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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Real Time Data System (RTDS)

Lessons learned from operational real time expert systems are examined. The basic system architecture is discussed. An expert system is any software that performs tasks to a standard that would normally require a human expert. An expert system implies knowledge contained in data rather than code. And an expert system implies the use of heuristics as well as algorithms. The 15 top lessons learned by the operation of a real time data system are presented.

Muratore, John F.↗
NASA NTRS1994

A performance analysis method for distributed real-time robotic systems: A case study of remote teleoperation

Robot coordination and control systems for remote teleoperation applications are by necessity implemented on distributed computers. Modeling and performance analysis of these distributed robotic systems is difficult, but important for economic system design. Performance analysis methods originally developed for conventional distributed computer systems are often unsatisfactory for evaluating real-time systems. The paper introduces a formal model of distributed robotic control systems; and a performance analysis method, based on scheduling theory, which can handle concurrent hard-real-time response specifications. Use of the method is illustrated by a case of remote teleoperation which assesses the effect of communication delays and the allocation of robot control functions on control system hardware requirements.

Lefebvre, D. R.↗
NASA NTRS1991

Robustness analysis of multirate and periodically time varying systems

A new method for analyzing the stability and robustness of multirate and periodically time varying systems is presented. It is shown that a multirate or periodically time varying system can be transformed into an equivalent time invariant system. For a SISO system, traditional gain and phase margins can be found by direct application of the Nyquist criterion to this equivalent time invariant system. For a MIMO system, structured and unstructured singular values can be used to determine the system's robustness. The limitations and implications of utilizing this equivalent time invariant system for calculating gain and phase margins, and for estimating robustness via singular value analysis are discussed.

Berg, Martin C.↗
NASA NTRS1978

Lectures on algebraic system theory: Linear systems over rings

The presentation centers on four classes of systems that can be treated as linear systems over a ring. These are: (1) discrete-time systems over a ring of scalars such as the integers; (2) continuous-time systems containing time delays; (3) large-scale discrete-time systems; and (4) time-varying discrete-time systems.

Kamen, E. W.↗
NASA NTRS1988

Effects of computing time delay on real-time control systems

The reliability of a real-time digital control system depends not only on the reliability of the hardware and software used, but also on the speed in executing control algorithms. The latter is due to the negative effects of computing time delay on control system performance. For a given sampling interval, the effects of computing time delay are classified into the delay problem and the loss problem. Analysis of these two problems is presented as a means of evaluating real-time control systems. As an example, both the self-tuning predicted (STP) control and Proportional-Integral-Derivative (PID) control are applied to the problem of tracking robot trajectories, and their respective effects of computing time delay on control performance are comparatively evaluated. For this example, the STP (PID) controller is shown to outperform the PID (STP) controller in coping with the delay (loss) problem.

Shin, Kang G.↗
NASA NTRS1987

Use of a FORTH-based PROLOG for real-time expert systems. 1: Spacelab life sciences experiment application

A real-time expert system is being developed to serve as the astronaut interface for a series of Spacelab vestibular experiments. This expert system is written in a version of Prolog that is itself written in Forth. The Prolog contains a predicate that can be used to execute Forth definitions; thus, the Forth becomes an embedded real-time operating system within the Prolog programming environment. The expert system consists of a data base containing detailed operational instructions for each experiment, a rule base containing Prolog clauses used to determine the next step in an experiment sequence, and a procedure base containing Prolog goals formed from real-time routines coded in Forth. In this paper, we demonstrate and describe the techniques and considerations used to develop this real-time expert system, and we conclude that Forth-based Prolog provides a viable implementation vehicle for this and similar applications.

Paloski, William H.↗
NASA NTRS1972

Computation of optimal output-feedback compensators for linear time-invariant systems

The control of linear time-invariant systems with respect to a quadratic performance criterion was considered, subject to the constraint that the control vector be a constant linear transformation of the output vector. The optimal feedback matrix, f*, was selected to optimize the expected performance, given the covariance of the initial state. It is first shown that the expected performance criterion can be expressed as the ratio of two multinomials in the element of f. This expression provides the basis for a feasible method of determining f* in the case of single-input single-output systems. A number of iterative algorithms are then proposed for the calculation of f* for multiple input-output systems. For two of these, monotone convergence is proved, but they involve the solution of nonlinear matrix equations at each iteration. Another is proposed involving the solution of Lyapunov equations at each iteration, and the gradual increase of the magnitude of a penalty function. Experience with this algorithm will be needed to determine whether or not it does, indeed, possess desirable convergence properties, and whether it can be used to determine the globally optimal f*.

Platzman, L. K.↗