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At least 1,045 records · Page 58

Algorithms for adaptive stochastic control for a class of linear systems

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

Toda, M.↗

OMEGA timing receiver, design and system test

The design of a two frequency OMEGA Timing Receiver is discussed. The receiver tracks the arrival time of the signals by precise phase matching at the receiving antenna. Provision is made for inserting a propagation delay correction for each signal path. Time is measured as the difference between the zero crossing coincidence of the corrected signals and the local time. This number is displayed on the front panel in microseconds. The receiver can also function as a precise phase tracking receiver for collection of propagation data essential to augmenting the propagation corrections. All phase and time information is made available in a BCD format for flexibility in interfacing with other equipment. Results of preliminary tests using experimental transmissions are given. Preliminary results indicate time may be transferred by this technique to an accuracy of a few microseconds.

Wilson, J. J.↗

Considerations in development of expert systems for real-time space applications

Over the years demand on space systems have been increased tremendously and this trend will continue for the near future. The enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems, and artificial intelligence and expert system concepts have a significant role in space applications. Expert systems could facilitate decision making, improved fault diagnosis and repair, enhanced performance and less reliance on ground support. However, some requirements have to be fulfilled before practical use of flight-worthy expert systems for onboard (and ground) operations. This paper discusses some of the characteristics and important considerations in design, development, implementation and use of expert systems for real-life space applications. Further, it describes a typical life cycle of expert system development and its usage.

Murugesan, S.↗

Time domain desensitized specific optimal system design

A digital computer algorithm for desensitized specific optimal system design for general time-invariant nonlinear systems is presented. The algorithm utilizes a technique of partitioning and uncoupling of the original specific closed-loop system state and sensitivity equations into linear, nonlinear, and control subsystems. Results of the application of the algorithm in the design of a Saturn V Launch Vehicle analog attitude control system and an LST image motion compensation digital controller are given.

Henson, T. F.↗

Demonstrating artificial intelligence for space systems - Integration and project management issues

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

Hack, Edmund C.↗

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Wang, Lui↗

Enhanced Data-Acquisition System

Time-consuming, costly digitization of analog signals on magnetic tape eliminated. Proposed data-acquisition system provides nearly immediate access to data in incoming signals by digitizing and recording them both on magnetic tape and on optical disk. Tape and/or disk later played back to reconstruct signals in analog or digital form for analysis. Of interest in industrial and scientific applications in which necessary to digitize, store, and/or process large quantities of experimental data.

Mustain, Roy W.↗

Fault recovery for real-time, multi-tasking computer system

System and methods for providing a recoverable real time multi-tasking computer system are disclosed. In one embodiment, a system comprises a real time computing environment, wherein the real time computing environment is adapted to execute one or more applications and wherein each application is time and space partitioned. The system further comprises a fault detection system adapted to detect one or more faults affecting the real time computing environment and a fault recovery system, wherein upon the detection of a fault the fault recovery system is adapted to restore a backup set of state variables.

Hess, Richard↗

A TRMM-Based System for Real-Time Quasi-Global Merged Precipitation Estimates

A new processing system has been developed to combine IR and microwave data into 0.25 degree x 0.25 degree gridded precipitation estimates in near-real time over the latitude band plus or minus 50 degrees. Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) precipitation estimates are used to calibrate Special Sensor Microwave/Imager (SSM/I) estimates, and Advanced Microwave Sounding Unit (AMSU) and Advanced Microwave Scanning Radiometer (AMSR) estimates, when available. The merged microwave estimates are then used to create a calibrated IR estimate in a Probability-Matched-Threshold approach for each individual hour. The microwave and IR estimates are combined for each 3-hour interval. Early results will be shown, including typical tropical and extratropical storm evolution and examples of the diurnal cycle. Major issues will be discussed, including the choice of IR algorithm, the approach for merging the IR and microwave estimates, extension to higher latitudes, retrospective processing back to 1999, and extension to the GPCP One-Degree Daily product (for which the authors are responsible). The work described here provides one approach to using data from the future NASA Global Precipitation Measurement program, which is designed to provide Jill global coverage by low-orbit passive microwave satellites every three hours beginning around 2008.

Starr, David OC.↗

System Synchronizes Recordings from Separated Video Cameras

A system of electronic hardware and software for synchronizing recordings from multiple, physically separated video cameras is being developed, primarily for use in multiple-look-angle video production. The system, the time code used in the system, and the underlying method of synchronization upon which the design of the system is based are denoted generally by the term "Geo-TimeCode(TradeMark)." The system is embodied mostly in compact, lightweight, portable units (see figure) denoted video time-code units (VTUs) - one VTU for each video camera. The system is scalable in that any number of camera recordings can be synchronized. The estimated retail price per unit would be about $350 (in 2006 dollars). The need for this or another synchronization system external to video cameras arises because most video cameras do not include internal means for maintaining synchronization with other video cameras. Unlike prior video-camera-synchronization systems, this system does not depend on continuous cable or radio links between cameras (however, it does depend on occasional cable links lasting a few seconds). Also, whereas the time codes used in prior video-camera-synchronization systems typically repeat after 24 hours, the time code used in this system does not repeat for slightly more than 136 years; hence, this system is much better suited for long-term deployment of multiple cameras.

Nail, William↗

GEWEX America Prediction Project (GAPP) Science and Implementation Plan

The purpose of this Science and Implementation Plan is to describe GAPP science objectives and the activities required to meet these objectives, both specifically for the near-term and more generally for the longer-term. The GEWEX Americas Prediction Project (GAPP) is part of the Global Energy and Water Cycle Experiment (GEWEX) initiative that is aimed at observing, understanding and modeling the hydrological cycle and energy fluxes at various time and spatial scales. The mission of GAPP is to demonstrate skill in predicting changes in water resources over intraseasonal-to-interannual time scales, as an integral part of the climate system.

TIME SCALES↗

Evaluating Performance of UAS Detect-And-Avoid System Using a Fast-Time Simulation Tool

Most unmanned aircraft systems will be required to be equipped with a Detect-and-Avoid (DAA) system. The surveillance performance of the DAA system to detect and track intruder aircraft will depend on the encounter geometries that unmanned aircraft are expected to have with other aircraft in the airspace. The performance of DAA alerting and avoidance system is also dependent on the timeliness of alerting for UAS pilots to give a sufficient time to determine and command a resolution maneuver to avoid well clear separation violations. This presentation introduces general background of UAS DAA systems and concept of well clear separation standard to satisfy see and avoid regulations. The presentation shows the several UAS mission profiles and analysis of the encounter geometries that were simulated using historical VFR traffic data and some proposed UAS missions. This presentation introduces several potential metrics for evaluating the performance of a DAA system and shows the results that measured through fast-time simulation with traffic scenarios that include NAS-wide VFR manned aircraft and IFR UAS flights. At the end, some research areas will be briefly discussed.

UAS↗

Implementation of a General Real-Time Visual Anomaly Detection System Via Soft Computing

The intelligent visual system detects anomalies or defects in real time under normal lighting operating conditions. The application is basically a learning machine that integrates fuzzy logic (FL), artificial neural network (ANN), and generic algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation to separate the object being tested from the background, preprocesses the image using fuzzy reasoning, performs the final segmentation using fuzzy reasoning techniques to retrieve regions with potential anomalies or defects, and finally retrieves them using a learning model built via ANN and GA techniques. FL provides a powerful framework for knowledge representation and overcomes uncertainty and vagueness typically found in image analysis. ANN provides learning capabilities, and GA leads to robust learning results. An application prototype currently runs on a regular PC under Windows NT, and preliminary work has been performed to build an embedded version with multiple image processors. The application prototype is being tested at the Kennedy Space Center (KSC), Florida, to visually detect anomalies along slide basket cables utilized by the astronauts to evacuate the NASA Shuttle launch pad in an emergency. The potential applications of this anomaly detection system in an open environment are quite wide. Another current, potentially viable application at NASA is in detecting anomalies of the NASA Space Shuttle Orbiter's radiator panels.

Dominguez, Jesus A.↗