875 resultados para Continuous constraint programming
Resumo:
Aluminum sheets are currently produced by the direct-chill process (DC). The need for low-cost aluminum sheets is a challenge for the development of new materials produced by the twin roll caster (TRC) process. It is expected that sheets produced from these different casting procedures will differ in their microstructure. These differences in microstructure and in the crystallographic texture have great impact on sheet mechanical properties and formability. The present study investigated microstructure and evaluated texture of two strips of Al-Mn-Fe-Si (3003) aluminum alloy produced by TRC and by hot-rolling processes. It was possible to notice that the microstructure, morphology, and grain size of the TRC sample were more homogenous than those found in hot-rolled samples. Both strips, obtained by the two processes, showed strong texture gradient across the thickness.
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This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.
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This contribution describes the development of a continuous emulsion copolymerization processs for vinyl acetate and n-butyl acrylate in a tubular reactor. Special features of this reactor include the use of oscillatory (pulsed) flow and internals (sieve plates) to prevent polymer fouling and promote good radial mixing, along with a controlled amount of axial mixing. The copolymer system studied (vinyl acetate and butyl acrylate) is strongly prone to composition drift due to very different reactivity ratios. An axially dispersed plug flow model, based on classical free radical copolymerization kinetics, was developed for this process and used successfully to optimize the lateral feeding profile to reduce compositional drift. An energy balance was included in the model equations to predict the effect of temperature variations on the process. The model predictions were validated with experimental data for monomer conversion, copolymer composition, average particle size, and temperature measured along the reactor length.
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This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.
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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.
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The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.
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This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.
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We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.
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This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.
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The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.
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Carbon dioxide released from alcoholic fermentation accounts for 33% of the whole CO(2) involved in the use of ethanol as fuel derived from glucose. As Arthrospira platensis can uptake this greenhouse gas, this study evaluates the use of the CO(2) released from alcoholic fermentation for the production of Arthrospira platensis. For this purpose, this cyanobacterium was cultivated in continuous process using urea as nitrogen source, either using CO(2) from alcoholic fermentation, without any treatment, or using pure CO(2) from cylinder. The experiments were carried out at 120 mu mol photons m(-2) s(-1) in tubular photobioreactor at different dilution rates (0.2 <= D <= 0.8 d(-1)). Using CO(2) from alcoholic fermentation, maximum steady-state cell concentration (2661 +/- 71 mg L(-1)) was achieved at D 0.2 d(-1), whereas higher dilution rate (0.6 d(-1)) was needed to maximize cell productivity (839 mg L(-1) d(-1)). This value was 10% lower than the one obtained with pure CO(2), and there was no significant difference in the biomass protein content. With D 0.8 d(-1), it was possible to obtain 56% +/- 1.5% and 50% +/- 1.2% of protein in the dry biomass, using pure CO(2) and CO(2) from alcoholic fermentation, respectively. These results demonstrate that the use of such cost free CO(2) from alcoholic fermentation as carbon source, associated with low cost nitrogen source, may be a promising way to reduce costs of continuous cultivation of photosynthetic microorganisms, contributing at the same time to mitigate the greenhouse effect. (C) 2011 American Institute of Chemical Engineers Biotechnol. Prog., 27: 650-656, 2011
Resumo:
The ascorbate oxidase is the enzyme used to determine the content of ascorbic acid in the pharmaceutical and food industries and clinics analyses. The techniques currently used for the purification of this enzyme raise its production cost. Thus, the development of alternative processes and with the potential to reduce costs is interesting. The application of aqueous two-phase system is proposed as an alternative to purification because it enables good separation of biomolecules. The objective of this study was to determine the conditions to continuously pre-purify the enzyme ascorbate oxidase by an aqueous two-phase system (PEG/citrate) using rotating column provided with perforated discs. Under the best conditions (20,000 g/mol PEG molar mass, 10% PEG concentration, and 25% citrate concentration), the system showed satisfactory results (partition coefficient, 3.35; separation efficiency, 54.98%; and purification factor, 1.46) and proved suitable for the pre-purification of ascorbate oxidase in continuous process.
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A 2(3-1) factorial experimental design was used to evaluate the performance of a perforated rotating disc contactor to extract alpha-toxin from the fermented broth of Clostridium perfringens Type A by aqueous two-phase system of polyethylene glycol-phosphate salts. The influence of three independent variables, specifically the dispersed phase flowrate, the continuous phase flowrate and the disc rotational speed, was investigated on the hold up, the mass transfer coefficient, the separation efficiency and the purification factor, taken as the response variables. The optimum dispersed phase flowrate was 3.0 mL/min for all these responses. Besides, maximum values of hold up (0.80), separation efficiency (0. 10) and purification factor (2.4) were obtained at this flowrate using the lowest disc rotational speed (35 rpm), while the optimum mass transfer coefficient (0. 165 h(-1)) was achieved at the highest agitation level (140 rpm). The results of this study demonstrated that the dispersed phase flowrate strongly influenced the performance of PRDC, in that both the mass transfer coefficient and hold up increased with this parameter. (c) 2007 Elsevier B. V. All rights reserved.
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These notes follow on from the material that you studied in CSSE1000 Introduction to Computer Systems. There you studied details of logic gates, binary numbers and instruction set architectures using the Atmel AVR microcontroller family as an example. In your present course (METR2800 Team Project I), you need to get on to designing and building an application which will include such a microcontroller. These notes focus on programming an AVR microcontroller in C and provide a number of example programs to illustrate the use of some of the AVR peripheral devices.
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The present study details new turbulence field measurements conducted continuously at high frequency for 50 hours in the upper zone of a small subtropical estuary with semi-diurnal tides. Acoustic Doppler velocimetry was used, and the signal was post-processed thoroughly. The suspended sediment concentration wad further deduced from the acoustic backscatter intensity. The field data set demonstrated some unique flow features of the upstream estuarine zone, including some low-frequency longitudinal oscillations induced by internal and external resonance. A striking feature of the data set is the large fluctuations in all turbulence properties and suspended sediment concentration during the tidal cycle. This feature has been rarely documented.