Process and plantwide control
Industrial use of advanced process control increases rapidly, and candidates who combine process knowledge and control expertise are in high demand in industry. Control is an enabling technology, thus basic for any industry-based society. The use of advanced control is transforming industries previously regarded as "lowtech" into "high-tech". In process control (Skogestad, Preisig, Jäschke), the objective of the research is to develop simple yet rigorous tools to solve problems significant to industrial applications (of engineering significance).
Up to now, the design of the overall "plant-wide" control structure has been based on engineering experience and intuition, whilst the aim has been to develop rigorous techniques. The concept of "self-optimizing control" provides a basis for linking economic optimization and control (Skogestad). For example, for a marathon runner, the heart rate may be a good "self-optimizing" variable that may be kept constant in spite of uncertainty. Control is done in a hierarchical construct. At the bottom of the hierarchy, the main issue is to "stabilize" the operation and follow the setpoints provided by the layer above.
Further up in the hierarchy one finds optimising control co-ordinating the control of units and plants. A special case is sequential control, which is used to implement recipes in batch operations but also is the basics of handling start-up and shut-down as well as all fault and emergency handling. Another important concept is controllability, which links control and design. Here the main focus is on applications, which currently include reactor and recycle processes, distillation columns, gas processing plants, cooling cycles including liquefied natural gas (LNG) plants, low-temperature polymer fuel cells and anti-slug control.
The fourth generation of a high-level modelling tool is presently being developed (Preisig), which we aim to apply to large-scale plants, including the Mongstad refinery. It incorporates object-oriented tools for efficient thermodynamic modelling, which extend into the efficient computation of thermodynamic information. Rather than a traditional implementation of activity or fugacity coefficients, emphasis is put on the use of structured equation sets governed by thermodynamic consistency rules (Haug-Warberg). The thermodynamic models are implemented in symbolic form with automatic differentiation capabilities and serves as the basis of several industrial strength simulations (YASIM, CADAS) and energy accounting tools (HERE) in cooperation with Norsk Hydro and Yara. A primary aspect of thermodynamic (and other physics) modelling is the required consistency of physical units. We have a procedure to obtain self-consistent models, including automatic generation of gradients. This technique has so far been tested up to sixth order gradients, which are needed for higher-order critical point calculations.
The systems biology and bioinformatics research area (Skjøndal-Bar) applies dynamic modelling and control in order to understand and regulate processes in biology and chemistry, such as intercellular processes (molecular biology), enzymatic reactions, hormonal regulation and sensory-motion control. Current projects are:
- Dynamic modelling of the motion of RNA polymerase and its abortive initiation in the non-coding regions of the DNA
- Model and analyse biological processes such as body growth, feed intake, adipose cells and nutrition pathways. This project is applied in aquaculture sciences, with dynamic models that predict body mass and composition in Atlantic salmon, and regulate appetite and feed intake in fish. We also work on Salmon- parasite immune system interaction models, in order to increase resistance of the fish to parasites.
- Modeling, analysis and control of the process of gene expression in Eukaryotic and prokaryotic cells, including translational initiation regulation, elongation and transcription. This project has many applications, from controlling production of proteins with medical and industrial importance to cancer research.
- Sensory-motion control models. Dynamic models of sensory processing and flight motion in bats, is with cooperation with labs in Israel and USA, where we investigate bats motion and navigation in the air and the manner bats process its sensory information to fly, navigate and find food. This projects include field works (mexico, Israel, US) and laboratory work, in addition to dynamic modeling and parameter estimation.
Subsea processing (SUBPRO)
Subsea processing (SUBPRO) is a Centre for Research-based Innovation (SFI) funded by the Norwegian Research Council. Subsea production and processing technology is a key enabler for exploitation of Norwegian and international oil and gas resources. Norwegian oil companies and foreign oil companies with basis in Norway, with the strong support of Norwegian-based suppliers and manufacturing companies, have been in the forefront of developing subsea fields.