Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research

1. Introduction
Chao Shang

2. Monitoring of Operating Condition and Process Dynamics with Slow Feature Analysis
Chao Shang

3. Control Performance Monitoring and Diagnosis Based on SFA and Contribution Plot
Chao Shang

4. Recursive SFA Algorithm and Adaptive Monitoring System Design
Chao Shang

5. Probabilistic Slow Feature Regression for Dynamic Soft Sensing
Chao Shang

6. Enhanced Dynamic PLS with Temporal Smoothness for Soft Sensing
Chao Shang

7. Nonlinear Dynamic Soft Sensing Based on Bayesian Inference
Chao Shang

8. Conclusions and Recommendations
Chao Shang

Keywords: Engineering, Quality Control, Reliability, Safety and Risk, Manufacturing, Machines, Tools, Control, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences