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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)
Results for "supervisors_tesim:"Huang, Biao (Chemical and Materials Engineering)""
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Fall 2014
In this thesis, time-varying behaviour, nonlinearity and switching dynamics are generally treated as multi-modal behaviour. Two multi-model modelling techniques, i.e., the linear parameter varying (LPV) technique and the switched modelling technique, are investigated to model the multi-modal...
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Dual Neural Extended Kalman Filtering Approach for Multirate Sensor Data Fusion with Industrial Applications
DownloadFall 2020
The Kalman filter algorithm and its variants have been widely applied to the multisensor data fusion problems to provide joint state estimation, which is more accurate than estimations from individual sensors. The performance of the Kalman filter based fusion relies on the accuracy of the models...
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Camera based Primary Separation Vessel Interface Level Detection and Estimation Utilizing Markov Random Field based Image Processing
DownloadSpring 2017
The level of the froth middling interface in primary separation vessel plays an important role in overall bitumen recovery in conventional oil sands bitumen extraction process. To maintain the interface within a certain range of level, the accurate measurement is always desired. Online camera...
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Spring 2016
In data-driven modelling, model accuracy relies heavily on the data set collected from target process. However, various types of measurement noise exist extensively in industrial processes and the data obtained are usually contaminated. If the influence of measurement noise is neglected, both the...
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Spring 2017
Recently, increasing attention has been given to the theoretical and practical analysis of large-scale networked systems. Large-scale systems are usually composed of several interconnected subsystems connected through material and energy flows. Due to the scale of these systems and the...
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Fall 2013
The utility system plays an important role in efficient plant operations of chemical processes. In this thesis, economic optimization of steam utility system is investigated in detail. The objective is: 1) to calculate the optimal generation amount of steam and electricity under uncertainty in...
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EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification
DownloadSpring 2016
In this thesis, under the EM algorithm framework, a multiple model approach is developed towards electricity price prediction, and the identification problem for errors-in-variables (EIV) systems is studied. Alberta's electricity price, which shows high volatility and erratic nature, is...
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Fall 2018
The objective of this work is to study the problems that arise in state estimation for severely nonlinear systems. In practice, many processes are nonlinear, accompanied by uncertain parameters. The complexity of the model causes the probability density function (PDF) of the states to deviate...
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Spring 2013
Parameter estimation of a dynamic system is an important task in process systems engineering. The utilization of an augmented system offers the approach of estimating process states and parameters simultaneously. In practice, the parameters often satisfy certain constraints which should be...
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Spring 2020
Machine learning (ML) has shown great potential to create tremendous value and growth to all sectors around the world, enhancing productivity, health, and longevity of humanity. ML differentiates itself from all previous methods through its adaptive and self-learning capabilities. In recent...