2,723 research outputs found
Test bed experiments for various telerobotic system characteristics and configurations
Dexterous manipulation and grasping in telerobotic systems depends on the integration of high-performance sensors, displays, actuators and controls into systems in which careful consideration has been given to human perception and tolerance. Research underway at the Wisconsin Center for Space Automation and Robotics (WCSAR) has the objective of enhancing the performance of these systems and their components, and quantifying the effects of the many electrical, mechanical, control, and human factors that affect their performance. This will lead to a fundamental understanding of performance issues which will in turn allow designers to evaluate sensor, actuator, display, and control technologies with respect to generic measures of dexterous performance. As part of this effort, an experimental test bed was developed which has telerobotic components with exceptionally high fidelity in master/slave operation. A Telerobotic Performance Analysis System has also been developed which allows performance to be determined for various system configurations and electro-mechanical characteristics. Both this performance analysis system and test bed experiments are described
Impact of inertia, friction, and backlash upon force control in telemanipulation
The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors
Capillary Movement in Substrates in Microgravity
A more complete understanding of the dynamics of capillary flow through an unsaturated porous medium would be useful for a number of space and terrestrial applications. Knowledge of capillary migration of liquids in granular beds in microgravity would significantly enhance the development and understanding of how a matrix based nutrient delivery system for the growth of plants would function in a microgravity environment. Thus, such information is of interest from the theoretical as well as practical point of view
Holomorphic transforms with application to affine processes
In a rather general setting of It\^o-L\'evy processes we study a class of
transforms (Fourier for example) of the state variable of a process which are
holomorphic in some disc around time zero in the complex plane. We show that
such transforms are related to a system of analytic vectors for the generator
of the process, and we state conditions which allow for holomorphic extension
of these transforms into a strip which contains the positive real axis. Based
on these extensions we develop a functional series expansion of these
transforms in terms of the constituents of the generator. As application, we
show that for multidimensional affine It\^o-L\'evy processes with state
dependent jump part the Fourier transform is holomorphic in a time strip under
some stationarity conditions, and give log-affine series representations for
the transform.Comment: 30 page
Cladding strategies for building-integrated photovoltaics
Photovoltaic cladding on the surfaces of commercial buildings has the potential for considerable reductions in carbon emissions due to embedded renewable power generation displacing conventional power utilization. In this paper, a model is described for the optimization of photovoltaic cladding densities on commercial building surfaces. The model uses a modified form of the ‘fill factor’ method for photovoltaic power supply coupled to new regression-based procedures for power demand estimation. An optimization is included based on a defined ‘mean index of satisfaction’ for matched power supply and demand (i.e., zero power exportation to the grid). The mean index of satisfaction directly translates to the reduction in carbon emission that might be expected over conventional power use. On clear days throughout the year, reductions of conventional power use of at least 60% can be achieved with an optimum cladding pattern targeted to lighting and small power load demands
Monthly average daily global and diffuse solar radiation based on sunshine duration and clearness index for Brasov, Romania
The main objective of this study is to develop single location appropriate models for the estimation of the monthly average daily global and diffuse horizontal solar radiation for Brasov, Romania. The study focuses particularly on models based on the sunshine duration and clearness index. The data used for the calibration of the models were collected during a period of 4 yr, between November 2008 and October 2012, at the Transilvania University of Brasov. The testing and validation of the models was carried out using data from the online SoDa database for Brasov for the year 2005. Different statistical error tests were applied to evaluate the accuracy of the models. The predicted values are also compared with values from three other known models concerning the global and diffuse solar radiation. A new mixed model was developed for the estimation of monthly average daily global horizontal solar radiation. The data processing was performed by means of a real-time interface developed with LabVIEW graphical programming language. The parameters taken into account were the relative sunshine, the clearness index, the extraterrestrial radiation, the latitude and the longitude. The methodology is simple and effective and may be applied for any region. Its effectiveness was proven through comparison with global models
Evolutionary estimation of a Coupled Markov Chain credit risk model
There exists a range of different models for estimating and simulating credit
risk transitions to optimally manage credit risk portfolios and products. In
this chapter we present a Coupled Markov Chain approach to model rating
transitions and thereby default probabilities of companies. As the likelihood
of the model turns out to be a non-convex function of the parameters to be
estimated, we apply heuristics to find the ML estimators. To this extent, we
outline the model and its likelihood function, and present both a Particle
Swarm Optimization algorithm, as well as an Evolutionary Optimization algorithm
to maximize the likelihood function. Numerical results are shown which suggest
a further application of evolutionary optimization techniques for credit risk
management
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Optimal seismic upgrade timing in seaports with increasing throughput demand via real options
A real options (RO) formulation is proposed for decision-making on the timing to upgrade the seismic performance of existing seaports with increasing throughput demand in earthquake prone areas. The pay-off of the seismic upgrade investment option is estimated based on projected net earnings, repair cost, and downtime for a damaging reference seismic event having a pre-specified annual probability of occurrence. These projections inform a discrete-time RO binomial tree, following the American option valuation framework, which propagates the probability of the reference seismic event assuming Poisson temporal distribution of earthquake occurrence. The net present value of the expected annual payoff of the considered investment is used as an index supporting risk-informed decision-making discounted by the weighted average cost of capital (WACC). Numerical examples pertaining to decision makers with different capital cost, namely port authorities and terminal operators, operating in different economic environments typical of developed and developing countries are furnished to illustrate the applicability of the proposed RO formulation. It is found that high WACC and/or low throughput growth bring the optimal seismic upgrade timing forward, while earthquake consequences and upgrade cost have almost no influence on this timing
Entropy of the Nordic electricity market: anomalous scaling, spikes, and mean-reversion
The electricity market is a very peculiar market due to the large variety of
phenomena that can affect the spot price. However, this market still shows many
typical features of other speculative (commodity) markets like, for instance,
data clustering and mean reversion. We apply the diffusion entropy analysis
(DEA) to the Nordic spot electricity market (Nord Pool). We study the waiting
time statistics between consecutive spot price spikes and find it to show
anomalous scaling characterized by a decaying power-law. The exponent observed
in data follows a quite robust relationship with the one implied by the DEA
analysis. We also in terms of the DEA revisit topics like clustering,
mean-reversion and periodicities. We finally propose a GARCH inspired model but
for the price itself. Models in the context of stochastic volatility processes
appear under this scope to have a feasible description.Comment: 16 pages, 7 figure
Scope for Credit Risk Diversification
This paper considers a simple model of credit risk and derives the limit distribution of losses under different assumptions regarding the structure of systematic risk and the nature of exposure or firm heterogeneity. We derive fat-tailed correlated loss distributions arising from Gaussian risk factors and explore the potential for risk diversification. Where possible the results are generalised to non-Gaussian distributions. The theoretical results indicate that if the firm parameters are heterogeneous but come from a common distribution, for sufficiently large portfolios there is no scope for further risk reduction through active portfolio management. However, if the firm parameters come from different distributions, then further risk reduction is possible by changing the portfolio weights. In either case, neglecting parameter heterogeneity can lead to underestimation of expected losses. But, once expected losses are controlled for, neglecting parameter heterogeneity can lead to overestimation of risk, whether measured by unexpected loss or value-at-risk
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