A multi-cell variable frequency interleaved ZCS boost rectifier digitally controlled by FPGA

This paper presents a multi-cell single-phase high power factor boost rectifier in interleave connection, operating in critical conduction mode, employing a soft-switching technique, and controlled by Field Programmable Gate Array (FPGA). The soft-switching technique is based on zero-current-switching (ZCS) cells, providing ZC (zero-current) turn-on and ZCZV (zero-current-zero-voltage) turn-off for the active switches, and ZV (zero-vohage) turn-on and ZC (zero-current) turn-off for the boost diodes. The disadvantages related to reverse recovery effects of boost diodes operated in continuous conduction mode (additional losses, and electromagnetic interference (EMI) problems) are minimized, due to the operation in critical conduction mode. In addition, due to the interleaving technique, the rectifier's features include the reduction in the input current ripple, the reduction in the output voltage ripple, the use of low stress devices, low volume for the EMI input filter, high input power factor (PF), and low total harmonic distortion (THD) in the input current, in compliance with the IEC61000-3-2 standards. The digital controller has been developed using a hardware description language (VHDL) and implemented using a XC2S200E-SpartanII-E/Xilinx FPGA device, performing a true critical conduction operation mode for all interleaved cells, and a closed-loop to provide the output voltage regulation, like as a preregulator rectifier. Experimental results are presented for a implemented prototype with two and with four interleaved cells, 400V nominal output voltage and 220V(rms) nominal input voltage, in order to verify the feasibility and performance of the proposed digital control through the use of a FPGA device.

An adaptive system based on artificial neural networks for NPK fluid fertilizer application

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt with training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision fanning. Copyright (C) 2000 IFAC.

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

THE FLUID SYSTEMS FOR THE SLD CHERENKOV RING IMAGING DETECTOR

We describe the design and operation of the fluid delivery, monitor and control systems for the SLD barrel Cherenkov Ring Imaging Detector (CRID). The systems deliver drift gas (C2H6+TMAE), radiator gas (C5F12+N2) and radiator liquid (C6F14). MeasUred critical quantities such as electron lifetime in the drift gas and ultra-violet (UV) transparencies of the radiator fluids, together with the operational experience, are also reported.

Anticoccidial effects of coumestans from Eclipta alba for sustainable control of Eimeria tenella parasitosis in poultry production

The aim of this study was to evaluate the anticoccidial efficacy of a product containing coumestans from Eclipta alba. Experimental conditions were set up as to reproduce the environment conditions for husbandry adopted in commercial broiler farms. Broilers were raised in broiler chicken shed provided with feeders, drinkers, illumination and temperature control systems and floor covering to afford an adequate nourishing environment. Male Cobb broilers (240) were assigned to four experimental groups being each experimental group set apart in rice straw-covered shed isolated with wire mesh. One-day-old broilers were reared in a coccidian-free environment with ad libitum supply of filtered water and freely available standard feed, from the 1st to the 35th day of life. The T1 group received standard feed (negative control); T2 was treated with standard feed supplemented with 66 ppm of salinomycin (positive control); groups T3 and T4 had standard feed supplemented with the ethyl acetate fraction from methanolic extract of E. alba aerial parts, which contains the coumestans WL and DWL (120 and 180 ppm, respectively). The chicken broilers were individually infected with 2 x 104 oocysts of Eimeria tenella when they were 14 days old and were monitored weekly to evaluate zootechnical parameters such as weight gain and food conversion ratio. Counting of coccidial oocyst in chiken feces was assessed from random samples, from the 21st to 28th days of life, which corresponded to 7-14 days after the infection. Five chickens selected at random from each experimental group were subsequently euthanized at 21, 28 or 35 days of life to determine the lesion score in the cecal region and to excise a cecum portion for histopathological evaluation. The group treated with coumestans from E. alba presented an average weight gain and food conversion ratio higher than the negative control group and similar to the mean value of the positive control group. Coumestan-treated groups showed a significant decrease in the oocyst counting since the 21th day of life and displayed a reduced number of macroscopic lesions. Histopathological evaluations of cecum fragments showed that both treatments induced the migration of defense cells at the site of infection. A severe destruction of the cecal lining was found in the intestinal tract of broilers fed with a coumestans dose of 180 ppm. Overall, our results validate the use of a phytotherapy containing E. alba coumestans at a dose of 120 ppm as a therapeutic or prophylactic agent against avian coccidiosis. (C) 2010 Elsevier B.V. All rights reserved.

Optimal control problem for deflection plate with crack

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Oscillating holograms recorded in photorefractive crystals by a frequency detuned feedback loop

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

Fuzzy sets in distributed traffic control

The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

Necessary conditions for optimal impulsive control problems

A Maximum Principle is derived for a class of optimal control problems arising in midcourse guidance, in which certain controls are represented by measures and, the state trajectories are functions of bounded variation. The optimality conditions improves on previous optimality conditions by allowing nonsmooth data, measurable time dependence, and a possibly time varying constraint set for the conventional controls.

Well-conditioned robust observer for detection of faulty systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

H2 and/or H∞-norm model reduction of uncertain discrete-time systems

This paper addresses the problem of model reduction for uncertain discrete-time systems with convex bounded (polytope type) uncertainty. A reduced order precisely known model is obtained in such a way that the H2 and/or the H∞ guaranteed norm of the error between the original (uncertain) system and the reduced one is minimized. The optimization problems are formulated in terms of coupled (non-convex) LMIs - Linear Matrix Inequalities, being solved through iterative algorithms. Examples illustrate the results.

Control automatico de un sistema electrico mediante logica difusa

Substitution of fuzzy logic control in an electrical system normally controlled by proportional-integral frequency was studied and analyzed. A linear model of an electrical system, the concepts which govern the theory of fuzzy logic, and the application of this theory to systems control, are briefly presented. The methodology of fuzzy logic was then applied to develop a model for an electrical energy system. The results of the simulation demonstrated that fuzzy logic control eliminated the area frequency error and permitted that only the area experiencing an increase in charge responds to this variation. Based on the results, it is concluded that control based on fuzzy logic is simple, is easy to maintain, is of low cost, and can be used to substitute traditional velocity controllers.

Control preventivo dinamico de sistemas de energia electrica usando redespacho de generacion y corte de carga

A model for preventive control in electrical systems is presented, taking into account the dynamic aspects of the network. Among these aspects, the effects provoked by perturbations which cause oscillations in synchronous machine angles (transient stability), such as electric equipment outages and short circuits, are presented. The energy function is used to measure the stability of the system using a procedure defined as the security margin. The control actions employed are load shedding and generation reallocation. An application of the methodology to a system located in southern Brazil, which is composed of 10 synchronous machines, 45 busses, and 72 transmission lines. The results confirm the theoretical studies.

AI automates substation control

An overview is given on the possibility of controlling the status of circuit breakers (CB) in a substations with the use of a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets. It is shown that even when all the magnitudes to be controlled cannot be included in the analysis, it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.