969 resultados para Partially decentralized system
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This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.
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This work is a continuation of our efforts to quantify the irregular scalar stress signals from the Ananthakrishna model for the Portevin-Le Chatelier instability observed under constant strain rate deformation conditions. Stress related to the spatial average of the dislocation activity is a dynamical variable that also determines the time evolution of dislocation densities. We carry out detailed investigations on the nature of spatiotemporal patterns of the model realized in the form of different types of dislocation bands seen in the entire instability domain and establish their connection to the nature of stress serrations. We then characterize the spatiotemporal dynamics of the model equations by computing the Lyapunov dimension as a function of the drive parameter. The latter scales with the system size only for low strain rates, where isolated dislocation bands are seen, and at high strain rates, where fully propagating bands are seen. At intermediate applied strain rates corresponding to the partially propagating bands, the Lyapunov dimension exhibits two distinct slopes, one for small system sizes and another for large. This feature is rationalized by demonstrating that the spatiotemporal patterns for small system sizes are altered from the partially propagating band types to isolated burst type. This in turn allows us to reconfirm that low-dimensional chaos is projected from the stress signals as long as there is a one-to-one correspondence between the bursts of dislocation bands and the stress drops. We then show that the stress signals in the regime of partially to fully propagative bands have features of extensive chaos by calculating the correlation dimension density. We also show that the correlation dimension density also depends on the system size. A number of issues related to the system size dependence of the Lyapunov dimension density and the correlation dimension density are discussed.
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In this study we determined the molecular mechanisms of how homocysteine differentially affects receptor activator of nuclear factor-kappa B ligand (RANKL) and osteoprotegerin (OPG) synthesis in the bone. The results showed that oxidative stress induced by homocysteine deranges insulin-sensitive FOXO1 and MAP kinase signaling cascades to decrease OPG and increase RANKL synthesis in osteoblast cultures. We observed that downregulation of insulin/FOXO1 and p38 MAP kinase signaling mechanisms due to phosphorylation of protein phosphatase 2 A (PP2A) was the key event that inhibited OPG synthesis in homocysteine-treated osteoblast cultures. siRNA knockdown experiments confirmed that FOXO1 is integral to OPG and p38 synthesis. Conversely homocysteine increased RANKL synthesis in osteoblasts through c-Jun/JNK MAP kinase signaling mechanisms independent of FOXO1. In the rat bone milieu, high-methionine diet-induced hyperhomocysteinemia lowered FOXO1 and OPG expression and increased synthesis of proresorptive and inflammatory cytokines such as RANKL, M-CSF, IL-1 alpha, IL-1 beta, G-CSF, GM-CSF, MIP-1 alpha, IFN-gamma, IL-17, and TNF-alpha. Such pathophysiological conditions were exacerbated by ovariectomy. Lowering the serum homocysteine level by a simultaneous supplementation with N-acetylcysteine improved OPG and FOXO1 expression and partially antagonized RANKL and proresorptive cytokine synthesis in the bone milieu. These results emphasize that hyperhomocysteinemia alters the redox regulatory mechanism in the osteoblast by activating PP2A and deranging FOXO1 and MAPK signaling cascades, eventually shifting the OPG:RANKL ratio toward increased osteoclast activity and decreased bone quality (C) 2013 Elsevier Inc. All rights reserved.
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The partially exfoliated and reduced graphite oxide (PE-RGO) is prepared by low temperature thermal exfoliation of graphite oxide under air atmosphere. A symmetric carbon/carbon supercapacitor is studied in a Na2SO4 aqueous electrolyte. The discharge capacitance is 92 F g(-1), when symmetric cell is cycled between the potential ranges from 0 to 1.6 V. This system demonstrates a stable charge/discharge cycle behavior up to 3000 cycles when the cell is operated at a voltage window of 1.6 V. The utilization ratio of potential window is 90% for this system is attributed to the more negative value of electrodes potential when the cell voltage is set to 0 V. The low-temperature exfoliation approach is convenient for mass production of graphenes at low cost and it can be used as electrode material for energy storage applications. (C) 2014 Elsevier Ltd. All rights reserved.
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Diffuse optical tomography (DOT) using near-infrared light is a promising tool for non-invasive imaging of deep tissue. This technique is capable of quantitative reconstruction of absorption (mu(a)) and scattering coefficient (mu(s)) inhomogeneities in the tissue. The rationale for reconstructing the optical property map is that the absorption coefficient variation provides diagnostic information about metabolic and disease states of the tissue. The aim of DOT is to reconstruct the internal tissue cross section with good spatial resolution and contrast from noisy measurements non-invasively. We develop a region-of-interest scanning system based on DOT principles. Modulated light is injected into the phantom/tissue through one of the four light emitting diode sources. The light traversing through the tissue gets partially absorbed and scattered multiple times. The intensity and phase of the exiting light are measured using a set of photodetectors. The light transport through a tissue is diffusive in nature and is modeled using radiative transfer equation. However, a simplified model based on diffusion equation (DE) can be used if the system satisfies following conditions: (a) the optical parameter of the inhomogeneity is close to the optical property of the background, and (b) mu(s) of the medium is much greater than mu(a) (mu(s) >> mu(a)). The light transport through a highly scattering tissue satisfies both of these conditions. A discrete version of DE based on finite element method is used for solving the inverse problem. The depth of probing light inside the tissue depends on the wavelength of light, absorption, and scattering coefficients of the medium and the separation between the source and detector locations. Extensive simulation studies have been carried out and the results are validated using two sets of experimental measurements. The utility of the system can be further improved by using multiple wavelength light sources. In such a scheme, the spectroscopic variation of absorption coefficient in the tissue can be used to arrive at the oxygenation changes in the tissue. (C) 2016 AIP Publishing LLC.
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An n degree-of-freedom Hamiltonian system with r (1¡r¡n) independent 0rst integrals which are in involution is calledpartially integrable Hamiltonian system. A partially integrable Hamiltonian system subject to light dampings andweak stochastic excitations is called quasi-partially integrable Hamiltonian system. In the present paper, the procedures for studying the 0rst-passage failure and its feedback minimization of quasi-partially integrable Hamiltonian systems are proposed. First, the stochastic averaging methodfor quasi-partially integrable Hamiltonian systems is brie4y reviewed. Then, basedon the averagedIt ˆo equations, a backwardKolmogorov equation governing the conditional reliability function, a set of generalized Pontryagin equations governing the conditional moments of 0rst-passage time and their boundary and initial conditions are established. After that, the dynamical programming equations and their associated boundary and 0nal time conditions for the control problems of maximization of reliability andof maximization of mean 0rst-passage time are formulated. The relationship between the backwardKolmogorov equation andthe dynamical programming equation for reliability maximization, andthat between the Pontryagin equation andthe dynamical programming equation for maximization of mean 0rst-passage time are discussed. Finally, an example is worked out to illustrate the proposed procedures and the e9ectiveness of feedback control in reducing 0rst-passage failure.
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ICECCS 2010
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Modern robots are increasingly expected to function in uncertain and dynamically challenging environments, often in proximity with humans. In addition, wide scale adoption of robots requires on-the-fly adaptability of software for diverse application. These requirements strongly suggest the need to adopt formal representations of high level goals and safety specifications, especially as temporal logic formulas. This approach allows for the use of formal verification techniques for controller synthesis that can give guarantees for safety and performance. Robots operating in unstructured environments also face limited sensing capability. Correctly inferring a robot's progress toward high level goal can be challenging.
This thesis develops new algorithms for synthesizing discrete controllers in partially known environments under specifications represented as linear temporal logic (LTL) formulas. It is inspired by recent developments in finite abstraction techniques for hybrid systems and motion planning problems. The robot and its environment is assumed to have a finite abstraction as a Partially Observable Markov Decision Process (POMDP), which is a powerful model class capable of representing a wide variety of problems. However, synthesizing controllers that satisfy LTL goals over POMDPs is a challenging problem which has received only limited attention.
This thesis proposes tractable, approximate algorithms for the control synthesis problem using Finite State Controllers (FSCs). The use of FSCs to control finite POMDPs allows for the closed system to be analyzed as finite global Markov chain. The thesis explicitly shows how transient and steady state behavior of the global Markov chains can be related to two different criteria with respect to satisfaction of LTL formulas. First, the maximization of the probability of LTL satisfaction is related to an optimization problem over a parametrization of the FSC. Analytic computation of gradients are derived which allows the use of first order optimization techniques.
The second criterion encourages rapid and frequent visits to a restricted set of states over infinite executions. It is formulated as a constrained optimization problem with a discounted long term reward objective by the novel utilization of a fundamental equation for Markov chains - the Poisson equation. A new constrained policy iteration technique is proposed to solve the resulting dynamic program, which also provides a way to escape local maxima.
The algorithms proposed in the thesis are applied to the task planning and execution challenges faced during the DARPA Autonomous Robotic Manipulation - Software challenge.
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X-ray phase imaging with illumination by a partially coherent source with a setup similar to in-line holography is considered. Using the optical transform function, we consider the effects of partial coherence on this x-ray phase imaging for a weak phase object. The optimal contrast and the resolution of phase imaging are analyzed. As the coherence decreases, the imaging contrast and the optimal contrast frequency decrease, and the resolution degrades. It is shown that this contrast-enhanced phase-imaging method can be regarded as a linear bandpass filter and that the bandwidth and the image contrast are changeable. The frequency property of the imaging system can be improved if an incoherent x-ray source with the proper shape is used. (C) 1999 Optical Society of America.
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The theoretical model of direct diffraction phase-contrast imaging with partially coherent x-ray source is expressed by an operator of multiple integral. It is presented that the integral operator is linear. The problem of its phase retrieval is described by solving an operator equation of multiple integral. It is demonstrated that the solution of the phase retrieval is unstable. The numerical simulation is performed and the result validates that the solution of the phase retrieval is unstable.
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Part I:
The earth's core is generally accepted to be composed primarily of iron, with an admixture of other elements. Because the outer core is observed not to transmit shear waves at seismic frequencies, it is known to be liquid or primarily liquid. A new equation of state is presented for liquid iron, in the form of parameters for the 4th order Birch-Murnaghan and Mie-Grüneisen equations of state. The parameters were constrained by a set of values for numerous properties compiled from the literature. A detailed theoretical model is used to constrain the P-T behavior of the heat capacity, based on recent advances in the understanding of the interatomic potentials for transition metals. At the reference pressure of 105 Pa and temperature of 1811 K (the normal melting point of Fe), the parameters are: ρ = 7037 kg/m3, KS0 = 110 GPa, KS' = 4.53, KS" = -.0337 GPa-1, and γ = 2.8, with γ α ρ-1.17. Comparison of the properties predicted by this model with the earth model PREM indicates that the outer core is 8 to 10 % less dense than pure liquid Fe at the same conditions. The inner core is also found to be 3 to 5% less dense than pure liquid Fe, supporting the idea of a partially molten inner core. The density deficit of the outer core implies that the elements dissolved in the liquid Fe are predominantly of lower atomic weight than Fe. Of the candidate light elements favored by researchers, only sulfur readily dissolves into Fe at low pressure, which means that this element was almost certainly concentrated in the core at early times. New melting data are presented for FeS and FeS2 which indicate that the FeS2 is the S-hearing liquidus solid phase at inner core pressures. Consideration of the requirement that the inner core boundary be observable by seismological means and the freezing behavior of solutions leads to the possibility that the outer core may contain a significant fraction of solid material. It is found that convection in the outer core is not hindered if the solid particles are entrained in the fluid flow. This model for a core of Fe and S admits temperatures in the range 3450K to 4200K at the top of the core. An all liquid Fe-S outer core would require a temperature of about 4900 K at the top of the core.
Part II.
The abundance of uses for organic compounds in the modern world results in many applications in which these materials are subjected to high pressures. This leads to the desire to be able to describe the behavior of these materials under such conditions. Unfortunately, the number of compounds is much greater than the number of experimental data available for many of the important properties. In the past, one approach that has worked well is the calculation of appropriate properties by summing the contributions from the organic functional groups making up molecules of the compounds in question. A new set of group contributions for the molar volume, volume thermal expansivity, heat capacity, and the Rao function is presented for functional groups containing C, H, and O. This set is, in most cases, limited in application to low molecular liquids. A new technique for the calculation of the pressure derivative of the bulk modulus is also presented. Comparison with data indicates that the presented technique works very well for most low molecular hydrocarbon liquids and somewhat less well for oxygen-bearing compounds. A similar comparison of previous results for polymers indicates that the existing tabulations of group contributions for this class of materials is in need of revision. There is also evidence that the Rao function contributions for polymers and low molecular compounds are somewhat different.
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This thesis describes investigations of two classes of laboratory plasmas with rather different properties: partially ionized low pressure radiofrequency (RF) discharges, and fully ionized high density magnetohydrodynamically (MHD)-driven jets. An RF pre-ionization system was developed to enable neutral gas breakdown at lower pressures and create hotter, faster jets in the Caltech MHD-Driven Jet Experiment. The RF plasma source used a custom pulsed 3 kW 13.56 MHz RF power amplifier that was powered by AA batteries, allowing it to safely float at 4-6 kV with the cathode of the jet experiment. The argon RF discharge equilibrium and transport properties were analyzed, and novel jet dynamics were observed.
Although the RF plasma source was conceived as a wave-heated helicon source, scaling measurements and numerical modeling showed that inductive coupling was the dominant energy input mechanism. A one-dimensional time-dependent fluid model was developed to quantitatively explain the expansion of the pre-ionized plasma into the jet experiment chamber. The plasma transitioned from an ionizing phase with depressed neutral emission to a recombining phase with enhanced emission during the course of the experiment, causing fast camera images to be a poor indicator of the density distribution. Under certain conditions, the total visible and infrared brightness and the downstream ion density both increased after the RF power was turned off. The time-dependent emission patterns were used for an indirect measurement of the neutral gas pressure.
The low-mass jets formed with the aid of the pre-ionization system were extremely narrow and collimated near the electrodes, with peak density exceeding that of jets created without pre-ionization. The initial neutral gas distribution prior to plasma breakdown was found to be critical in determining the ultimate jet structure. The visible radius of the dense central jet column was several times narrower than the axial current channel radius, suggesting that the outer portion of the jet must have been force free, with the current parallel to the magnetic field. The studies of non-equilibrium flows and plasma self-organization being carried out at Caltech are relevant to astrophysical jets and fusion energy research.
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The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.
The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.
We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.
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Esta dissertação concentra suas investigações nas contramedidas do direito internacional geral e da Organização Mundial do Comércio (OMC). No âmbito do direito internacional, estudou-se a essência política da sociedade internacional descentralizada, bem como a tendência do processo de fragmentação do direito internacional em direção a regimes mais regulados pelo direito. Além disso, investigou-se a tentativa de ampliação da normatização das contramedidas por meio do Projeto de Artigos sobre Responsabilidade Internacional do Estado de 2001. No âmbito do regime especial da OMC, analisou-se o maior adensamento jurídico das contramedidas como ponto culminante na fase de implementação das decisões no sistema de solução de controvérsias da OMC. Com base na avaliação sobre a necessidade de reforma do instituto das contramedidas da OMC, foram pesquisadas as principais propostas para sua modificação, buscando-se identificar a tentativa de redução do espaço político. A hipótese deste trabalho partiu da afirmação sobre a existência de uma tendência evolutiva no direito internacional geral e na OMC no que tange ao aumento da juridicidade do instituto das contramedidas. Entretanto, essa hipótese confirmou-se apenas parcialmente, pois a tentativa de aprimorar a regulamentação jurídica do instituto das contramedidas ocorre em meio à permanência de elementos políticos.
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A propriedade de auto-cura, em redes inteligente de distribuição de energia elétrica, consiste em encontrar uma proposta de reconfiguração do sistema de distribuição com o objetivo de recuperar parcial ou totalmente o fornecimento de energia aos clientes da rede, na ocorrência de uma falha na rede que comprometa o fornecimento. A busca por uma solução satisfatória é um problema combinacional cuja complexidade está ligada ao tamanho da rede. Um método de busca exaustiva se torna um processo muito demorado e muitas vezes computacionalmente inviável. Para superar essa dificuldade, pode-se basear nas técnicas de geração de árvores de extensão mínima do grafo, representando a rede de distribuição. Porém, a maioria dos estudos encontrados nesta área são implementações centralizadas, onde proposta de reconfiguração é obtida por um sistema de supervisão central. Nesta dissertação, propõe-se uma implementação distribuída, onde cada chave da rede colabora na elaboração da proposta de reconfiguração. A solução descentralizada busca uma redução no tempo de reconfiguração da rede em caso de falhas simples ou múltiplas, aumentando assim a inteligência da rede. Para isso, o algoritmo distribuído GHS é utilizado como base na elaboração de uma solução de auto-cura a ser embarcada nos elementos processadores que compõem as chaves de comutação das linhas da rede inteligente de distribuição. A solução proposta é implementada utilizando robôs como unidades de processamento que se comunicam via uma mesma rede, constituindo assim um ambiente de processamento distribuído. Os diferentes estudos de casos testados mostram que, para redes inteligentes de distribuição compostas por um único alimentador, a solução proposta obteve sucesso na reconfiguração da rede, indiferentemente do número de falhas simultâneas. Na implementação proposta, o tempo de reconfiguração da rede não depende do número de linhas nela incluídas. A implementação apresentou resultados de custo de comunicação e tempo dentro dos limites teóricos estabelecidos pelo algoritmo GHS.