Search NASA⌕ Search

SEARCH · Search NASA

Results for “Markov”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

Improvement of observer/Kalman filter identification (OKID) by residual whitening

This paper presents a time-domain method to identify a state space model of a linear system and its corresponding observer/Kalman filter from a given set of general input-output data. The identified filter has the properties that its residual is minimized in the least squares sense, orthogonal to the time-shifted versions of itself, and to the given input-output data sequence. The connection between the state space model and a particular auto-regressive moving average description of a linear system is made in terms of the Kalman filter and a deadbeat gain matrix. The procedure first identifies the Markov parameters of an observer system, from which a state space model of the system and the filter gain are computed. The developed procedure is shown to improve results obtained by an existing observer/Kalman filter identification method, which is based on an auto-regressive model without the moving average terms. Numerical and experimental results are presented to illustrate the proposed method.

Phan, Minh↗

On-line identification of forward/inverse systems for adaptive control applications

The paper is concerned with the on-line identification of system Markov parameters using observers. Two types of parameters are sought: the forward system parameters, which provide estimates of the outputs for given inputs, and inverse system parameters, which provide estimates of inputs for given outputs. A procedure is proposed which uses the inverse system to generate commands that produce a desired system response. The feasibility of the procedure is demonstrated using test results from an implementation of a truss structure fitted with piezoelectric actuators and collocated strain gauges.

Horta, Lucas G.↗

SO2 on Venus: A final cross-calibration with Pioneer Venus

In our previous report, we noted that we had successfully completed all of the IUE observations which were proposed. A total of 7 Venus spectra were obtained. In the present reporting period, essentially all of the associated data reduction and analysis activities were completed, and Drs. Stern, Barker, and Na met to collaborate on data interpretation. The model atmosphere used in this analysis is similar to the one used in the analysis of the Pioneer Venus observations (Esposito, et al. 1979, 1988) and the previous IUE observations (Na, et al. 1990). In this model, sulfuric acid aerosols with a radius of about 1 micron are mixed uniformly with Rayleigh scattering gases throughout the cloud layer. There are two wavelength-independent absorbers. First, the aerosols are assumed to have a single scattering albedo of 0.98, and second a pure absorbing layer with an optical depth of 0.2 is added at an altitude of 75 mbar. The variable parameters in this model are the mixing ratios of SO2 at the cloud top (40 mbar level), and the scale height of SO2 at the same altitude. Model spectra were calculated using a radiative transfer code utilizing a Markov Chain method. Each model calculation takes into account the multiple scattering and the vertical inhomogeneity of the atmosphere. We reported those initial results at the 1992 meeting of the AAS Division of Planetary Sciences (Barker, Stern, and Na 1992) The important finding we have reached is that the 1991 IUE observations indicate that the long-term decline in Venus SO2 abundance has either halted or reversed. Our simultaneous groundbased measurements made on the McDonald Observatory 2.7 m corroborate this result. We are now preparing a paper describing these IUE results for publication in Icarus. With the IUE results reduced, we are also beginning a project to compare the 1991 IUE results to Pioneer Venus UV spectra made on the same dates.

Stern, S. Alan↗

Availability analysis of the traveling-wave maser amplifiers in the deep space network. Part 1: The 70-meter antennas

The results of the reliability and availability analyses of the individual S- and X-band traveling-wave maser (TWM) assemblies and their operational configurations in the 70-meter antennas of NASA's Deep Space Network (DSN) are described. For the period 1990 through 1991, the TWM availability parameters for the Telemetry Data System are: mean time between failures (MTBF), 930 hr; mean time to restore services (MTTRS), 1.4 hr; and the average availability, 99.85 percent. In previously published articles, the performance analysis of the TWM assemblies was confined to the determination of the parameters specified above. However, as the mean down time (MDT) for the repair of TWM's increases, the levels of the TWM operational availabilities and MTTRS are adversely affected. A more comprehensive TWM availability analysis is presented to permit evaluation of both MTBF and MDT effects. Performance analysis of the TWM assemblies, based on their station monthly failure reports, indicates that the TWM's required MTBF and MDT levels of 3000 hr and 36 to 48 hr, respectively, have been achieved by the TWM's only at the Canberra Deep Space Station (DSS 43). The Markov Process technique is employed to develop suitable availability measures for the S- and X-band TWM configurations when each is operated in a two-assembly standby mode. The derived stochastic expressions allow for the evaluation of those configurations' simultaneous availability for the Antenna Microwave Subsystem. The application of these expressions to demonstrate the impact of various levels of TWM maintainability (or MDT) on their configurations' operational availabilities is presented for each of the 70-m antenna stations.

Issa, T. N.↗

Data availability and data archeology from the former Soviet Union

Acquisition of data on the ocean is believed to start in 1872, when the Royal Navy ship 'Challenger' performed oceanographic stations in its round-world voyage (1872-1876). The first oceanographic studies of the World Ocean refer to the 80s second half of the 19th century. During its round-world expedition 'Vityaz' (1886-1889) headed by S.O. Markov, performed hydrological measurements in the Baltic Sea, Atlantic and Pacific Oceans. According to information available the regular expedition observations (prototype of future complex international program on the ocean research) started in the second half of 80s last century under the auspice of Kiev commission for exploration of German Seas. Systematic hydrological observations were organized by Hydrographic Department of Russia in 1876-1879 according to the program similar to the Kiev one and observations were regularly made by ships of custom service over the Russian area of the Baltic Sea. The increasing demands in oceanographic data contributed to considerable progress in exploration of the World Ocean during current century whole tendency to increase and become more significant has been observed for the last 30-40 years. Most probably various expeditions which were carried out during International Geophysical Year in different regions of the World Ocean are to be reference point in performing intensive oceanographic observations of Marine environment. In the former USSR oceanographic observations are made by research and hydrographic vessels, commercial and fishery ships as well as oil production platforms, coastal hydrometeorological station and other observing platforms. Oceanographic observations data, available from main sources of information on the ocean-research vessels, are also considered in the report.

Sychev, Yuri↗

Reliability studies of integrated modular engine system designs

A study was performed to evaluate the reliability of Integrated Modular Engine (IME) concepts. Comparisons were made between networked IME systems and non-networked discrete systems using expander cycle configurations. Both redundant and non-redundant systems were analyzed. Binomial approximation and Markov analysis techniques were employed to evaluate total system reliability. In addition, Failure Modes and Effects Analyses (FMEA), Preliminary Hazard Analyses (PHA), and Fault Tree Analysis (FTA) were performed to allow detailed evaluation of the IME concept. A discussion of these system reliability concepts is also presented.

Hardy, Terry L.↗

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance.

Iyer, Ravishankar, K.↗

Eigenvalue error analysis of viscously damped structures using a Ritz reduction method

The efficient solution of the eigenvalue problem that results from inserting passive dampers with variable stiffness and damping coefficients into a structure is addressed. Eigenanalysis of reduced models obtained by retaining a number of normal modes augmented with Ritz vectors corresponding to the static solutions resulting from the load patterns introduced by the dampers has been empirically shown to yield excellent approximations to the full eigenvalue problem. An analysis of this technique in the case of a single damper is presented. A priori and a posteriori error estimates are generated and tested on numerical examples. Comparison theorems with modally truncated models and a Markov parameter matching reduced-order model are derived. These theorems corroborate the heuristic that residual flexibility methods improve low-frequency approximation of the system. The analysis leads to other techniques for eigenvalue approximation. Approximate closed-form solutions are derived that include a refinement to eigenvalue derivative methods for approximation. An efficient Newton scheme is also developed. A numerical example is presented demonstrating the effectiveness of each of these methods.

Chu, Cheng-Chih↗

Substructure system identification and synthesis

This paper explores the possibility of performing system identification at the substructure level and then synthesizing the results to obtain a mathematical model for the assembled structure. The study here shows that in order to enforce interface compatibility and equilibrium conditions to the substructure test data, it is necessary to place collocated actuator/sensor pair at every interface degree-of-freedom. Procedures for assembling substructure transfer function data, substructure state-space models, and substructure Markov parameters are presented. Testing difficulties and possible solutions are also discussed. A numerical simulation example is included to illustrate the proposed substructure synthesis methods.

Su, Tzu-Jeng↗

Reliability studies of Integrated Modular Engine system designs

A study was performed to evaluate the reliability of Integrated Modular Engine (IME) concepts. Comparisons were made between networked IME systems and non-networked discrete systems using expander cycle configurations. Both redundant and non-redundant systems were analyzed. Binomial approximation and Markov analysis techniques were employed to evaluate total system reliability. In addition, Failure Modes and Effects Analyses (FMEA), Preliminary Hazard Analyses (PHA), and Fault Tree Analysis (FTA) were performed to allow detailed evaluation of the IME concept. A discussion of these system reliability concepts is also presented.

Hardy, Terry L.↗

Frequency domain system identification methods - Matrix fraction description approach

This paper presents the use of matrix fraction descriptions for least-squares curve fitting of the frequency spectra to compute two matrix polynomials. The matrix polynomials are intermediate step to obtain a linearized representation of the experimental transfer function. Two approaches are presented: first, the matrix polynomials are identified using an estimated transfer function; second, the matrix polynomials are identified directly from the cross/auto spectra of the input and output signals. A set of Markov parameters are computed from the polynomials and subsequently realization theory is used to recover a minimum order state space model. Unevenly spaced frequency response functions may be used. Results from a simple numerical example and an experiment are discussed to highlight some of the important aspect of the algorithm.

Horta, Luca G.↗

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

Rignot, E.↗

Performance evaluation of automated manufacturing systems using generalized stochastic Petri Nets

The main objective of this research is to develop a generic modeling methodology with a flexible and modular framework to aid in the design and performance evaluation of integrated manufacturing systems using a unified model. After a thorough examination of the available modeling methods, the Petri Net approach was adopted. The concurrent and asynchronous nature of manufacturing systems are easily captured by Petri Net models. Three basic modules were developed: machine, buffer, and Decision Making Unit. The machine and buffer modules are used for modeling transfer lines and production networks. The Decision Making Unit models the functions of a computer node in a complex Decision Making Unit Architecture. The underlying model is a Generalized Stochastic Petri Net (GSPN) that can be used for performance evaluation and structural analysis. GSPN's were chosen because they help manage the complexity of modeling large manufacturing systems. There is no need to enumerate all the possible states of the Markov Chain since they are automatically generated from the GSPN model.

Al-Jaar, Robert Y.↗

Determining state-space models from sequential output data

This talk focuses on the determination of state-space models for large space systems using only the output data. The output data could be generated by the unknown or deliberate initial conditions of the space structure in question. We shall review some relevant fundamental work on the state-space modeling of sequential output data that is potentially applicable to large space structures. If formulated in terms of some generalized Markov parameters, this approach is in some sense similar to, but much simpler than, the Juang-Pappa Eigensystem Realization Algorithm (ERA) and the Ho-Kalman construction procedure.

Lin, Jiguan Gene↗

A measurement-based performability model for a multiprocessor system

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Ilsueh, M. C.↗

Necessary conditions for the optimality of variable rate residual vector quantizers

Residual vector quantization (RVQ), or multistage VQ, as it is also called, has recently been shown to be a competitive technique for data compression. The competitive performance of RVQ reported in results from the joint optimization of variable rate encoding and RVQ direct-sum code books. In this paper, necessary conditions for the optimality of variable rate RVQ's are derived, and an iterative descent algorithm based on a Lagrangian formulation is introduced for designing RVQ's having minimum average distortion subject to an entropy constraint. Simulation results for these entropy-constrained RVQ's (EC-RVQ's) are presented for memory less Gaussian, Laplacian, and uniform sources. A Gauss-Markov source is also considered. The performance is superior to that of entropy-constrained scalar quantizers (EC-SQ's) and practical entropy-constrained vector quantizers (EC-VQ's), and is competitive with that of some of the best source coding techniques that have appeared in the literature.

Kossentini, Faouzi↗

Parallelizing Timed Petri Net simulations

The possibility of using parallel processing to accelerate the simulation of Timed Petri Nets (TPN's) was studied. It was recognized that complex system development tools often transform system descriptions into TPN's or TPN-like models, which are then simulated to obtain information about system behavior. Viewed this way, it was important that the parallelization of TPN's be as automatic as possible, to admit the possibility of the parallelization being embedded in the system design tool. Later years of the grant were devoted to examining the problem of joint performance and reliability analysis, to explore whether both types of analysis could be accomplished within a single framework. In this final report, the results of our studies are summarized. We believe that the problem of parallelizing TPN's automatically for MIMD architectures has been almost completely solved for a large and important class of problems. Our initial investigations into joint performance/reliability analysis are two-fold; it was shown that Monte Carlo simulation, with importance sampling, offers promise of joint analysis in the context of a single tool, and methods for the parallel simulation of general Continuous Time Markov Chains, a model framework within which joint performance/reliability models can be cast, were developed. However, very much more work is needed to determine the scope and generality of these approaches. The results obtained in our two studies, future directions for this type of work, and a list of publications are included.

Nicol, David M.↗

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Goad, Clyde C.↗