990 resultados para Control constraints
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.
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In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.
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This thesis gathers the work carried out by the author in the last three years of research and it concerns the study and implementation of algorithms to coordinate and control a swarm of mobile robots moving in unknown environments. In particular, the author's attention is focused on two different approaches in order to solve two different problems. The first algorithm considered in this work deals with the possibility of decomposing a main complex task in many simple subtasks by exploiting the decentralized implementation of the so called \emph{Null Space Behavioral} paradigm. This approach to the problem of merging different subtasks with assigned priority is slightly modified in order to handle critical situations that can be detected when robots are moving through an unknown environment. In fact, issues can occur when one or more robots got stuck in local minima: a smart strategy to avoid deadlock situations is provided by the author and the algorithm is validated by simulative analysis. The second problem deals with the use of concepts borrowed from \emph{graph theory} to control a group differential wheel robots by exploiting the Laplacian solution of the consensus problem. Constraints on the swarm communication topology have been introduced by the use of a range and bearing platform developed at the Distributed Intelligent Systems and Algorithms Laboratory (DISAL), EPFL (Lausanne, CH) where part of author's work has been carried out. The control algorithm is validated by demonstration and simulation analysis and, later, is performed by a team of four robots engaged in a formation mission. To conclude, the capabilities of the algorithm based on the local solution of the consensus problem for differential wheel robots are demonstrated with an application scenario, where nine robots are engaged in a hunting task.
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Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.
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A full set of geochemical and Sr, Nd and Pb isotope data both on bulk-rock and mineral samples is provided for volcanic rocks representative of the whole stratigraphic succession of Lipari Island in the Aeolian archipelago. These data, together with petrographic observations and melt/fluid inclusion investigations from the literature, give outlines on the petrogenesis and evolution of magmas through the magmatic and eruptive history of Lipari. This is the result of nine successive Eruptive Epochs developing between 271 ka and historical times, as derived from recentmost volcanological and stratigraphic studies, combined with available radiometric ages and correlation of tephra layers and marine terrace deposits. These Eruptive Epochs are characterized by distinctive vents partly overlapping in space and time, mostly under control of the main regional tectonic trends (NNW-SSE, N-S and minor E-W). A large variety of lava flows, scoriaceous deposits, lava domes, coulees and pyroclastics are emplaced, ranging in composition through time from calcalkaline (CA) and high-K (HKCA) basaltic andesites to rhyolites. CA and HKCA basaltic andesitic to dacitic magmas were erupted between 271 and 81 ka (Eruptive Epochs 1-6) from volcanic edifices located along the western coast of the island (and subordinately the eastern Monterosa) and the M.Chirica and M.S.Angelo stratocones. These mafic to intermediate magmas mainly evolved through AFC and RAFC processes, involving fractionation of mafic phases, assimilation of wall rocks and mixing with newly injected mafic magmas. Following a 40 ka-long period of volcanic quiescence, the rhyolitic magmas were lately erupted from eruptive vents located in the southern and north-eastern sectors of Lipari between 40 ka and historical times (Eruptive Epochs 7-9). They are suggested to derive from the previous mafic to intermediate melts through AFC processes. During the early phases of rhyolitic magmatism (Eruptive Epochs 7-8), enclaves-rich rocks and banded pumices, ranging in composition from HKCA dacites to low-SiO2 rhyolites were erupted, representing the products of magma mixing between fresh mafic magmas and the fractionated rhyolitic melts. The interaction of mantle-derived magmas with the crust represents an essential process during the whole magmatic hystory of Lipari, and is responsible for the wide range of observed geochemical and isotopic variations. The crustal contribution was particularly important during the intermediate phases of activity of Lipari when the cordierite-bearing lavas were erupted from the M. S.Angelo volcano (Eruptive Epoch 5, 105 ka). These lavas are interpreted as the result of mixing and subsequent hybridization of mantle-derived magmas, akin to the ones characterizing the older phases of activity of Lipari (Eruptive Epochs 1-4), and crustal anatectic melts derived from dehydration-melting reactions of metapelites in the lower crust. A comparison between the adjacent islands of Lipari and Vulcano outlines that their mafic to intermediate magmas seem to be genetically connected and derive from a similar mantle source affected by different degrees of partial melting (and variable extent of crustal assimilation) producing either the CA magmas of Lipari (higher degrees) or the HKCA to SHO magmas of Vulcano (lower degrees). On a regional scale, the most primitive rocks (SiO2<56%, MgO>3.5%) of Lipari, Vulcano, Salina and Filicudi are suggested to derive from a similar MORB-like source, variably metasomatized by aqueous fluids coming from the slab and subordinately by the additions of sediments.
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Power electronic converters are extensively adopted for the solution of timely issues, such as power quality improvement in industrial plants, energy management in hybrid electrical systems, and control of electrical generators for renewables. Beside nonlinearity, this systems are typically characterized by hard constraints on the control inputs, and sometimes the state variables. In this respect, control laws able to handle input saturation are crucial to formally characterize the systems stability and performance properties. From a practical viewpoint, a proper saturation management allows to extend the systems transient and steady-state operating ranges, improving their reliability and availability. The main topic of this thesis concern saturated control methodologies, based on modern approaches, applied to power electronics and electromechanical systems. The pursued objective is to provide formal results under any saturation scenario, overcoming the drawbacks of the classic solution commonly applied to cope with saturation of power converters, and enhancing performance. For this purpose two main approaches are exploited and extended to deal with power electronic applications: modern anti-windup strategies, providing formal results and systematic design rules for the anti-windup compensator, devoted to handle control saturation, and “one step” saturated feedback design techniques, relying on a suitable characterization of the saturation nonlinearity and less conservative extensions of standard absolute stability theory results. The first part of the thesis is devoted to present and develop a novel general anti-windup scheme, which is then specifically applied to a class of power converters adopted for power quality enhancement in industrial plants. In the second part a polytopic differential inclusion representation of saturation nonlinearity is presented and extended to deal with a class of multiple input power converters, used to manage hybrid electrical energy sources. The third part regards adaptive observers design for robust estimation of the parameters required for high performance control of power systems.
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This thesis addresses the issue of generating texts in the style of an existing author, that also satisfy structural constraints imposed by the genre of the text. Although Markov processes are known to be suitable for representing style, they are difficult to control in order to satisfy non-local properties, such as structural constraints, that require long distance modeling. The framework of Constrained Markov Processes allows to precisely generate texts that are consistent with a corpus, while being controllable in terms of rhymes and meter. Controlled Markov processes consist in reformulating Markov processes in the context of constraint satisfaction. The thesis describes how to represent stylistic and structural properties in terms of constraints in this framework and how this approach can be used for the generation of lyrics in the style of 60 differents authors An evaluation of the desctibed method is provided by comparing it to both pure Markov and pure constraint-based approaches. Finally the thesis describes the implementation of an augmented text editor, called Perec. Perec is intended to improve creativity, by helping the user to write lyrics and poetry, exploiting the techniques presented so far.
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MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks
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The research and the activities presented in the following thesis report have been led at the California Polytechnic State University (US) under the supervision of Prof. Jordi Puig Suari. The objective of the research has been the study of magnetic actuators for nanosatellite attitude control, called magnetorquer. Theese actuators are generally divided in three different kinds: air core torquer, embedded coil and torquerod. In a first phase of the activity, each technology has been analyzed, defining advantages and disadvantages, determining manufacturing procedures and creating mathematical model and designing equation. Dimensioning tools have been then implemented in numerical software to create an instrument that permits to determine the optimal configuration for defined requirements and constraints. In a second phase of the activities the models created have been validated exploiting prototypes and proper instruments for measurements. The instruments and the material exploited for experiments and prototyping have been provided by the PolySat and CubeSat laboratories. The results obtained led to the definition of a complete designing tool and procedure for nanosatellite magnetic actuators, introducing a cost analysis for each kind of solution. The models and the tools have been maintained fully parametric in order to offer a universal re-scalable instrument for satellite of different dimension class.
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We report molybdenum isotope compositions and concentrations in water samples from a variety of river catchment profiles in order to investigate the influence of anthropogenic contamination, catchment geology, within-river precipitation, and seasonal river flow variations on riverine molybdenum. Our results show that the observed variations in δ98/95Mo from 0‰ to 1.9‰ are primarily controlled by catchment lithology, particularly by weathering of sulfates and sulfides. Erosion in catchments dominated by wet-based glaciers leads to very high dissolved molybdenum concentrations. In contrast, anthropogenic inputs affect neither the concentration nor the isotopic composition of dissolved molybdenum in the rivers studied here. Seasonal variations are also quite muted. The finding that catchment geology exerts the primary control on the delivery of molybdenum to seawater indicates that the flux and isotope composition of molybdenum to seawater has likely varied in the geologic past.
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This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.
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OBJECTIVE: To review trial design issues related to control groups. DESIGN: Review of the literature with specific reference to critical care trials. MAIN RESULTS AND CONCLUSIONS: Performing randomized controlled trials in the critical care setting presents specific problems: studies include patients with rapidly lethal conditions, the majority of intensive care patients suffer from syndromes rather than from well-definable diseases, the severity of such syndromes cannot be precisely assessed, and the treatment consists of interacting therapies. Interactions between physiology, pathophysiology, and therapies are at best marginally understood and may have a major impact on study design and interpretation of results. Selection of the right control group is crucial for the interpretation and clinical implementation of results. Studies comparing new interventions with current ones or different levels of current treatments have the problem of the necessity of defining "usual care." Usual care controls without any constraints typically include substantial heterogeneity. Constraints in the usual therapy may help to reduce some variation. Inclusion of unrestricted usual care groups may help to enhance safety. Practice misalignment is a novel problem in which patients receive a treatment that is the direct opposite of usual care, and occurs when fixed-dose interventions are used in situations where care is normally titrated. Practice misalignment should be considered in the design and interpretation of studies on titrated therapies.
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Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.
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In a world characterized by increasing pressure from financial and product markets, the question of how exogenous constraints affect internal coordination and control processes has become increasingly important. This experiment investigates how two exogenous constraints that superiors can face in budget negotiation settings, increased opportunity costs and financial pressure to meet unit targets, affect budget negotiations and subordinate effort. The results show that both constraints induce more cooperation, but in different ways. Financial pressure on the superior leads to more cooperative negotiation behavior by superiors and subordinates than increased opportunity costs. Specifically, subordinates do not take advantage of the superior's increased financial pressure to enforce lower budgets. After negotiation, both constraints strongly mitigate the negative effects of superior budget imposition on subordinate effort because exogenous constraints eliminate the effect of procedural fairness considerations on subordinate effort.