914 resultados para linear dynamic output feedback control


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Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

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We proposed a simple feedback control method to suppress chaotic behavior in oscillators with limited power supply. The small-amplitude controlling signal is applied directly to the power supply system, so as to alter the characteristic curve of the driving motor. Numerical results are presented showing the method efficiency for a wide range of control parameters. Moreover, we have found that, for some parameters, this kind of control may introduce coexisting periodic attractors with complex basins of attraction and, therefore, serious problems with predictability of the final state the system will asymptote to. (c) 2006 Elsevier Ltd. All rights reserved.

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A systematic procedure of zero placement to design control systems is proposed. A state feedback controller with vector gain K is used to perform the pole placement. An estimator with vector gain L is also designed for output feedback control. A new systematic method of zero assignment to reduce the effect of the undesirable poles of the plant and also to increase the velocity error constant is presented. The methodology places the zeros in a specific region and it is based on Linear Matrix Inequalities (LMIs) framework, which is a new approach to solve this problem. Three examples illustrate the effectiveness of the proposed method.

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

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The p53 tumor suppressor protein and the MDM2 oncoprotein form a feedback-control loop that up-regulates cellular MDM2 production, blocks p53 activity, and promotes p53 decay. tsg101 was discovered as a gene whose deficiency results in neoplastic transformation of NIH 3T3 cells and the ability to generate metastatic tumors in nude mice. Its protein product contains a domain, Ubc, characteristic of the catalytic domain of ubiquitin conjugase (E2) enzymes but lacking an active-site cysteine crucial for ubiquitin conjugase activity. Here we report that TSG101 participates with MDM2 in an autoregulatory loop that modulates the cellular levels of both proteins, and also of p53, by affecting protein decay. We show that the Ubc domain of TSG101 interferes with ubiquitination of MDM2, that TSG101 inhibits MDM2 decay and elevates its steady-state level, and that these events are associated with down-regulation of p53 protein. Conversely, pulse–chase and Western blot experiments in wild-type and mutant fibroblasts indicate that elevation of MDM2 by overexpression of wild-type p53, by amplification of the endogenous MDM2 gene, or by transfection of MDM2-expressing constructs promotes TSG101 loss, which we show occurs by 26S proteasome-dependent decay. Our results identify TSG101 as both a regulator of, and target of, MDM2/p53 circuitry.

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Tuber formation in potato (Solanum tuberosum) is promoted by short photoperiods and is inhibited by gibberellins (GAs). Endogenous levels of GA1 were shown to decrease in stolons and leaves of potato plants induced to tuberize, which suggests that photoperiodic regulation of GA biosynthesis may play a role in tuber induction. We report the isolation of three potato cDNA clones (StGA20ox1–3) encoding GA 20-oxidase, a key regulatory enzyme in the GA-biosynthetic pathway. Using northern analysis, we detected a differential pattern of tissue-specific expression of the mRNAs corresponding to these clones. StGA20ox mRNAs were also very abundant in leaves of the potato ga1 mutant, which is blocked in the 13-hydroxylation step, and were strongly down-regulated by gibberellic acid, suggesting a feedback regulation of these genes. In plants grown in short-day (inductive) conditions, levels of the StGA20ox transcripts in leaves fluctuated during a 24-h period, with a peak of accumulation observed about 4 h after the lights were turned off. Interruption of the night with a 30-min “night break” of light (noninductive conditions) did not have a marked effect on the levels of accumulation of the three GA 20-oxidase mRNAs during the day, but it induced a second peak of expression of StGA20ox1 and StGA20ox3 transcripts late in the night. This observation, together with the finding that StGA20ox1 mRNA is expressed at high levels in leaves, suggests that night-break induction of this gene might play a role in the control of tuberization by regulating endogenous levels of GAs in response to daylength conditions.

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A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.

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National Highway Traffic Safety Administration, Washington, D.C.