Pseudospectral Model Predictive Control under Partially Learned Dynamics

Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underlying parametric model. In the field of robotics, a lack of model knowledge can be overcome with machine learning techniques, utilizing measurements to build a dynamical model from the data. This paper aims to take the middle ground between these two approaches by introducing a semi-parametric representation of the underlying system dynamics. Our goal is to leverage the considerable information contained in a traditional physics based model and combine it with a data-driven, non-parametric regression technique known as a Gaussian Process. Integrating this semi-parametric model with model predictive pseudospectral control, we demonstrate this technique on both a cart pole and quadrotor simulation with unmodeled damping and parametric error. In order to manage parametric uncertainty, we introduce an algorithm that utilizes Sparse Spectrum Gaussian Processes (SSGP) for online learning after each rollout. We implement this online learning technique on a cart pole and quadrator, then demonstrate the use of online learning and obstacle avoidance for the dubin vehicle dynamics.Comment: Accepted but withdrawn from AIAA Scitech 201

Sobre algunas plantas de las Yeseras de Almería

Se ofrecen datos corológicos y ecológicos sobre algunos táxones de interés de la flora gipsícola almeriense. Quince táxones pueden haberse citado por primera vez en la provincia.Corological and ecological data of some interesting taxa of the gypsum flora from Almería province are presented. Fifteen taxa are probably cited at the first time for Almería province (SE of Spain)

Web based application for the selection of cable trays

Peer Reviewe

Adaptation of the application qualifo to communicate with the photon kinetics 800 otdr

Peer Reviewe

Sobre la parasíntesis en español.

Sin resume

US state health expenditure convergence: A revisited analysis

This paper studies the evolution of US state health expenditure for a sample that covers 1966–2014. Our results provide evidence against the existence of a single pattern of behavior of personal health care expenditure across the US states. Rather, we can observe the existence of two statistically different convergence clubs. We cannot find evidence of convergence when we disaggregate health expenditure into its three main payers: Medicare, Medicaid and private health insurance expenditure, whilst we again find evidence of convergence clubs. However, the estimated clubs for Medicaid and private health insurance expenditure are statistically different that estimated for total health expenditure. Consequently, our results offer strong evidence of heterogeneity in the evolution of US health expenditure. The analysis of the forces that drive club creation shows that economic situation and some supply-side factors are important. We can also appreciate that some healthcare outcome variables are only related to private insurance health expenditure. The other health expenditures, thus, show a certain lack of efficiency which may be due to practices that have little benefit for patient health

Evaluation of the changes in working limits in an automobile assembly line using simulation

The aim of the work presented in this paper consists of the development of a decision-making support system, based on discrete-event simulation models, of an automobile assembly line which was implemented within an Arena simulation environment and focused at a very specific class of production lines with a four closed-loop network configuration. This layout system reflects one of the most common configurations of automobile assembly and preassembly lines formed by conveyors. The sum of the number of pallets on the intermediate buffers, remains constant, except for the fourth closed-loop, which depends on the four-door car ratio (x) implemented between the door disassembly and assembly stations of the car body. Some governing equations of the four closed-loops are not compatible with the capacities of several intermediate buffers for certain values of variable x. This incompatibility shows how the assembly line cannot operate in practice for x0,97 in a stationary regime, due to the starvation phenomenon or the failure of supply to the machines on the production line. We have evaluated the impact of the pallet numbers circulating on the first closed-loop on the performance of the production line, translated into the number of cars produced/hour, in order to improve the availability of the entire manufacturing system for any value of x. Until the present date, these facts have not been presented in specialized literature. © 2012 American Institute of Physics

Optimization of the design of polygeneration systems for the residential sector under different self-consumption regulations

Polygeneration systems enable natural resources to be exploited efficiently, decreasing CO2 emissions and achieving economic savings relative to the conventional separate production. However, their economic feasibility depends on the legal framework. Preliminary design of polygeneration systems for the residential sector based on the last Spanish self-consumption regulations RD 900/2015 and RD 244/2019 was carried out in Zaragoza, Spain. Both regulations were applied to individual and collective installations. Several technologies, appropriate for the energy supply to residential buildings, for example, photovoltaics, wind turbines, solar thermal collectors, microcogeneration engines, heat pump, gas boiler, absorption chiller, and thermal and electric energy storage were considered candidate technologies for the polygeneration system. A mixed integer linear programming model was developed to minimize the total annual cost of polygeneration systems. Scenarios with and without electricity sale were considered. CO2 emissions were also calculated to estimate the environmental impact. Results show that RD 900/2015 discourages the investment in self-consumption systems whereas the RD 244/2019 encourages them, especially in renewable energy technologies. Moreover, in economic terms, it is more profitable to invest in collective self-consumption installations over individual installations. However, this does not necessarily represent a significant reduction of CO2 emissions with respect to individual installations since the natural gas consumption tends to increase as its unit price decreases because of the increase of its consumption level. Thus, more appropriate pricing of natural gas in residential sector, in which its cost would not be reduced when increasing its consumption, would be required to achieve significant CO2 emissions reduction. In all cases, the photovoltaic panels (PV) are competitive and profitable without subsidies in self-consumption schemes and the reversible heat pump (HP) played an important role for the CO2 emissions reduction. In a horizon to achieve zero CO2 emissions, the net metering scheme could be an interesting and profitable alternative to be considered

Evaluation of a Bayesian Algorithm to Detect Burned Areas in the Canary Islands’ Dry Woodlands and Forests Ecoregion Using MODIS Data

Burned Area (BA) is deemed as a primary variable to understand the Earth’s climate system. Satellite remote sensing data have allowed for the development of various burned area detection algorithms that have been globally applied to and assessed in diverse ecosystems, ranging from tropical to boreal. In this paper, we present a Bayesian algorithm (BY-MODIS) that detects burned areas in a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2002 to 2012 of the Canary Islands’ dry woodlands and forests ecoregion (Spain). Based on daily image products MODIS, MOD09GQ (250 m), and MOD11A1 (1 km), the surface spectral reflectance and the land surface temperature, respectively, 10 day composites were built using the maximum temperature criterion. Variables used in BY-MODIS were the Global Environment Monitoring Index (GEMI) and Burn Boreal Forest Index (BBFI), alongside the NIR spectral band, all of which refer to the previous year and the year the fire took place in. Reference polygons for the 14 fires exceeding 100 hectares and identified within the period under analysis were developed using both post-fire LANDSAT images and official information from the forest fires national database by the Ministry of Agriculture and Fisheries, Food and Environment of Spain (MAPAMA). The results obtained by BY-MODIS can be compared to those by official burned area products, MCD45A1 and MCD64A1. Despite that the best overall results correspond to MCD64A1, BY-MODIS proved to be an alternative for burned area mapping in the Canary Islands, a region with a great topographic complexity and diverse types of ecosystems. The total burned area detected by the BY-MODIS classifier was 64.9% of the MAPAMA reference data, and 78.6% according to data obtained from the LANDSAT images, with the lowest average commission error (11%) out of the three products and a correlation (R2) of 0.82. The Bayesian algorithm—originally developed to detect burned areas in North American boreal forests using AVHRR archival data Long-Term Data Record—can be successfully applied to a lower latitude forest ecosystem totally different from the boreal ecosystem and using daily time series of satellite images from MODIS with a 250 m spatial resolution, as long as a set of training areas adequately characterising the dynamics of the forest canopy affected by the fire is defined