Generalized Models of Sequential Decision-Making under Uncertainty

Sequential decision-making under uncertainty is an important branch of artificial intelligence research with a plethora of real-life applications. In this thesis, we generalize two fundamental properties of the decision-making process. First, we show that the theory on planning methods for finite spaces can be extended to infinite but countable...

LQG and Gaussian process techniques: For fixed-structure wind turbine control

Wind turbines are growing bigger to becomemore cost-efficient. This does increase the severity of the vibrations that are present in the turbine blades, both due to predictable effects like wind shear and tower shadow, and due to less predictable effects like turbulence and flutter. If wind turbines are to become bigger and more cost-efficient,...

Model reduction for dynamic real-time optimization of chemical processes

The value of models in process industries becomes apparent in practice and literature where numerous successful applications are reported. Process models are being used for optimal plant design, simulation studies, for off-line and online process optimization. For online optimization applications the computational load is a limiting factor. The...

Dynamic Optimization in Business-wide Process Control

The chemical marketplace is a global one with strong competition between man- ufacturers. To continuously meet the customer demands regarding product quality and delivery conditions without the need to maintain very large stor- age levels chemical manufactures need to strive for production on demand. In this thesis we research how market...