRS1983

The 1982 control network of Mars

Attention is given to a planet-wide control network of Mars that was computed in September 1982 using a large single-block analytical triangulation with 47,524 measurements of 6853 control points on 1054 Mariner 9 and 757 Viking pictures. In all, 19,139 normal equations were solved, with a resulting standard error of measurement of 18.06 microns. The control points identified by name and letter designation are given, as are the aerographic coordinates of the control points. In addition, the coordinates of the Viking I lander site are given: latitude, 22.480 deg; longitude, 47.962 deg (radius, 3389.32 km). This study expands and updates the previously published network (1978). It is noted that the computation differs in many respects from standard aerial mapping photogrammetric practice. In comparison with aerial mapping photography, the television formats are small and the focal lengths are long; stereo coverage is rare, the scale of the pictures varies greatly, and the residual camera distortions are large.

Davies, M. E.↗
NASA NTRS1991

Space Network Control Conference on Resource Allocation Concepts and Approaches

The results are presented of the Space Network Control (SNC) Conference. In the late 1990s, when the Advanced Tracking and Data Relay Satellite System is operational, Space Network communication services will be supported and controlled by the SNC. The goals of the conference were to survey existing resource allocation concepts and approaches, to identify solutions applicable to the Space Network, and to identify avenues of study in support of the SNC development. The conference was divided into three sessions: (1) Concepts for Space Network Allocation; (2) SNC and User Payload Operations Control Center (POCC) Human-Computer Interface Concepts; and (3) Resource Allocation Tools, Technology, and Algorithms. Key recommendations addressed approaches to achieving higher levels of automation in the scheduling process.

Moe, Karen L.↗
NASA NTRS1987

The control networks of the satellites of Uranus

The present photogrammetric derivation of control networks for the five Uranus satellites Miranda, Ariel, Umbriel, Titania, and Oberon, on the basis of Voyager 2 images, covers the illuminated southern hemisphere of each satellite and respectively yields 103, 52, 43, 46, and 34 coordinate points. It is found that Titania is ellipsoidal, with 241-, 235-, and 232-km radii.In addition, mean radii are determined to be 579 km for Ariel, 586 km for Umbriel, 790 km for Titania, and 762 km for Oberon. Some of the control points used have been identified on the U.S. Geological Survey maps of these satellites.

Davies, Merton E.↗