920 resultados para Distributed Control Problems


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In the light of first-hand data from a Beninese urban household survey in Cotonou, we investigate several motives aiming to explain participation in Rotating Savings and Credit Associations. We provide anecdotal pieces of evidence, descriptive statistics, FIML regressions and matching estimates which tend to indicate that most individuals use their participation in a rosca as a device to commit themselves to save money and to deal with self-control problems.

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Most US credit card holders revolve high-interest debt, often combined with substantial (i) asset accumulation by retirement, and (ii) low-rate liquid assets. Hyperbolic discounting can resolve only the former puzzle (Laibson et al., 2003). Bertaut and Haliassos (2002) proposed an 'accountant-shopper'framework for the latter. The current paper builds, solves, and simulates a fully-specified accountant-shopper model, to show that this framework canactually generate both types of co-existence, as well as target credit card utilization rates consistent with Gross and Souleles (2002). The benchmark model is compared to setups without self-control problems, with alternative mechanisms, and with impatient but fully rational shoppers.

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Most US credit card holders revolve high-interest debt, often combined with substantial (i) asset accumulation by retirement, and (ii) low-rate liquid assets. Hyperbolic discounting can resolve only the former puzzle (Laibson et al., 2003). Bertaut and Haliassos (2002) proposed an 'accountant-shopper'framework for the latter. The current paper builds, solves, and simulates a fully-specified accountant-shopper model, to show that this framework canactually generate both types of co-existence, as well as target credit card utilization rates consistent with Gross and Souleles (2002). The benchmark model is compared to setups without self-control problems, with alternative mechanisms, and with impatient but fully rational shoppers.

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We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

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Approximately 40,000 tons of deteriorated asphalt concrete has been removed from Interstate 80 in Cass County and stockpiled. Laboratory tests indicate that this material has considerable value when upgraded with new aggregate and asphalt cement. This report documents the procedures used and results obtained on an experimental recycling project. It was demonstrated that present drum mixing-recycling equipment and procedures can be used to utilize this material with satisfactory results. Laboratory analyses of material components and mixtures were performed; these analyses indicate mixture can be produced that is uniform, stable, and very closely resembles mixture produced with all virgin material. A 1700 foot long test section was constructed on US 169 in Kossuth County wherein salvaged asphalt concrete from I-80 in Cass County was utilized. The salvaged mix was blended with virgin aggregate and recycled through a modified drum mixing plant, the reprocessed mixture was satisfactorily placed 1 1/2 inches thick as a resurfacing course on an old PCC pavement. An inspection of the test section was made in December of 1978 to evaluate the performance after one full year of service. There was no evidence of rutting or shoving from traffic. The surface does, however, have a very dry and somewhat ravelled appearance. This can be related to a low asphalt content in the mix and some temperature control problems which were difficult to get fully corrected on such a short project and with a short supply of readily available materials.

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Työn tavoitteena oli kehittää automaattinen optimointijärjestelmä energiayhtiön omistamaan pieneen sähkön- ja lämmöntuotantolaitokseen (CHP-laitos). Optimointitarve perustuu energiayhtiön sähkön hankintaan sähköpörssistä, kaasun hankintahintaan, kohteen paikallisiin sähkö- ja lämpökuormituksiin ja muihin laitoksen talouteen vaikuttaviin tekijöihin. Kehitettävällä optimointijärjestelmällä ontarkoitus tulevaisuudessa hallita useita hajautetun energiantuotannon yksiköitäkeskitetysti. Työssä kehitettiin algoritmi, joka optimoi voimalaitoksen taloutta sähkötehoa säätävillä ajomalleilla ja suoralla sähköteho-ohjeella. Työssä kehitetyn algoritmin tuottamia hyötyjä selvitettiin Harjun oppimiskeskuksen CHP-laitoksen mittaushistoriatiedoilla. CHP-laitosten käytön optimointiin luotiin keskitettyyn laskentaan ja hajautettuun ohjaukseen perustuva järjestelmä. Se ohjaa CHP-laitoksia reaaliaikaisesti ja ennustaa historiatietoihin perustuvalla aikasarjamallilla laitoksen tulevaa käyttöä. Optimointijärjestelmän toimivuus ja saatu hyöty selvitettiin Harjun oppimiskeskuksen CHP-laitoksella vertaamalla mittauksista laskettua toteutunutta hyötyä optimointijärjestelmän laskemaan ennustettuun hyötyyn.

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Kansallisten rajojen yli laajentuvat yritykset kohtaavat kasvavia paineita yhtenäistää eri yksiköiden toimintatapoja, prosesseja ja järjestelmiä. Hyvin toteutettuna organisaation sisäinen integrointi voi johtaa tytäryritysten tuottavuuden parantumiseen ja strategisiin mittakaavaetuihin, kun taas huonosti toteutettuna integrointi voi johtaa lisääntyviin konflikteihin ja emoyhtiön kontrollin katoamiseen. Integroinnin kannalta Venäjälle perustettavat tytäryritykset asettavat suuria haasteita. Kasvava ja kehittyvä kansantalous on jatkuvassa muutoksessa kohti edistyneempiä ja tuottavampia toimintamalleja, mutta toisaalta yritystoiminnantaustalla vaikuttaa edelleenkin Neuvostoajan perinnöt, jotka muokkaavat yritysten johtamisrakenteita ja prosesseja. Nämä taustavaikuttajat vaikeuttavat kansainvälisen yrityksen yhtenäistämistä, mutta toisaalta tarjoavat suuria mahdollisuuksia yrityksille, jotka oppivat elämään Venäjän markkinoiden ehdoilla. Tämä tutkimus käyttää apunaan konstruktiivista tutkimustyötä ratkoakseenYIT:n Venäjälle perustettavien yritysten integrointiin liittyviä ongelmia ja mahdollisuuksia. Työn lopputuloksena syntyy oppimiseen pohjautuva integraatiostrategia ja tätä strategiaa tukeva integroinnin johtamisjärjestelmä.

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Kiristyvä kansainvälinen kilpailu pakottaa automaatiojärjestelmien valmistajat ottamaan käyttöön uusia menetelmiä, joiden avulla järjestelmien suorituskykyä ja joustavuutta saadaan parannettua. Agenttiteknologiaa on esitetty käytettäväksi olemassa olevien automaatiojärjestelmien kanssa vastaamaan automaatiolle asetettaviin uusiin haasteisiin. Agentit ovat itsenäisiä yhteisöllisiä toimijoita, jotka suorittavat niille ennalta määrättyjä tehtäviä. Ne tarjoavat yhtenäisen kehyksen kehittyneiden toimintojen toteutukselle. Agenttiteknologian avulla automaatiojärjestelmä saadaan toimimaan joustavasti ja vikasietoisesti. Tässä työssä selostetaan agenttiteknologian ajatuksia ja käsitteitä. Lisäksi selvitetään sen soveltuvuutta monimutkaisten ohjausjärjestelmien kehittämiseen ja etsitään käyttökohteita sen soveltamiselle levytehtaassa. Työssä käsitellään myös aatteita, jotka ovat johtaneet agenttiteknologian käyttöön automaatiojärjestelmissä, sekä selostetaan agenttiavusteisen esimerkkisovelluksen rakenne ja testitulokset. Tutkimuksen tuloksena löydettiin useita kohteita agenttiteknologian käytölle levytehtaassa. Esimerkkisovellus osoittaa sen sopivan hyvin kehittyneiden toimintojen toteutukseen automaatiojärjestelmissä.

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This study investigates whether incumbent audit firm-provided tax services enhance or impair the likelihood of acknowledging client companies’ low financial reporting quality. In particular, we examine the association between tax-related fees and the likelihood of timely restatements, and internal control weakness disclosures among a sample of US companies that all have misstatements in financial information. The empirical findings indicate that companies paying higher tax-related fees are less likely to disclose SOX 404 internal control weakness disclosures, implying that underlying control problems are unacknowledged when incumbent audit firm provided tax-related fees are higher. However, the findings suggest that just providing both audit and tax-related services does not have an impact on audit quality per se, but rather it is the magnitude of the tax-related fees in particular that counts. We also find some evidence suggesting that companies paying higher tax-related fees have higher likelihood of restatement lags, whereas companies paying smaller tax-related fees to their audit firm restate financial statements in a timelier manner. Overall, the findings suggest that audit scrutiny of client companies with low quality financial reporting is weaker when the magnitude of tax-related fees is higher.

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The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

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Behavioral economics has addressed interesting positive and normative questions underlying the standard rational choice theory. More recently, it suggests that, in a real world of boundedly rational agents, economists could help people to improve the quality of their choices without any harm to autonomy and freedom of choice. This paper aims to scrutinize available arguments for and against current proposals of light paternalistic interventions mainly in the domain of intertemporal choice. It argues that incorporating the notion of bounded rationality in economic analysis and empirical findings of cognitive biases and self-control problems cannot make an indisputable case for paternalism.

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Cette thèse est divisée en deux grands chapitres, dont le premier porte sur des problèmes de commande optimale en dimension un et le deuxième sur des problèmes en dimension deux ou plus. Notons bien que, dans cette thèse, nous avons supposé que le facteur temps n'intervient pas. Dans le premier chapitre, nous calculons, au début, l'équation de programmation dynamique pour la valeur minimale F de l'espérance mathématique de la fonction de coût considérée. Ensuite, nous utilisons le théorème de Whittle qui est applicable seulement si une condition entre le bruit blanc v et les termes b et q associés à la commande est satisfaite. Sinon, nous procédons autrement. En effet, un changement de variable transforme notre équation en une équation de Riccati en G= F', mais sans conditions initiales. Dans certains cas, à partir de la symétrie des paramètres infinitésimaux et de q, nous pouvons en déduire le point x' où G(x')=0. Si ce n'est pas le cas, nous nous limitons à des bonnes approximations. Cette même démarche est toujours possible si nous sommes dans des situations particulières, par exemple, lorsque nous avons une seule barrière. Dans le deuxième chapitre, nous traitons les problèmes en dimension deux ou plus. Puisque la condition de Whittle est difficile à satisfaire dans ce cas, nous essayons de généraliser les résultats du premier chapitre. Nous utilisons alors dans quelques exemples la méthode des similitudes, qui permet de transformer le problème en dimension un. Ensuite, nous proposons une nouvelle méthode de résolution. Cette dernière linéarise l'équation de programmation dynamique qui est une équation aux dérivées partielles non linéaire. Il reste à la fin à trouver les conditions initiales pour la nouvelle fonction et aussi à vérifier que les n expressions obtenues pour F sont équivalentes.

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One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

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Fujaba is an Open Source UML CASE tool project started at the software engineering group of Paderborn University in 1997. In 2002 Fujaba has been redesigned and became the Fujaba Tool Suite with a plug-in architecture allowing developers to add functionality easily while retaining full control over their contributions. Multiple Application Domains Fujaba followed the model-driven development philosophy right from its beginning in 1997. At the early days, Fujaba had a special focus on code generation from UML diagrams resulting in a visual programming language with a special emphasis on object structure manipulating rules. Today, at least six rather independent tool versions are under development in Paderborn, Kassel, and Darmstadt for supporting (1) reengineering, (2) embedded real-time systems, (3) education, (4) specification of distributed control systems, (5) integration with the ECLIPSE platform, and (6) MOF-based integration of system (re-) engineering tools. International Community According to our knowledge, quite a number of research groups have also chosen Fujaba as a platform for UML and MDA related research activities. In addition, quite a number of Fujaba users send requests for more functionality and extensions. Therefore, the 8th International Fujaba Days aimed at bringing together Fujaba develop- ers and Fujaba users from all over the world to present their ideas and projects and to discuss them with each other and with the Fujaba core development team.

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This report addresses the problem of achieving cooperation within small- to medium- sized teams of heterogeneous mobile robots. I describe a software architecture I have developed, called ALLIANCE, that facilitates robust, fault tolerant, reliable, and adaptive cooperative control. In addition, an extended version of ALLIANCE, called L-ALLIANCE, is described, which incorporates a dynamic parameter update mechanism that allows teams of mobile robots to improve the efficiency of their mission performance through learning. A number of experimental results of implementing these architectures on both physical and simulated mobile robot teams are described. In addition, this report presents the results of studies of a number of issues in mobile robot cooperation, including fault tolerant cooperative control, adaptive action selection, distributed control, robot awareness of team member actions, improving efficiency through learning, inter-robot communication, action recognition, and local versus global control.