Supervisory control of a variable speed wind turbine with doubly fed induction generator

This paper is on an onshore variable speed wind turbine with doubly fed induction generator and under supervisory control. The control architecture is equipped with an event-based supervisor for the supervision level and fuzzy proportional integral or discrete adaptive linear quadratic as proposed controllers for the execution level. The supervisory control assesses the operational state of the variable speed wind turbine and sends the state to the execution level. Controllers operation are in the full load region to extract energy at full power from the wind while ensuring safety conditions required to inject the energy into the electric grid. A comparison between the simulations of the proposed controllers with the inclusion of the supervisory control on the variable speed wind turbine benchmark model is presented to assess advantages of these controls. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Error control on spectral data of four-wave mixing based on a-SiC technology

In this paper we exploit the nonlinear property of the SiC multilayer devices to design an optical processor for error detection that enables reliable delivery of spectral data of four-wave mixing over unreliable communication channels. The SiC optical processor is realized by using double pin/pin a-SiC:H photodetector with front and back biased optical gating elements. Visible pulsed signals are transmitted together at different bit sequences. The combined optical signal is analyzed. Data show that the background acts as selector that picks one or more states by splitting portions of the input multi optical signals across the front and back photodiodes. Boolean operations such as EXOR and three bit addition are demonstrated optically, showing that when one or all of the inputs are present, the system will behave as an XOR gate representing the SUM. When two or three inputs are on, the system acts as AND gate indicating the present of the CARRY bit. Additional parity logic operations are performed using four incoming pulsed communication channels that are transmitted and checked for errors together. As a simple example of this approach, we describe an all-optical processor for error detection and then provide an experimental demonstration of this idea. (C) 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optical processor based on a-SiC technology for spectral data error control

The SiC optical processor for error detection and correction is realized by using double pin/pin a-SiC:H photodetector with front and back biased optical gating elements. Data shows that the background act as selector that pick one or more states by splitting portions of the input multi optical signals across the front and back photodiodes. Boolean operations such as exclusive OR (EXOR) and three bit addition are demonstrated optically with a combination of such switching devices, showing that when one or all of the inputs are present the output will be amplified, the system will behave as an XOR gate representing the SUM. When two or three inputs are on, the system acts as AND gate indicating the present of the CARRY bit. Additional parity logic operations are performed by use of the four incoming pulsed communication channels that are transmitted and checked for errors together. As a simple example of this approach, we describe an all optical processor for error detection and correction and then, provide an experimental demonstration of this fault tolerant reversible system, in emerging nanotechnology.

On performance of distributed model predictive control in power system frequency regulation

This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).

Assessment and control of nanoparticles exposure in welding operations by use of a control banding tool

This paper describes the use of a Control Banding Tool to assess and further control of exposure of nanoparticles emitted during welding operations. The tool was applied to Metal Active Gas (MAG) arc welding of mild and stainless steel, providing semi-quantitative data on the process, so that protection measures could be derived, e.g. exhaust gas ventilation by hoods, local ventilation devices and containment measures. This tool is quite useful to compare and evaluate the characteristics of arc welding procedures so that more eco-friendly processes could be preferred over the more potentially noxious ones.

Control of predators in industrial scale microalgae cultures with Pulsed Electric Fields.

This work describes the utilization of Pulsed Electric Fields to control the protozoan contamination of a microalgae culture, in an industrial 2.7m3 microalgae photobioreactor. The contaminated culture was treated with Pulsed Electric Fields, PEF, for 6h with an average of 900V/cm, 65μs pulses of 50Hz. Working with recirculation, all the culture was uniformly exposed to the PEF throughout the assay. The development of the microalgae and protozoan populations was followed and the results showed that PEF is effective on the selective elimination of protozoa from microalgae cultures, inflicting on the protozoa growth halt, death or cell rupture, without affecting microalgae productivity. Specifically, the results show a reduction of the active protozoan population of 87% after 6h treatment and 100% after few days of normal cultivation regime. At the same time, microalgae growth rate remained unaffected. © 2014 Elsevier B.V.

Complementary filter design with three frequency bands: robot attitude estimation

This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.