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We present a data-driven protocol and a supporting architecture for communication amoung cooperating intelligent agents in real-time diagnostic systems.
Many aspects of space system operations involve continuous control of real time processes. These processes include electrical power system monitoring, prelaunch and ongoing propulsion system health and maintenance, environmental and life support systems, space suit checkout, onboard manufacturing, and vehicle servicing including satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real time processes has been done by trained human experts monitoring telemetry data. However, the long duration of future space missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge based expert control procedures for these space systems.
The NASA Lewis Research Center is developing and evaluating experimental hardware and software systems to help meet future needs for real-time, high-fidelity simulations of air-breathing propulsion systems. Specifically, the real-time multiprocessor simulator project focuses on the use of multiple microprocessors to achieve the required computing speed and accuracy at relatively low cost. Operating systems for such hardware configurations are generally not available. A real time multiprocessor operating system (RTMPOS) that supports a variety of multiprocessor configurations was developed at Lewis. With some modification, RTMPOS can also support various microprocessors. RTMPOS, by means of menus and prompts, provides the user with a versatile, user-friendly environment for interactively loading, running, and obtaining results from a multiprocessor-based simulator. The menu functions are described and an example simulation session is included to demonstrate the steps required to go from the simulation loading phase to the execution phase.
The development of ultra stable optical fiber distribution systems for the dissemination of frequency and timing references is reported. The ultimate design goals for these systems are a frequency stability of 10 to the -17 power for tau or = 100 sec and time stability of + or - 0.1 ns for 1 year and operation over distances or = 30 km. A prototype system is reviewed and progress is discussed.
Two off-line schemes are proposed for the identification of unknown noise covariance matrices Q and R of a discrete-time dynamic system. The first scheme is based on a maximum a posteriori cost function utilizing smoothed state estimates, while the second is based on a maximum likelihood cost function utilizing filtered state estimates. Sensitivity of the cost functions to Q and R is analyzed for the following cases: (1) single-input single-output systems; (2) multiinput single-output systems; and (3) single-input multioutput systems with a diagonal R. Identifiability criteria are presented for the cases considered and demonstrated by examples.
An automated monitoring and diagnostics system (MDS) using virtual real-time software was developed for NASA's High Resolution Microwave Survey (HRMS) Targeted Search System (TSS). The four main tasks required of the MDS were monitoring and recording system health, alerting operators of problems, diagnosing poor system performance, and performing an emergency system shutdown. The MDS was implemented using commercial expert system software tools in addition to interface hardware and software developed on site. The expert system used objects, rules, and schematics in its TSS knowledge representation. The MDS was successfully integrated into the HRMS computer environment, and its performance met or exceeded its requirements.
During early manned spacecraft operations, the primary role of ground telemetry systems was data display to flight controllers. As manned spaceflights have increased in complexity, greater demands have been placed on flight controllers to simultaneously monitor systems and replan systems operations. This has led to interest in automated telemetry monitoring systems to decrease the workload on flight controllers. The Mission Operations Directorate at the Lyndon B. Johnson Space Center has developed a five layer model to integrate various monitoring and analysis technologies such as digital filtering, fault detection algorithms, and expert systems. The paper describes the five layer model and explains how it has been used to guide prototyping efforts at Mission Control. Results from some initial expert systems are presented. The paper also describes the integrated prototype currently under development which implements a real time expert system to assist flight controllers in the Mission Control Center in monitoring Space Shuttle communications systems.
Necessary and sufficient conditions of complete controllability of a class linear, time invariant, delay differential system are presented, and the result is expressed in an algebraic form.
Time dependent small-strain modulus of styrene- butadiene rubber, noting predictability from selected molecular parameters
Time dependent Green function method for premature saturation due to parametric amplification of nonuniform spin wave modes by one and two magnon processes
Timings of occultation events observed at Perth, Australia during the appulse of Uranus to SAO 158687 are presented. In addition to pre- and post-appulse observations of the alpha ring, a search of the data confirms events by the '4', '5', and '6' rings on the pre-appulse side of Venus, and the '5' and beta rings on the post-appulse side. A table of other suspected events obtained from a statistical search of the data down to the same level of significance as the '4', '5', and '6' events is presented. A fairly strong 'event', so far unconfirmed, is noted near the 5:1 Miranda resonance orbit. Examination of the light curves at high time resolution indicates that the alpha ring was, during this aspect, about 10 km in radial extent and about 50% transparent.
As the complexity and expected life-span of modern space systems continue to increase, the need for real-time data monitoring and failure analysis becomes more critical to their successful operation. The DEcision Support SYstem (DESSY) is a joint effort by the Intelligent Systems Branch/ER2 and the Remote Manipulator System (RMS) Section/DF44 to develop an expert system for the monitoring of the Payload Deployment and Retrieval System (PDRS). DESSY users, the RMS flight controllers, are provided with user interface enhancements and automated monitoring of system state (physical orientation) and status (operational health). Currently, a DESSY prototype for the Manipulator Positioning Mechanism (MPM) and Manipulator Retention Latches (MRL) of the PDRS has been developed and successfully demonstrated during the STS-49 and STS-46 missions. Expert systems for monitoring real-time operations must not only accurately represent domain knowledge, but also address the challenges of using unfiltered real-time data as input. This paper describes the methods and design strategies developed to overcome problems with real-time data in the NASA Mission Control Center. Types of data problems addressed are as follows: (1) loss of data; (2) erratic data; and (3) data lags and irregularities during state transition. Methods used to handle data problems include rule disabling for ignoring data when data quality is uncertain, context-sensitive bounded pattern recognition for minimizing incorrect conclusions based on bad data, and graceful recovery through system correction when reliable data returns. This combination of methods with an object-based modular DESSY design assures a robust program capable of lengthy periods of uninterrupted use in operations.
Emerging operations involving Advanced Air Mobility (AAM), such as Urban Air Mobility (UAM), pose a challenge to safety assurance and to accessibility within the National Airspace System (NAS).In particular, the public has a low tolerance for risk in aviation and the current NAS tends to be labor-intensive with limited ability to scale up for UAM. In response to this landscape, NASA is collaborating with industry to define a Concept of Operations (ConOps) for In-time System-Wide Safety Assurance (ISSA) for scalable UAM involving a service-oriented architecture. This architecture focuses safety investments for technological solutions that can overcome safety related barriers for emerging operations. By working with industry, consensus can be reached on desirable system traits that are based on integration and fusion of data and leverage increasingly autonomous and automated systems. These complex systems can identify anomalies, precursors, and trends that together enable more proactive management of operational risks. AAM and UAM elevate the need for risk management in relation to increasing density and heterogeneity of vehicles and operations. Whereas safety in today’s NAS is built on a history of programs and technologies that react to incidents and accidents, AAM presents an opportunity to leverage that experience and its implications and proactively integrate safety into the earliest designs of vehicles and systems. In a perfect world AAM and UAM would not be inherently dangerous but until then ensuring the highest quality of safety requirements is the bridge to mitigating risks.
Recent advances in optimal control have brought design techniques based on optimization of H(2) and H(infinity) norm criteria, closer to be attractive alternatives to single-loop design methods for linear time-variant systems. Significant steps forward in this technology are the deeper understanding of performance and robustness issues of these design procedures and means to perform design trade-offs. However acceptance of the technology is hindered by the lack of convenient design tools to exercise these powerful multivariable techniques, while still allowing single-loop design formulation. Presented is a unique computer tool for designing arbitrary low-order linear time-invarient controllers than encompasses both performance and robustness issues via the familiar H(2) and H(infinity) norm optimization. Application to disturbance rejection design for a commercial transport is demonstrated.
Time Warp Operating System, TWOS, is special purpose computer program designed to support parallel simulation of discrete events. Complete implementation of Time Warp software mechanism, which implements distributed protocol for virtual synchronization based on rollback of processes and annihilation of messages. Supports simulations and other computations in which both virtual time and dynamic load balancing used. Program utilizes underlying resources of operating system. Written in C programming language.
This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.
In recent years, much emphasis has been placed on the Kalman filter to solve on-line estimation problems. Smoothers, which determine state estimates at a certain time t using measurements between 0 and T, have been used primarily in off-line estimation schemes. This paper presents alternative forms of smoothers that can be used for on-line estimation problems. The alternative smoothing algorithms provide state estimates which are more refined than Kalman filtered state estimates. The alternative smoothing algorithms are illustrated in two examples. The first example considers a linear discrete-time system while the second example considers a nonlinear continuous-time system with discrete-time measurements.
Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.