994 resultados para Optimal regulation


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To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a pre-synthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system. Copyright (C) 2013 John Wiley & Sons, Ltd.

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Neste trabalho é analisada a relação entre um regulador e uma empresa petrolífera. Há várias incertezas inerentes à essa relação e o trabalho se concentra nos efeitos da assimetria de informação. Fazemos a caracterização da regulação ótima sob informação assimétrica, quando o regulador deve desenhar um mecanismo que induz a firma a revelar corretamente sua informação privada. No caso em que a rma não pode se comprometer a não romper o acordo, mostramos que o regulador pode não implementar o resultado ótimo que é obtido sob informação completa. Nesse caso, o regulador não consegue compartilhar os riscos com a firma de forma ótima. Por fim, é apresentado um exemplo, em que mostramos que a condição de Spence-Mirrlees (SMC) pode não valer. Esse resultado aparece de forma natural no modelo.

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把小流域水文生态研究 ,分解为小流域水分行为、生态效应及其优化调控研究 3个方面。在分析国内外研究现状与问题的基础上 ,指出了其需要系统加以探讨的若干内容 ,认为由此可构建流域水文生态学的基本框架 ,进而发展流域水文生态学。

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In the midst of health care reform, Colombia has succeeded in increasing health insurance coverage and the quality of health care. In spite of this, efficiency continues to be a matter of concern, and small-area variations in health care are one of the plausible causes of such inefficiencies. In order to understand this issue, we use individual data of all births from a Contributory-Regimen insurer in Colombia. We perform two different specifications of a multilevel logistic regression model. Our results reveal that hospitals account for 20% of variation on the probability of performing cesarean sections. Geographic area only explains 1/3 of the variance attributable to the hospital. Furthermore, some variables from both demand and supply sides are found to be also relevant on the probability of undergoing cesarean sections. This paper contributes to previous research by using a hierarchical model and by defining hospitals as cluster. Moreover, we also include clinical and supply induced demand variables.

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In an early paper, Cavalcanti and Wallace (2001) showed, using a computable version of Cavalcanti-Wallace model (CW-1999), that optimal regulation induces banks to pay interests, instead of contracting the money supply in an inside money allocation. Here, we generalize CW in two fashions, assuming inside money allocations, so that banks are supposed to issue money as they find a potential producer wishing to produce. The first generalization allows for seasonality due to real shocks on preferences with persistence and for monetary policy improvement. We found an asymmetric path for interest rates when constraints matter, even when shocks are independent. The second generalization allows for bank competition, in the sense that banks can choose between two different banking nets. We proof the existence of simple stable and unstable equilibria and also verify the existence of multiple equilibria.

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La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Actualmente existen dos tipos de terapias aplicada en tejido subcutáneo: mediante inyección múltiple realizada con plumas, y la otra es mediante infusión continua de insulina por bomba (CSII). El mayor problema de esta terapia son los retardos por la absorción, tanto de los carbohidratos como de la insulina, y los retardos introducidos por el sensor subcutáneo de glucosa que mide la glucosa del líquido intersticial, lo deseable es controlar la glucosa en sangre. Para intentar independizar al paciente de su enfermedad se está trabajando en el desarrollo del páncreas endocrino artificial (PEA) que dotaría al paciente de una bomba de insulina, un sensor de glucosa y un controlador, el cual se encargaría de la toma de decisiones de las infusiones de insulina. Este proyecto persigue el diseño de un regulador en modo de funcionamiento en CL, con el objetivo de conseguir una regulación óptima del nivel de glucosa en sangre. El diseño de dicho regulador va a ser acometido utilizando la teoría del control por modelo interno (IMC). Esta teoría se basa en la idea de que es necesario realimentar la respuesta de un modelo aproximado del proceso que se quiere controlar. La salida del modelo, comparada con la del proceso real nos da la incertidumbre del modelo de la planta, frente a la planta real. Dado que según la teoría del modelo interno, estas diferencias se dan en las altas frecuencias, la teoría IMC propone un filtro paso bajo como regulador en serie con la inversa del modelo de la planta para conseguir el comportamiento deseado. Además se pretende implementar un Predictor Smith para minimizar los efectos del retardo de la medida del sensor. En el proyecto para conseguir la viabilidad del PEA se ha adaptado el controlador IMC clásico utilizando las ganancias estáticas de un modelo de glucosa, a partir de la ruta subcutánea de infusión y la vía subcutánea de medida. El modo de funcionamiento del controlador en SCL mejora el rango de normoglucemia, necesitando la intervención del paciente indicando anticipadamente el momento de las ingestas al controlador. El uso de un control SCL con el Predictor de Smith mejora los resultados pues se añade al controlador una variable sobre las ingestas con la participación del paciente. ABSTRACT. Diabetes mellitus is a group of metabolic diseases in which a person has high blood sugar, due to the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. There are currently two types of therapies applied in subcutaneous tissue: the first one consists in using the intensive therapy with an insulin pen, and the other one is by continuous subcutaneous insulin infusion (CSII). The biggest problems of this therapy are the delays caused by the absorption of carbohydrates and insulin, and the delays introduced by the subcutaneous glucose sensor that measures glucose from interstitial fluid, it is suitable to control glucose blood. To try to improve these patients quality of life, work is being done on the development of an artificial endocrine pancreas (PEA) consisting of a subcutaneous insulin pump, a subcutaneous glucose sensor and an algorithm of glucose control, which would calculate the bolus that the pump would infuse to patient. This project aims to design a controller for closed-loop therapy, with the objective of obtain an optimal regulation of blood glucose level. The design of this controller will be formed using the theory of internal model control (IMC). This theory is based on the uncertainties given by a model to feedback the system control. Output model, in comparison with the actual process gives the uncertainty of the plant model, compared to the real plant. Since the theory of the internal model, these differences occur at high frequencies, the theory proposes IMC as a low pass filter regulator in series with the inverse model of the plant to get the required behavior. In addition, it will implement a Smith Predictor to minimize the effects of the delay measurement sensor. The project for the viability of PEA has adapted the classic IMC controller using the gains static of glucose model from the subcutaneous infusion and subcutaneous measuring. In simulation the SemiClosed-Loop controller get on the normoglycemia range, requiring patient intervention announce the bolus priming connected to intakes. Using an SCL control with the Smith Predictor improves the outcome because a variable about intakes is added to the controller through patient intervention.

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The degradation rate of 3-hydroxy-3-methylglutaryl CoA reductase (HMG-R), a key enzyme of the mevalonate pathway, is regulated through a feedback mechanism by the mevalonate pathway. To discover the intrinsic determinants involved in the regulated degradation of the yeast HMG-R isozyme Hmg2p, we replaced small regions of the Hmg2p transmembrane domain with the corresponding regions from the other, stable yeast HMG-R isozyme Hmg1p. When the first 26 amino acids of Hmg2p were replaced with the same region from Hmg1p, Hmg2p was stabilized. The stability of this mutant was not due to mislocalization, but rather to an inability to be recognized for degradation. When amino acid residues 27–54 of Hmg2p were replaced with those from Hmg1p, the mutant was still degraded, but its degradation rate was poorly regulated. The degradation of this mutant was still dependent on the first 26 amino acid residues and on the function of the HRD genes. These mutants showed altered ubiquitination levels that were well correlated with their degradative phenotypes. Neither determinant was sufficient to impart regulated degradation to Hmg1p. These studies provide evidence that there are sequence determinants in Hmg2p necessary for degradation and optimal regulation, and that independent processes may be involved in Hmg2p degradation and its regulation.

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The idea of spacecraft formations, flying in tight configurations with maximum baselines of a few hundred meters in low-Earth orbits, has generated widespread interest over the last several years. Nevertheless, controlling the movement of spacecraft in formation poses difficulties, such as in-orbit high-computing demand and collision avoidance capabilities, which escalate as the number of units in the formation is increased and complicated nonlinear effects are imposed to the dynamics, together with uncertainty which may arise from the lack of knowledge of system parameters. These requirements have led to the need of reliable linear and nonlinear controllers in terms of relative and absolute dynamics. The objective of this thesis is, therefore, to introduce new control methods to allow spacecraft in formation, with circular/elliptical reference orbits, to efficiently execute safe autonomous manoeuvres. These controllers distinguish from the bulk of literature in that they merge guidance laws never applied before to spacecraft formation flying and collision avoidance capacities into a single control strategy. For this purpose, three control schemes are presented: linear optimal regulation, linear optimal estimation and adaptive nonlinear control. In general terms, the proposed control approaches command the dynamical performance of one or several followers with respect to a leader to asymptotically track a time-varying nominal trajectory (TVNT), while the threat of collision between the followers is reduced by repelling accelerations obtained from the collision avoidance scheme during the periods of closest proximity. Linear optimal regulation is achieved through a Riccati-based tracking controller. Within this control strategy, the controller provides guidance and tracking toward a desired TVNT, optimizing fuel consumption by Riccati procedure using a non-infinite cost function defined in terms of the desired TVNT, while repelling accelerations generated from the CAS will ensure evasive actions between the elements of the formation. The relative dynamics model, suitable for circular and eccentric low-Earth reference orbits, is based on the Tschauner and Hempel equations, and includes a control input and a nonlinear term corresponding to the CAS repelling accelerations. Linear optimal estimation is built on the forward-in-time separation principle. This controller encompasses two stages: regulation and estimation. The first stage requires the design of a full state feedback controller using the state vector reconstructed by means of the estimator. The second stage requires the design of an additional dynamical system, the estimator, to obtain the states which cannot be measured in order to approximately reconstruct the full state vector. Then, the separation principle states that an observer built for a known input can also be used to estimate the state of the system and to generate the control input. This allows the design of the observer and the feedback independently, by exploiting the advantages of linear quadratic regulator theory, in order to estimate the states of a dynamical system with model and sensor uncertainty. The relative dynamics is described with the linear system used in the previous controller, with a control input and nonlinearities entering via the repelling accelerations from the CAS during collision avoidance events. Moreover, sensor uncertainty is added to the control process by considering carrier-phase differential GPS (CDGPS) velocity measurement error. An adaptive control law capable of delivering superior closed-loop performance when compared to the certainty-equivalence (CE) adaptive controllers is finally presented. A novel noncertainty-equivalence controller based on the Immersion and Invariance paradigm for close-manoeuvring spacecraft formation flying in both circular and elliptical low-Earth reference orbits is introduced. The proposed control scheme achieves stabilization by immersing the plant dynamics into a target dynamical system (or manifold) that captures the desired dynamical behaviour. They key feature of this methodology is the addition of a new term to the classical certainty-equivalence control approach that, in conjunction with the parameter update law, is designed to achieve adaptive stabilization. This parameter has the ultimate task of shaping the manifold into which the adaptive system is immersed. The performance of the controller is proven stable via a Lyapunov-based analysis and Barbalat’s lemma. In order to evaluate the design of the controllers, test cases based on the physical and orbital features of the Prototype Research Instruments and Space Mission Technology Advancement (PRISMA) are implemented, extending the number of elements in the formation into scenarios with reconfigurations and on-orbit position switching in elliptical low-Earth reference orbits. An extensive analysis and comparison of the performance of the controllers in terms of total Δv and fuel consumption, with and without the effects of the CAS, is presented. These results show that the three proposed controllers allow the followers to asymptotically track the desired nominal trajectory and, additionally, those simulations including CAS show an effective decrease of collision risk during the performance of the manoeuvre.

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Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

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Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties. Copyright (C) 2009 John Wiley & Sons, Ltd.

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This paper sets out to assess the workability of the regulation currently in force in the European anchovy fishery of the VIII division. Particular attention is paid to the importance of the institutional regime in the allocation of natural resources. The study uses a bio-economic approach and takes into account the fact that, not only the European Union and the individual countries involved, but also some of the resource users or appropriators intervene in its management. In order to compare the effectiveness of the rules which, at the various levels, have been set up to restrict exploitation of the resource, the anchovy fishery is simulated in two extreme situations: open access and sole ownership. The results obtained by effective management will then be contrasted with those obtained from the maximum and zero profit objectives related with the two above-mentioned scenarios. Thus, if the real data come close to those derived from the sole ownership model it will have to be acknowledged that the rules at present in force are optimal. If, on the other hand, the situation more closely approach the results obtained from the open access model, we will endeavour in our conclusions to provide suggestions for economic policy measures that might improve the situation in the fishery.

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The theory of H/sup /spl infin// optimal control has the feature of minimizing the worst-case gain of an unknown disturbance input. When appropriately modified, the theory can be used to design a "switching" controller that can be applied to insulin injection for blood glucose (BG) regulation. The "switching" controller is defined by a collection of basic insulin rates and a rule that switches the insulin rates from one value to another. The rule employed an estimation of BG from noisy measurements, and the subsequent optimization of a performance index that involves the solution of a "jump" Riccati differential equation and a discrete-time dynamic programming equation. With an appropriate patient model, simulation studies have shown that the controller could correct BG deviation using clinically acceptable insulin delivery rates.