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Skip to Search Results- 40Huang, Biao (Chemical and Materials Engineering)
- 5Forbes, Fraser (Chemical and Materials Engineering)
- 2Li, Zukui (Chemical and Materials Engineering)
- 2Prasad, Vinay (Chemical and Materials Engineering)
- 1Afacan, Artin (Chemical and Materials Engineering)
- 1Forbes, J.Fraser (Chemical and Materials Engineering)
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Fall 2009
This thesis is concerned with subspace identification and its applications for controller performance assessment and process modeling from closed-loop data. A joint input-output closed-loop subspace identification method is developed which provides consistent estimation of the subspace matrices...
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Moving horizon estimation for continuum and noncontinuum states with applications in distillation processes
DownloadFall 2011
This thesis focuses on the development of advanced state estimators for continuum and noncontinuum state estimations in a switching dynamic system, and the demonstration of their applications in addressing some important process monitoring problems of distillation processes. First, the...
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Fall 2011
The large number of control loops in a modern industrial plant poses a serious challenge for operators and engineers to monitor these loops to maintain them at optimal conditions continuously. Much research has been done on control loop performance assessment and monitoring of individual...
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Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development
DownloadSpring 2012
For chemical engineering processes, state estimation plays a key role in various applications such as process monitoring, fault detection, process optimization and model based control. Thanks to their distinct advantages of inference mechanism, Bayesian state estimators have been extensively...
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Data Quality Assessment for Closed-Loop System Identification and Forecasting with Application to Soft Sensors
DownloadFall 2012
In many chemical plants, data historians store thousands of variables at fast sampling rates. Much of this collected data is routine operating data that could easily be used for system identification and forecasting, especially in the design of soft sensors. Currently, there is no framework for...
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Spring 2012
Limitations of measurement techniques and increasingly complex chemical process render difficulties in obtaining certain critical process variables. The hardware sensor reading may have an obvious bias compared with the real value. Off-line laboratory analysis with high accuracy can only be...
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Performance Monitoring of Iterative Learning Control and Development of Generalized Predictive Control for Batch Processes
DownloadSpring 2012
Unlike continuous processes, a batch process has a certain period of operation time, and there are a number of batches in a typical operation. Hence variables in a batch process have dynamics in two dimensions, along time and across batches. Besides, batch processes involve large transient phases...
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Fall 2013
Time consuming offline laboratory analysis and high cost hardware measurement techniques render difficulties in obtaining the important quality variables in real time application. Near-infrared (NIR) spectroscopy is widely used as a process analytical tool (PAT) in chemical processes, providing...
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Fall 2013
State inference and identification of discrete-time, non-linear, stochastic state-space models (SSMs) are considered here. A novel sequential Monte Carlo (SMC) based Bayesian method for simultaneous on-line state inference and identification of non-linear SSMs is proposed. Extension of the method...
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Spring 2013
In the steam methane reforming process, improvement of the reformed gas outlet temperature control performance can lead to a larger hydrogen production rate, while ensuring safe process operation. In this work, a side fired primary gas reformer is investigated. The three objectives of this work...