895 resultados para optimal control design


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We combine theories of optimal pump-dump control and the related transient probe absorption spectroscopy in order to elucidate the relation between these two optical processes and the possibility of experimental realization. In the weak response regime, we identify the globally optimal pair of pump-dump control fields, and further propose a second-order difference detection scheme to monitor the wave packets dynamics that is jointly controlled by both the pump and dump fields. The globally optimal solution serves also as the initial input for the iterative search for the optimal control fields in the strong response regime. We use a model I-2 molecule to demonstrate numerically the pump-dump control and the detection of a highly vibrationally excited wave packet focusing dynamics on the ground X surface in both the weak and strong response regimes. The I2B surface serves as the intermediate to assist the pump-dump control and the optical detection processes. Demonstrated in the strong response regime are the optimal pair of pump-dump molecular-pi pulses that invert nearly total population onto the predefined target region within a half period of vibration motion. (C) 1999 American Institute of Physics. [S0021-9606(99)00115-4].

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A massive change is currently taking place in the manner in which power networks are operated. Traditionally, power networks consisted of large power stations which were controlled from centralised locations. The trend in modern power networks is for generated power to be produced by a diverse array of energy sources which are spread over a large geographical area. As a result, controlling these systems from a centralised controller is impractical. Thus, future power networks will be controlled by a large number of intelligent distributed controllers which must work together to coordinate their actions. The term Smart Grid is the umbrella term used to denote this combination of power systems, artificial intelligence, and communications engineering. This thesis focuses on the application of optimal control techniques to Smart Grids with a focus in particular on iterative distributed MPC. A novel convergence and stability proof for iterative distributed MPC based on the Alternating Direction Method of Multipliers is derived. Distributed and centralised MPC, and an optimised PID controllers' performance are then compared when applied to a highly interconnected, nonlinear, MIMO testbed based on a part of the Nordic power grid. Finally, a novel tuning algorithm is proposed for iterative distributed MPC which simultaneously optimises both the closed loop performance and the communication overhead associated with the desired control.

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This paper discusses a reliability based optimisation modelling approach demonstrated for the design of a SiP structure integrated by stacking dies one upon the other. In this investigation the focus is on the strategy for handling the uncertainties in the package design inputs and their implementation into the design optimisation modelling framework. The analysis of fhermo-mechanical behaviour of the package is utilised to predict the fatigue life-time of the lead-free board level solder interconnects and warpage of the package under thermal cycling. The SiP characterisation is obtained through the exploitation of Reduced Order Models (ROM) constructed using high fidelity analysis and Design of Experiments (DoE) methods. The design task is to identify the optimal SiP design specification by varying several package input parameters so that a specified target reliability of the solder joints is achieved and in the same time design requirements and package performance criteria are met

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Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

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Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.

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This brief investigates a possible application of the inverse Preisach model in combination with the feedforward and feedback control strategies to control shape memory alloy actuators. In the feedforward control design, a fuzzy-based inverse Preisach model is used to compensate for the hysteresis nonlinearity effect. An extrema input history and a fuzzy inference is utilized to replace the inverse classical Preisach model. This work allows for a reduction in the number of experimental parameters and computation time for the inversion of the classical Preisach model. A proportional-integral-derivative (PID) controller is used as a feedback controller to regulate the error between the desired output and the system output. To demonstrate the effectiveness of the proposed controller, real-time control experiment results are presented.

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Background

Endocrine disrupting chemicals and carcinogens, some of which may not yet have been classified as such, are present in many occupational environments and could increase breast cancer risk. Prior research has identified associations with breast cancer and work in agricultural and industrial settings. The purpose of this study was to further characterize possible links between breast cancer risk and occupation, particularly in farming and manufacturing, as well as to examine the impacts of early agricultural exposures, and exposure effects that are specific to the endocrine receptor status of tumours.

Methods

1005 breast cancer cases referred by a regional cancer center and 1147 randomly-selected community controls provided detailed data including occupational and reproductive histories. All reported jobs were industry- and occupation-coded for the construction of cumulative exposure metrics representing likely exposure to carcinogens and endocrine disruptors. In a frequency-matched case?control design, exposure effects were estimated using conditional logistic regression.

Results

Across all sectors, women in jobs with potentially high exposures to carcinogens and endocrine disruptors had elevated breast cancer risk (OR = 1.42; 95% CI, 1.18-1.73, for 10 years exposure duration). Specific sectors with elevated risk included: agriculture (OR = 1.36; 95% CI, 1.01-1.82); bars-gambling (OR = 2.28; 95% CI, 0.94-5.53); automotive plastics manufacturing (OR = 2.68; 95% CI, 1.47-4.88), food canning (OR = 2.35; 95% CI, 1.00-5.53), and metalworking (OR = 1.73; 95% CI, 1.02-2.92). Estrogen receptor status of tumors with elevated risk differed by occupational grouping. Premenopausal breast cancer risk was highest for automotive plastics (OR = 4.76; 95% CI, 1.58-14.4) and food canning (OR = 5.70; 95% CI, 1.03-31.5).

Conclusions

These observations support hypotheses linking breast cancer risk and exposures likely to include carcinogens and endocrine disruptors, and demonstrate the value of detailed work histories in environmental and occupational epidemiology.

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Among various technologies to tackle the twin challenges of sustainable energy supply and climate change, energy saving through advanced control plays a crucial role in decarbonizing the whole energy system. Modern control technologies, such as optimal control and model predictive control do provide a framework to simultaneously regulate the system performance and limit control energy. However, few have been done so far to exploit the full potential of controller design in reducing the energy consumption while maintaining desirable system performance. This paper investigates the correlations between control energy consumption and system performance using two popular control approaches widely used in the industry, namely the PI control and subspace model predictive control. Our investigation shows that the controller design is a delicate synthesis procedure in achieving better trade-o between system performance and energy saving, and proper choice of values for the control parameters may potentially save a significant amount of energy

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The conversion of biomass for the production of liquid fuels can help reduce the greenhouse gas (GHG) emissions that are predominantly generated by the combustion of fossil fuels. Oxymethylene ethers (OMEs) are a series of liquid fuel additives that can be obtained from syngas, which is produced from the gasification of biomass. The blending of OMEs in conventional diesel fuel can reduce soot formation during combustion in a diesel engine. In this research, a process for the production of OMEs from woody biomass has been simulated. The process consists of several unit operations including biomass gasifi- cation, syngas cleanup, methanol production, and conversion of methanol to OMEs. The methodology involved the development of process models, the identification of the key process parameters affecting OME production based on the process model, and the development of an optimal process design for high OME yields. It was found that up to 9.02 tonnes day1 of OME3, OME4, and OME5 (which are suitable as diesel additives) can be produced from 277.3 tonnes day1 of wet woody biomass. Furthermore, an optimal combination of the parameters, which was generated from the developed model, can greatly enhance OME production and thermodynamic efficiency. This model can further be used in a techno- economic assessment of the whole biomass conversion chain to produce OMEs. The results of this study can be helpful for petroleum-based fuel producers and policy makers in determining the most attractive pathways of converting bio-resources into liquid fuels.

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The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

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Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

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Cette recherche porte sur des questions relatives à la conception des interfaces humain-ordinateur. Elle s’inscrit dans le courant des recherches sur l’utilisabilité et elle s’intéresse particulièrement aux approches centrées sur l’utilisateur. Nous avons été très souvent témoin des difficultés éprouvées par les utilisateurs dans l’usage de certaines interfaces interactives et nous considérons que ces difficultés découlent d’un problème de design. Le design d’interface doit être basé sur les besoins de l’utilisateur dans le cadre de ses activités, dont les caractéristiques devaient être bien comprises et bien prises en considération pour mener à la conception d’interfaces qui respectent les critères d’utilisabilité. De plus, la communauté des chercheurs ainsi que l’industrie admettent maintenant que pour améliorer le design, il est crucial de développer les interfaces humain-ordinateur au sein d’une équipe multidisciplinaire. Malgré les avancées significatives dans le domaine du design centrées sur l’utilisateur, les visées annoncées sont rarement réalisées. La problématique étudiée nous a conduit à poser la question suivante : En tant que designer d’une équipe multidisciplinaire de conception, comment modifier la dynamique de collaboration et créer les conditions d’une conception véritablement centrée sur l’interaction humain-ordinateur ? Notre démarche de recherche a été guidée par l’hypothèse voulant que l’activité de design puisse être le moyen de faciliter la création d’un langage commun, des échanges constructifs entre les disciplines, et une réflexion commune centrée sur l’utilisateur. La formulation de cette hypothèse nous a mené à réfléchir sur le rôle du designer. Pour mener cette recherche, nous avons adopté une méthodologie mixte. Dans un premier temps, nous avons utilisé une approche de recherche par projet (recherche-projet) et notre fonction était celle de designer-chercheur. La recherche-projet est particulièrement appropriée pour les recherches en design. Elle privilégie les méthodes qualitatives et interprétatives ; elle étudie la situation dans sa complexité et de façon engagée. Nous avons effectué trois études de cas successives. L’objectif de la première étude était d’observer notre propre rôle et nos interactions avec les autres membres de l’équipe de projet pendant le processus de design. Dans la seconde étude, notre attention a été portée sur les interactions et la collaboration de l’équipe. Nous avons utilisé le processus de design comme méthode pour la construction d’un langage commun entre les intervenants, pour enrichir les réflexions et pour favoriser leur collaboration menant à redéfinir les objectifs du projet. Les limites de ces deux cas nous ont conduit à une intervention différente que nous avons mise en œuvre dans la troisième étude de cas. Cette intervention est constituée par la mise en place d’un atelier intensif de conception où les intervenants au projet se sont engagés à développer une attitude interdisciplinaire permettant la copratique réflexive pour atteindre les objectifs d’un projet de construction d’un site web complexe centré sur l’utilisateur. L’analyse et l’interprétation des données collectées de ces trois études de cas nous ont conduit à créer un modèle théorique de conception d’interface humain-ordinateur. Ce modèle qui informe et structure le processus de design impliquant une équipe multidisciplinaire a pour objectif d’améliorer l’approche centrée sur l’utilisateur. Dans le cadre de ce modèle, le designer endosse le rôle de médiateur en assurant l’efficacité de la collaboration de l’équipe. Dans un deuxième temps, afin de valider le modèle et éventuellement le perfectionner, nous avons utilisé une approche ethnographique comportant des entrevues avec trois experts dans le domaine. Les données des entrevues confirment la validité du modèle ainsi que son potentiel de transférabilité à d’autres contextes. L’application de ce modèle de conception permet d’obtenir des résultats plus performants, plus durables, et dans un délai plus court.

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Optimal control theory is a powerful tool for solving control problems in quantum mechanics, ranging from the control of chemical reactions to the implementation of gates in a quantum computer. Gradient-based optimization methods are able to find high fidelity controls, but require considerable numerical effort and often yield highly complex solutions. We propose here to employ a two-stage optimization scheme to significantly speed up convergence and achieve simpler controls. The control is initially parametrized using only a few free parameters, such that optimization in this pruned search space can be performed with a simplex method. The result, considered now simply as an arbitrary function on a time grid, is the starting point for further optimization with a gradient-based method that can quickly converge to high fidelities. We illustrate the success of this hybrid technique by optimizing a geometric phase gate for two superconducting transmon qubits coupled with a shared transmission line resonator, showing that a combination of Nelder-Mead simplex and Krotov’s method yields considerably better results than either one of the two methods alone.

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This paper deals with the problem of stabilizing a class of structures subject to an uncertain excitation due to the temporary coupling of the main system with another uncertain dynamical subsystem. A Lyapunov function based control scheme is proposed to attenuate the structural vibration. In the control design, the actuator dynamics is taken into account. The control scheme is implemented by using only feedback information of the main system. The effectiveness of the control scheme is shown for a bridge platform with crossing vehicle

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This short paper addresses the problem of designing a QFT (quantitative feedback theory) based controllers for the vibration reduction in a 6-story building structure equipped with shear-mode magnetorheological dampers. A new methodology is proposed for characterizing the nonlinear hysteretic behavior of the MR damper through the uncertainty template in the Nichols chart. The design procedure for QFT control design is briefly presented