Research theme: Industrial process control

The relevant trends in process industry could be summarized as: better profitability, increased flexibility and the incorporation of sustainability. The current research focus is on profitability and flexibility and could be summarized as model-based control/optimization of ``difficult'' unit operations and complete plants. In this research three aspects can be recognized:

1. Modeling: this includes modeling, validation, identification and reduction. After modeling we should end up with a model that has sufficient accurate predictive power at acceptable computational cost.
2. Observation: Attention is paid to extended Kalman filters and horizon estimators.
3. Control/optimization: The research in this area concentrates on dynamic optimization (sequential and simultaneous approach) but also on the integration of control and optimization.

• Economic optimal plantwide control
• Closed-loop model predictive control
• Model reduction for dynamic optimization of chemical processes
• Rigorous model-based control strategy for batch crystallizers (CrysCODE)
• Intelligent adaptive control of bioreactors
• Artificial intelligence for the control of a hopper dredger
• Grey-box modeling and plant-wide integrated control of water purification processes
• Model based optimization of emulsification processes
• Model predictive control of municipal solid waste plants
• Model-based optimal process operational strategies in reservoir engineering using quantified model-uncertainty estimates