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Skip to Search Results- 1Bayesian Inference
- 1Distributed parameter systems
- 1Experimental design
- 1Frequency analysis
- 1Gaussian Mixture
- 1Inferential Sensing
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Spring 2011
Unsatisfactory performance of a control system may have different root causes, of which diagnosis and control have been subjects of interest. Numerous approaches have been used to identify the source of the oscillatory behavior of control systems. This work will focus on the nonlinearities...
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Enhanced Probabilistic Slow Feature Analysis - Dealing with Complexities in Industrial Process Data
DownloadFall 2023
In modern industrial processes, the measurement and storage of thousands of correlated process variables have become commonplace. Dimensionality reduction techniques are often employed to extract underlying informative patterns called features by discarding redundant information. Slow feature...
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Spring 2011
Optimal experiment design has been considered as an effective tool to improve model reliability and accuracy in nonlinear system identification in the past few decades. This thesis is concerned with the following challenges which have not been previously addressed: poor initial guess problem of...
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Mixtures of Probabilistic Principal Component Regression: Application in Optimality Assessment
DownloadSpring 2017
Performance of the operating processes may change by time due to uncertainties and process condition changes. Hence, online operating performance assessment has attracted attentions from academia and industry. One of the main ingredients of performance assessment is optimality assessment. On one...
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Spring 2015
Distributed parameter systems (DPSs) are distinguished by the fact that the states, controls, and outputs may depend on spatial position. The certain class of dissipative DPSs includes many underlying chemical and mechanical spatiotemporal phenomena such as chemical reactions, convection and...
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Robust Probabilistic Principal Component Analysis Based Modeling with Gaussian Mixture Noises
DownloadFall 2021
Most of the industrial plants are heavily instrumented with a large number of sensors and analyzers to provide the data needed for process control and monitoring purposes. However, online and fast-rate measurements are not always available due to restricted availability and/or reliability of...