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Characteristics of the transparent fluid assisted in-process measurement method /Tao, Zhengsu. January 2003 (has links)
Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 106-114). Also available in electronic version. Access restricted to campus users.
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MIMO control performance monitoring based on subspace projectionsMcNabb, Christopher Alan 28 August 2008 (has links)
Not available / text
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Towards the performance monitoring of constrained control systemsHarrison, Christopher Allen 28 August 2008 (has links)
Not available / text
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Discrete process control with batch inputs : a quality systems perspectiveNetherton, Susan Kay 12 1900 (has links)
No description available.
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Measurement System Design for Chemical ProcessesLiba, Michael Joseph 16 June 2011 (has links)
The problem of measurement system design for stochastic linear systems, a popular modeling strategy for chemical processes, is addressed. A multi-objective optimization approach is used. The design metrics are the capital cost of measurement equipment and a weighted uncertainty in terms of the Kalman filter state estimation error covariance matrix. The Pareto optimal set of measurement systems is identified by any of the following applicable techniques: an exhaustive combinatorial search, sequential sensor addition/removal, and branch-and-bound with semi-definite programs (BnB/SDP) solved at each node. The decision-making process involves the use of simulation experiments as a means to map Pareto optimal measurement systems to a dollar cost of operation. The closed-loop performance of Pareto optimal measurement systems are then simulated under a joint Kalman filter and robust profit-maximizing model predictive control strategy.
The design methodology is applied to two example problems. The first involves a low dimensionality fluid handling network where a number of stream flow rates, a tank level, and a leak stream describe the dynamics. The design variables are the process outputs and the precision with which they are measured. It is observed that the sequential and
BnB/SDP techniques are able to approximate the true Pareto optimal set very well, with improved performance in the latter case attainable through trial and error. The second example problem involves a high-dimensionality thermal network model of a one-floor office building. The impact of zero and nonzero state noise covariance structures on the results of the proposed design procedure is investigated. It is shown that measurement importance is placed on the disturbance variables in the deterministic case, whereas importance is placed on the controlled variables when model uncertainty is assumed. Closed-loop simulations incorporating MPC and Kalman filtering are then performed to generate expected operational cost data. The measurement system that minimizes the overall cost of capital investment and operation over the expected lifespan of the measurement is chosen as the final design. It is shown that the combination of measured variables which minimizes the overall cost is those of the three largest bodies of air that are to be controlled. / Thesis (Master, Chemical Engineering) -- Queen's University, 2011-06-15 22:17:06.903
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The design of a hybrid microprocessor/binary decision programmable controller /Hudson, Robert Douglas. January 1984 (has links)
No description available.
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Estimation and control of sheet forming processesRigopoulos, Apostolos 12 1900 (has links)
No description available.
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Prediction of workpiece location as a function of fixture-induced errorsRaghu, Anand 05 1900 (has links)
No description available.
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Process control using an optomux control boardSabri, Dina O. January 1987 (has links)
In this thesis process control concepts were used to develop software that could be adapted to a real world situation. The software was used to control a simple temperature regulating experiment. This experiment was used to demonstrate the use of OPTOMUX analog and digital input/output devices in controlling a process. The goal of this experiment was to use the input/output devices in controlling the temperature of the box within specified tolerances for a designated period of time. To accomplish optimal use of equipment and optimal control, a mathematical model was derived to predict the behavior of the process under control. The pattern observed while the temperature was increasing toward room temperature closely resembled an exponential function. For temperatures above room temperatures the curve then approximated a square root function. The pattern followed when decreasing the temperature-was exponential throughout. The time required to collect all the significant data in the case of increasing the temperature was two hours. In the case of decreasing temperature, one hour. Beyond these time limits the temperature remained essentially constant. The maximum temperature value that could be reached was six degrees above room temperature and the minimum two degrees below room temperature.
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Computer control of continuous and batch processes using a Petri-net interpreterDallas, P. S. January 1986 (has links)
No description available.
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