Search
Skip to Search Results- 3Soft Sensor
- 2Particle filters
- 1Bayesian State Estimation
- 1EM algorithm
- 1Model Plant Mismatch
- 1Model Predictive Control
Results for "supervisors_tesim:"Huang, Biao (Chemical and Materials Engineering)""
-
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...
-
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...
-
Robust Probabilistic Slow Feature Analysis for Soft Sensor Development and Model Quality Assessment
DownloadFall 2022
Model predictive control (MPC) is a popular advanced control technology. Unfortunately, over time the behaviour of the plant may deviate from its initial design conditions resulting in model-plant-mismatch. The detection and diagnosis of such mismatches is an important task to ensure that MPC...