Course overview
This course aims to provide an understanding of both advanced particulate processes and design, and advanced process dynamics and control. Theory and applications of particulate processes withing chemical plants are covered. Analysis and design of complex control systems and the modern use of artificial intelligence and machine learning for statistical process control are overviewed.
Course learning outcomes
- Characterise and describe particulate systems in terms of their basic physical properties
- Perform basic design calculations and analysis of typical particulate processes, such as mixing, size reduction and enlargement, storage and transport of powders
- Describe the hazards associated with fine powders and suggest preventative means by which these can be reduced
- Determine dynamic characteristics (e.g. in a first-order plus dead time model) and specify advanced controllers (e.g. dead time compensation, feed-forward, IMC, model-based controllers)
- Devise plant-wide control structures
- Use the z-transform in digital control and design controllers for discrete systems
- Describe how Artificial Intelligence and Machine Learning along with statistical process control are used in industrial processes