Estimation and identification study for flexible vehicles

Techniques are studied for the estimation of rigid body and bending states and the identification of model parameters associated with the single-axis attitude dynamics of a flexible vehicle. This problem is highly nonlinear but completely observable provided sufficient attitude and attitude rate data is available and provided all system bending modes are excited in the observation interval. A sequential estimator tracks the system states in the presence of model parameter errors. A batch estimator identifies all model parameters with high accuracy

Low thrust interplanetary trajectory open loop error analysis, volume 1 Final report

Computer program for open-loop error analysis of low thrust interplanetary trajectorie

Nonlinear and adaptive estimation techniques in reentry

The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported. Of particular interest is the identifcation of vehicle lift and drag characteristics in real time. Several nonlinear filters were developed and simulated. Adaptive filters for the real time identification of vehicle lift and drag characteristics, and unmodelable acceleration, were also developed and tested by simulation. The simulations feature an uncertain system environment with rather arbitrary model errors, thus providing a definitive test of estimator performance. It was found that nonlinear effects are indeed significant in reentry trajectory estimation and a nonlinear filter is demonstrated which successfully tracks through nonlinearities without degrading the information content of the data. Under the same conditions the usual extended Kalman filter diverges and is useless. The J-adaptive filter is shown to successfully track errors in the modeled vehicle lift and drag characteristics. The same filter concept is also shown to track successfully through rather arbitrary model errors, including lift and drag errors, vehicle mass errors, atmospheric density errors, and wind gust errors

Urban air quality estimation study, phase 1

Possibilities are explored for applying estimation theory to the analysis, interpretation, and use of air quality measurements in conjunction with simulation models to provide a cost effective method of obtaining reliable air quality estimates for wide urban areas. The physical phenomenology of real atmospheric plumes from elevated localized sources is discussed. A fluctuating plume dispersion model is derived. Individual plume parameter formulations are developed along with associated a priori information. Individual measurement models are developed

Suboptimal filtering. Part 2 - Compensation for modeling errors in orbit determination problems Final report

Compensation for dynamic and measurement model errors in real time orbit determination system

The Yeast Retrograde Response as a Model of Intracellular Signaling of Mitochondrial Dysfunction

Mitochondrial dysfunction activates intracellular signaling pathways that impact yeast longevity, and the best known of these pathways is the retrograde response. More recently, similar responses have been discerned in other systems, from invertebrates to human cells. However, the identity of the signal transducers is either unknown or apparently diverse, contrasting with the well-established signaling module of the yeast retrograde response. On the other hand, it has become equally clear that several other pathways and processes interact with the retrograde response, embedding it in a network responsive to a variety of cellular states. An examination of this network supports the notion that the master regulator NFκB aggregated a variety of mitochondria-related cellular responses at some point in evolution and has become the retrograde transcription factor. This has significant consequences for how we view some of the deficits associated with aging, such as inflammation. The support for NFκB as the retrograde response transcription factor is not only based on functional analyses. It is bolstered by the fact that NFκB can regulate Myc–Max, which is activated in human cells with dysfunctional mitochondria and impacts cellular metabolism. Myc–Max is homologous to the yeast retrograde response transcription factor Rtg1–Rtg3. Further research will be needed to disentangle the pro-aging from the anti-aging effects of NFκB. Interestingly, this is also a challenge for the complete understanding of the yeast retrograde response

Continuous-Discrete Path Integral Filtering

A summary of the relationship between the Langevin equation, Fokker-Planck-Kolmogorov forward equation (FPKfe) and the Feynman path integral descriptions of stochastic processes relevant for the solution of the continuous-discrete filtering problem is provided in this paper. The practical utility of the path integral formula is demonstrated via some nontrivial examples. Specifically, it is shown that the simplest approximation of the path integral formula for the fundamental solution of the FPKfe can be applied to solve nonlinear continuous-discrete filtering problems quite accurately. The Dirac-Feynman path integral filtering algorithm is quite simple, and is suitable for real-time implementation.Comment: 35 pages, 18 figures, JHEP3 clas

Body composition, IGF1 status, and physical functionality in nonagenarians: implications for osteosarcopenia

OBJECTIVES: Body composition alterations occur during aging. The purpose of the present analysis was to explore the functional consequences of the overlap of sarcopenia and osteoporosis, and the potential role of insulin-like growth factor 1 (IGF1) in their development in the oldest old. SETTING AND PARTICIPANTS: Eighty-seven nonagenarians from the Louisiana Healthy Aging Study were included. MEASURES: The definition of sarcopenia was based on appendicular lean mass (ALM). Osteoporosis was diagnosed based on bone mineral density (BMD) T score. Four phenotypes were compared: (1) healthy body composition, that is, nonosteoporotic nonsarcopenic (CO, control group), (2) osteoporotic (O, low BMD T score), (3) sarcopenic (S, low ALM), and (4) osteosarcopenic (OS, low BMD T score and low ALM). Sex- and age-specific IGF1-Standard Deviation Scores (SDS) were calculated. The Continuous Scale-Physical Functional Performance (CS-PFP) test was performed. RESULTS: In OS men, IGF1-SDS values (-0.61 ±0.37 vs -0.04 ± 0.52, P = .02) were lower than those in CO males (control group), whereas IGF1-SDS were similar in the 4 body composition phenotypes in women. In men only, ALM was positively associated with IGF1-SDS values (P = .01) independent of age and C-reactive protein concentration. Regarding bone health, we found no association between IGF1-SDS values and BMD. IGF1-SDS was not associated with functional performance (CS-PFP) in men and women. CONCLUSIONS/IMPLICATIONS: IGF1 sensitivity in skeletal muscle and bone may differ by sex in the oldest old. IGF1 status did not appear to affect physical functionality. Determinants and clinical and functional characteristics of osteosarcopenia need to be further investigated in order to define conclusive diagnostic criteria

J-adaptive estimation with estimated noise statistics

The J-adaptive sequential estimator is extended to include simultaneous estimation of the noise statistics in a model for system dynamics. This extension completely automates the estimator, eliminating the requirement of an analyst in the loop. Simulations in satellite orbit determination demonstrate the efficacy of the sequential estimation algorithm

Efficient non-linear data assimilation in geophysical fluid dynamics

New ways of combining observations with numerical models are discussed in which the size of the state space can be very large, and the model can be highly nonlinear. Also the observations of the system can be related to the model variables in highly nonlinear ways, making this data-assimilation (or inverse) problem highly nonlinear. First we discuss the connection between data assimilation and inverse problems, including regularization. We explore the choice of proposal density in a Particle Filter and show how the ’curse of dimensionality’ might be beaten. In the standard Particle Filter ensembles of model runs are propagated forward in time until observations are encountered, rendering it a pure Monte-Carlo method. In large-dimensional systems this is very inefficient and very large numbers of model runs are needed to solve the data-assimilation problem realistically. In our approach we steer all model runs towards the observations resulting in a much more efficient method. By further ’ensuring almost equal weight’ we avoid performing model runs that are useless in the end. Results are shown for the 40 and 1000 dimensional Lorenz 1995 model