Global Tracking Passivity--based PI Control of Bilinear Systems and its Application to the Boost and Modular Multilevel Converters

This paper deals with the problem of trajectory tracking of a class of bilinear systems with time--varying measurable disturbance. A set of matrices {A,B_i} has been identified, via a linear matrix inequality, for which it is possible to ensure global tracking of (admissible, differentiable) trajectories with a simple linear time--varying PI controller. Instrumental to establish the result is the construction of an output signal with respect to which the incremental model is passive. The result is applied to the boost and the modular multilevel converter for which experimental results are given.Comment: 9 pages, 10 figure

Solution of partial differential equations on vector and parallel computers

The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed

A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

New Flexible Regression Models Generated by Gamma Random Variables with Censored Data

We propose and study a new log-gamma Weibull regression model. We obtain explicit expressions for the raw and incomplete moments, quantile and generating functions and mean deviations of the log-gamma Weibull distribution. We demonstrate that the new regression model can be applied to censored data since it represents a parametric family of models which includes as sub-models several widely-known regression models and therefore can be used more effectively in the analysis of survival data. We obtain the maximum likelihood estimates of the model parameters by considering censored data and evaluate local influence on the estimates of the parameters by taking different perturbation schemes. Some global-influence measurements are also investigated. Further, for different parameter settings, sample sizes and censoring percentages, various simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We demonstrate that our extended regression model is very useful to the analysis of real data and may give more realistic fits than other special regression models

Evaluation of the economic and environmental performance of low-temperature heat to power conversion using a reverse electrodialysis - Multi-effect distillation system

In the examined heat engine, reverse electrodialysis (RED) is used to generate electricity from the salinity difference between two artificial solutions. The salinity gradient is restored through a multi-effect distillation system (MED) powered by low-temperature waste heat at 100 ◦C. The current work presents the first comprehensive economic and environmental analysis of this advanced concept, when varying the number of MED effects, the system sizing, the salt of the solutions, and other key parameters. The levelized cost of electricity (LCOE) has been calculated, showing that competitive solutions can be reached only when the system is at least medium to large scale. The lowest LCOE, at about 0.03 €/kWh, is achieved using potassium acetate salt and six MED effects while reheating the solutions. A similar analysis has been conducted when using the system in energy storage mode, where the two regenerated solutions are stored in reservoir tanks and the RED is operating for a few hours per day, supplying valuable peak power, resulting in a LCOE just below 0.10 €/kWh. A life-cycle assessment has been also carried out, showing that the case with the lowest environmental impact is the same as the one with the most attractive economic performance. Results indicate that the material manufacturing has the main impact; primarily the metallic parts of the MED. Overall, this study highlights the development efforts required in terms of both membrane performance and cost reduction, in order to make this technology cost effective in the future

A Statistical Prescription to Estimate Properly Normalized Distributions of Different Particle Species

We describe a statistical method to avoid biased estimation of the content of different particle species. We consider the case when the particle identification information strongly depends on some kinematical variables, whose distributions are unknown and different for each particles species. We show that the proposed procedure provides properly normalized and completely data-driven estimation of the unknown distributions without any a priori assumption on their functional form. Moreover, we demonstrate that the method can be generalized to any kinematical distribution of the particles