Robust Nonlinear Control of Brushless DC Motors for Direct-Drive Robotic Applications

The control problem associated with brushless DC motors (BLDCMs) for direct-drive robotic applications is considered. In order to guarantee the high-performance operation of BLDCMs in such applications, the effects of reluctance variations and magnetic saturation are accounted for in the model. Such a BLDCM model constitutes a highly coupled and nonlinear dynamic system. Using the transformation theory of nonlinear systems, a feedback control law, which is shown to compensate for the system nonlinearities, is derived. Conditions under which such a control law is possible are presented. The need for the derivation of explicit commutation strategies is eliminated, resulting in reduction of the computations involved. To guarantee the high-performance operation of the system under substantial uncertainties, a robust control law is derived and appended to the overall control structure. The inclusion of the robust controller results in good tracking performance when there are modeling and measurement errors and payload uncertainties. The efficacy of the overall control law is investigated by considering a single-link direct-drive arm actuated by a BLDCM

Retirement investor risk tolerance in tranquil and crisis periods: Experimental survey evidence

We conduct a choice experiment to investigate the impact of the financial crisis of 2008 on retirement saver investment choice and risk aversion. Analysis of estimated individual risk parameters shows a small increase in mean risk aversion between the relatively tranquil period of early 2007 and the crisis conditions of late 2008. Investment preferences of survey respondents, estimated using the scale-adjusted version of a latent class choice model, also change during the crisis. We identify age and income as important determinants of preference classes in both surveys and age is also identified as a key determinant of variability (scale). Young and low income individuals make choices that are more consistent with standard mean- variance analysis, but older and higher income individuals react positively to both higher returns and increasing risk in returns. Overall we find a mild moderating of retirement investor risk tolerance in 2008. © The Institute of Behavioral Finance

Long-term carbon and nitrogen dynamics at SPRUCE revealed through stable isotopes in peat profiles

Peatlands encode information about past vegetation dynamics, climate, and microbial processes. Here, we used δ15N and δ13C patterns from 16 peat profiles to deduce how the biogeochemistry of the Marcell S1 forested bog in northern Minnesota responded to environmental and vegetation change over the past  ∼ 10000 years. In multiple regression analyses, δ15N and δ13C correlated strongly with depth, plot location, C∕N, %N, and each other. Correlations with %N, %C, C∕N, and the other isotope accounted for 80% of variance for δ15N and 38% of variance for δ13C, reflecting N and C losses. In contrast, correlations with depth and topography (hummock or hollow) reflected peatland successional history and climate. Higher δ15N in plots closer to uplands may reflect upland-derived DON inputs and accompanying shifts in N dynamics in the lagg drainage area surrounding the bog. The Suess effect (declining δ13CO2 since the Industrial Revolution) lowered δ13C in recent surficial samples. High δ15N from −35 to −55cm probably indicated the depth of ectomycorrhizal activity after tree colonization of the peatland over the last 400 years, as confirmed by the occasional presence of wood down to −35cm depth. High δ13C at  ∼ 4000 years BP (−65 to −105cm) could reflect a transition at that time to slower rates of peat accumulation, when 13C discrimination during peat decomposition may increase in importance. Low δ13C and high δ15N at −213 and −225cm ( ∼ 8500 years BP) corresponded to a warm period during a sedge-dominated rich fen stage. The above processes appear to be the primary drivers of the observed isotopic patterns, whereas there was no clear evidence for methane dynamics influencing δ13C patterns

Robust Nonlinear Control of Brushless DC Motors in the Presence of Magnetic Saturation

A robust control law is derived and examined for a direct-drive robot arm driven by a brushless DC motor (BLDCM). The complete dynamics of the motor and its interaction with the robot arm are accounted for. This is important, since in a direct-drive servo system the torque generated by the motor is directly transmitted to the load. Effects of magnetic saturation as well as reluctance variations are accounted for, in order to ensure accuracy. The effectiveness of the method is examined through computer simulations. The computational complexity of the overall control scheme is such that it can be readily used for real-time contro

Financial Competence and Expectations Formation: Evidence from Australia

We study the financial competence of Australian retirement savers using self-assessed and quantified measures. Responses to financial literacy questions show large variation and compare poorly with some international surveys. Basic and sophisticated financial literacy vary significantly with most demographics, self-assessed financial competence, income, superannuation accumulation and net worth. General numeracy scores are largely constant across gender, age, higher education and income. Financial competence also significantly affects expectations of stock market performance. Using a discrete choice model, we show that individuals with a higher understanding of risk, diversification and financial assets are more likely to assign a probability to future financial crises rather than expressing uncertainty. © 2011 The Economic Society of Australia

Investment decisions for retirement savings

We conducted a choice experiment to investigate whether retirement savers follow simple portfolio theory when choosing investments. We modeled experimental survey data on 693 participants using a scale-adjusted version of the latent class choice model. Results show that underlying variability in response was explained by age and " risk profile" score and that preferences varied with income and age. Younger individuals were conventionally risk averse, but older, higher-income individuals may react positively to both higher returns and increasing risk, when risk is presented as widening ranges of possible outcomes. Respondents tended to choose among a few similar investment options. Copyright 2010 by The American Council on Consumer Interests

Using scenarios to explore UK upland futures

Uplands around the world are facing significant social, economic and environmental changes, and decision-makers need to better understand what the future may hold if they are to adapt and maintain upland goods and services. This paper draws together all major research comprising eight studies that have used scenarios to describe possible futures for UK uplands. The paper evaluates which scenarios are perceived by stakeholders to be most likely and desirable, and assesses the benefits and drawbacks of the scenario methods used in UK uplands to date. Stakeholders agreed that the most desirable and likely scenario would be a continuation of hill farming (albeit at reduced levels) based on cross-compliance with environmental measures. The least desirable scenario is a withdrawal of government financial support for hill farming. Although this was deemed by stakeholders to be the least likely scenario, the loss of government support warrants close attention due to its potential implications for the local economy. Stakeholders noted that the environmental implications of this scenario are much less clear-cut. As such, there is an urgent need to understand the full implications of this scenario, so that upland stakeholders can adequately prepare, and policy-makers can better evaluate the likely implications of different policy options. The paper concludes that in future, upland scenario research needs to: (1) better integrate in-depth and representative participation from stakeholders during both scenario development and evaluation; and (2) make more effective use of visualisation techniques and simulation models

Dynamic optimal taxation with human capital.

This paper revisits the dynamic optimal taxation results of Jones, Manuelli, and Rossi (1993, 1997). They use a growth model with human capital and find that optimal taxes on both capital income and labor income converge to zero in steady state. For one of the models under consideration, I show that the representative household's problem does not have an interior solution. This raises concerns since these corners are inconsistent with aggregate data. Interiority is restored if preferences are modified so that human capital augments the value of leisure time. With this change, the optimal tax problem is analyzed and, reassuringly, the Jones, Manuelli, and Rossi results are confirmed: neither capital income nor labor income should be taxed in steady state

Comparison of Computational-Model and Experimental-Example Trained Neural Networks for Processing Speckled Fringe Patterns

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model-generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models