895 resultados para optimal control design


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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

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The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

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Fluid bed granulation is a key pharmaceutical process which improves many of the powder properties for tablet compression. Dry mixing, wetting and drying phases are included in the fluid bed granulation process. Granules of high quality can be obtained by understanding and controlling the critical process parameters by timely measurements. Physical process measurements and particle size data of a fluid bed granulator that are analysed in an integrated manner are included in process analytical technologies (PAT). Recent regulatory guidelines strongly encourage the pharmaceutical industry to apply scientific and risk management approaches to the development of a product and its manufacturing process. The aim of this study was to utilise PAT tools to increase the process understanding of fluid bed granulation and drying. Inlet air humidity levels and granulation liquid feed affect powder moisture during fluid bed granulation. Moisture influences on many process, granule and tablet qualities. The approach in this thesis was to identify sources of variation that are mainly related to moisture. The aim was to determine correlations and relationships, and utilise the PAT and design space concepts for the fluid bed granulation and drying. Monitoring the material behaviour in a fluidised bed has traditionally relied on the observational ability and experience of an operator. There has been a lack of good criteria for characterising material behaviour during spraying and drying phases, even though the entire performance of a process and end product quality are dependent on it. The granules were produced in an instrumented bench-scale Glatt WSG5 fluid bed granulator. The effect of inlet air humidity and granulation liquid feed on the temperature measurements at different locations of a fluid bed granulator system were determined. This revealed dynamic changes in the measurements and enabled finding the most optimal sites for process control. The moisture originating from the granulation liquid and inlet air affected the temperature of the mass and pressure difference over granules. Moreover, the effects of inlet air humidity and granulation liquid feed rate on granule size were evaluated and compensatory techniques used to optimize particle size. Various end-point indication techniques of drying were compared. The ∆T method, which is based on thermodynamic principles, eliminated the effects of humidity variations and resulted in the most precise estimation of the drying end-point. The influence of fluidisation behaviour on drying end-point detection was determined. The feasibility of the ∆T method and thus the similarities of end-point moisture contents were found to be dependent on the variation in fluidisation between manufacturing batches. A novel parameter that describes behaviour of material in a fluid bed was developed. Flow rate of the process air and turbine fan speed were used to calculate this parameter and it was compared to the fluidisation behaviour and the particle size results. The design space process trajectories for smooth fluidisation based on the fluidisation parameters were determined. With this design space it is possible to avoid excessive fluidisation and improper fluidisation and bed collapse. Furthermore, various process phenomena and failure modes were observed with the in-line particle size analyser. Both rapid increase and a decrease in granule size could be monitored in a timely manner. The fluidisation parameter and the pressure difference over filters were also discovered to express particle size when the granules had been formed. The various physical parameters evaluated in this thesis give valuable information of fluid bed process performance and increase the process understanding.

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The UDP-glucuronosyltransferases (UGTs) are enzymes of the phase II metabolic system. These enzymes catalyze the transfer of α-D-glucuronic acid from UDP-glucuronic acid to aglycones bearing nucleophilic groups affording exclusively their corresponding β-D-glucuronides to render lipophilic endobiotics and xenobiotics more water soluble. This detoxification pathway aids in the urinary and biliary excretion of lipophilic compounds thus preventing their accumulation to harmful levels. The aim of this study was to investigate the effect of stereochemical and steric features of substrates on the glucuronidation catalyzed by UGTs 2B7 and 2B17. Furthermore, this study relates to the design and synthesis of novel, selective inhibitors that display high affinity for the key enzyme involved in drug glucuronidation, UGT2B7. The starting point for the development of inhibitors was to assess the influence of the stereochemistry of substrates on the UGT-catalyzed glucuronidation reaction. A set of 28 enantiomerically pure alcohols was subjected to glucuronidation assays employing the human UGT isoforms 2B7 and 2B17. Both UGT enzymes displayed high stereoselectivity, favoring the glucuronidation of the (R)-enantiomers over their respective mirror-image compounds. The spatial arrangement of the hydroxy group of the substrate determined the rate of the UGT-catalyzed reaction. However, the affinity of the enantiomeric substrates to the enzymes was not significantly influenced by the spatial orientation of the nucleophilic hydroxy group. Based on these results, a rational approach for the design of inhibitors was developed by addressing the stereochemical features of substrate molecules. Further studies showed that the rate of the enzymatic glucuronidation of substrates was also highly dependent on the steric demand in vicinity of the nucleophilic hydroxy group. These findings provided a rational approach to turn high-affinity substrates into true UGT inhibitors by addressing stereochemical and steric features of substrate molecules. The tricyclic sesquiterpenols longifolol and isolongifolol were identified as high-affinity substrates which displayed high selectivity for the UGT isoform 2B7. These compounds served therefore as lead structures for the design of potent and selective inhibitors for UGT2B7. Selective and potent inhibitors were prepared by synthetically modifying the lead compounds longifolol and isolongifolol taking stereochemical and steric features into account. The best inhibitor of UGT2B7, β-phenyllongifolol, displayed an inhibition constant of 0.91 nM.

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Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

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Several articles in this journal have studied optimal designs for testing a series of treatments to identify promising ones for further study. These designs formulate testing as an ongoing process until a promising treatment is identified. This formulation is considered to be more realistic but substantially increases the computational complexity. In this article, we show that these new designs, which control the error rates for a series of treatments, can be reformulated as conventional designs that control the error rates for each individual treatment. This reformulation leads to a more meaningful interpretation of the error rates and hence easier specification of the error rates in practice. The reformulation also allows us to use conventional designs from published tables or standard computer programs to design trials for a series of treatments. We illustrate these using a study in soft tissue sarcoma.

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The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

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Photovoltaic (PV) panels and electric domestic water heater with storage (DWH) are widely used in households in many countries. However, DWH should be explored as an energy storage mechanism before batteries when households have excess PV energy. Through a residential case study in Queensland, Australia, this paper presents a new optimized design and control solution to reduce water heating costs by utilizing existing DWH energy storage capacity and increasing PV self-consumption for water heating. The solution is produced by evaluating the case study energy profile and numerically maximizing the use of PV for DWH. A conditional probability matrix for different solar insolation and hot water usage days is developed to test the solution. Compared to other tariffs, this solution shows cost reduction from 20.8% to 63.3% This new solution could encourage solar households move to a more economical and carbon neutral water heating method.

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The specific objective of this paper is to develop multiloop controllers that would achieve asymptotic regulation in the presence of parameter variations and disturbance inputs for a tubular reactor used in ammonia synthesis. The dynamic model considered here has nine state variables, two control inputs, and two outputs. A systematic procedure for pairing the two inputs with the corresponding two outputs is presented. The two multiloop proportional controllers so configured are designed via the parameter plane method. This economic configuration of controllers maintains the temperature profile almost at the optimal value whereas the point controllers fail to do so.

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This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

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This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

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The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example

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A new procedure for reducing trajectory sensitivity for the optimal linear regulator is described. The design is achieved without increase in the order of optimization and without the feedback of trajectory sensitivity. The procedure is also used in the input signal design problem for linear system identification by interpreting it as increasing trajectory sensitivity with respect to parameters to be estimated.

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In this paper we first describe a framework to model the sponsored search auction on the web as a mechanism design problem. Using this framework, we design a novel auction which we call the OPT (optimal) auction. The OPT mechanism maximizes the search engine's expected revenue while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We show that the OPT mechanism is superior to two of the most commonly used mechanisms for sponsored search namely (1) GSP (Generalized Second Price) and (2) VCG (Vickrey-Clarke-Groves). We then show an important revenue equivalence result that the expected revenue earned by the search engine is the same for all the three mechanisms provided the advertisers are symmetric and the number of sponsored slots is strictly less than the number of advertisers.

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In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the Reusable Launch Vehicle (RLV). The controller has been designed based on a recently developed technique Optimal Dynamic Inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an Extended Kalman filter (EKF) is developed to estimate the states. The vehicle (RLV) has been has been consider as a nonlinear Six-Degree-Of-Freedom (6-DOF) model. The simulation results shows that EKF gives a very good estimation of the states and it is working well with ODI. The resultant trajectories are very similar to those obtained by perfect state feedback using ODI only.