Information Science

A Robustly Stabilizing Model Predictive Control Algorithm

The algorithm can be applied to industrial and automotive systems. A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a recedinghorizon implementation. Given a feasible solution to the finite-horizon optimal control problem at an initial time, resolvability implies the ability to solve the optimal control problem at subsequent times.

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Modeling Evaporation of Drops of Different Kerosenes

One model applies to all three classes of hydrocarbon constituents. A mathematical model describes the evaporation of drops of a hydrocarbon liquid composed of as many as hundreds of chemical species. The model is intended especially for application to any of several types of kerosenes commonly used as fuels. Like evaporating- multicomponent- fuel-drop models described in several previous NASA Tech Briefs articles, the present model invokes the concept of continuous thermodynamics, according to which the chemical composition of the evaporating multicomponent liquid is described by use of a probability distribution function (PDF). However, as described below, the present model is more generally applicable than is its immediate predecessor.

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Bayesian-Augmented Identification of Stars in a Narrow View

An adaptive threshold guides acceptance or rejection of a tentative identification. An algorithm for the identification of stars from a charge-coupled-device (CCD) image of a star field has been extended for use with narrower field-of-view images. Previously, the algorithm had been shown to be effective at a field of view of 8°. This work augments the earlier algorithm using Bayesian decision theory. The new algorithm is shown to be capable of effective star identification down to a field of view of 2°. The algorithm was developed for use in estimating the attitude of a spacecraft and could be used on Earth to help in the identification of stars and other celestial objects for astronomical observations.

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Enhanced Software for Scheduling Space-Shuttle Processing

Prototype software has been upgraded. The Ground Processing Scheduling System (GPSS) computer program is used to develop streamlined schedules for the inspection, repair, and refurbishment of space shuttles at Kennedy Space Center. A scheduling computer program is needed because space-shuttle processing is complex and it is frequently necessary to modify schedules to accommodate unanticipated events, unavailability of specialized personnel, unexpected delays, and the need to repair newly discovered defects. GPSS implements constraint-based scheduling algorithms and provides an interactive scheduling software environment. In response to inputs, GPSS can respond with schedules that are optimized in the sense that they contain minimal violations of constraints while supporting the most effective and efficient utilization of space-shuttle ground processing resources.

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Serial-Turbo-Trellis-Coded Modulation With Rate-1 Inner Code

Coders and decoders for bandwidth- and power-limited systems could be less complex. Serially concatenated turbo codes have been proposed to satisfy requirements for low bit- and word-error rates and for low (in comparison with related previous codes) complexity of coding and decoding algorithms and thus low complexity of coding and decoding circuitry. These codes are applicable to such high-level modulations as octonary phase-shift keying (8PSK) and 16-state quadrature amplitude modulation (16QAM); the signal product obtained by applying one of these codes to one of these modulations is denoted, generally, as "serially concatenated trellis-coded modulation" ("SCTCM"). These codes could be particularly beneficial for communication systems that must be designed and operated subject to limitations on bandwidth and power.

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More About the Phase-Synchroized Enhancement Method

A report presents further details regarding the subject matter of "Phase-Synchronized Enhancement Method for Engine Diagnostics" (MFS-26435), NASA Tech Briefs, Vol. 22, No. 1 (January 1998), page 54. To recapitulate: The phase-synchronized enhancement method (PSEM) involves the digital resampling of a quasi-periodic signal in synchronism with the instantaneous phase of one of its spectral components. This resampling transforms the quasi-periodic signal into a periodic one more amenable to analysis. It is particularly useful for diagnosis of a rotating machine through analysis of vibration spectra that include components at the fundamental and harmonics of a slightly fluctuating rotation frequency. The report discusses the machinery-signal-analysis problem, outlines the PSEM algorithms, presents the mathematical basis of the PSEM, and presents examples of application of the PSEM in some computational simulations.

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Utilizing Expert Knowledge in Estimating Future STS Costs

A method of estimating the costs of future space transportation systems (STSs) involves classical activity-based cost (ABC) modeling combined with systematic utilization of the knowledge and opinions of experts to extend the process-flow knowledge of existing systems to systems that involve new materials and/or new architectures. The expert knowledge is particularly helpful in filling gaps that arise in computational models of processes because of inconsistencies in historical cost data. Heretofore, the costs of planned STSs have been estimated following a "top-down" approach that tends to force the architectures of new systems to incorporate process flows like those of the space shuttles. In this ABC-based method, one makes assumptions about the processes, but otherwise follows a "bottoms up" approach that does not force the new system architecture to incorporate a space-shuttle-like process flow. Prototype software has been developed to implement this method. Through further development of software, it should be possible to extend the method beyond the space program to almost any setting in which there is a need to estimate the costs of a new system and to extend the applicable knowledge base in order to make the estimate.

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