Optimal State Estimation

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Fundamentals Of Engineering Thermodynamics

Towards a Digital Twin for Thermal Processes: Control-centric approach

Output feedback stochastic nonlinear model predictive control for batch processes

The present invention relates to a centrifugal compressor. The compressor is a compact magnetic bearing based on technology and efficient compressor, and the compressor may have a high speed operation and reliable control system. The present invention employs a compressor installed on a single common motor so that a driving means shared two separate compressors. Balance the axial force at high speed is achieved by employing a pair of electromagnetic bearing.

A centrifugal compressor

Model-Based and Model-Free Optimal Control of a Gas Liquid Cylindrical Cyclone

Steam delivery networks are large energy consuming processes and an important source of energy in many processing plants. These networks are often subject to large disturbances, which can lead to costly operating periods due to lack of steam and heavily loaded boilers. Thus, there is a potential for stabilization and reduction of the energy consumption. The objective of this thesis is to stabilize a steam delivery network using a model predictive controller, and further minimize the energy consumption by incorporating an overlying optimization problem, that is an optimizer, on top of the model predictive controller. The controller and the optimizer developed in this thesis are applied to the steam delivery network at Statoil Karsto, but the principles are applicable for any steam delivery network. A study of the steam delivery networks including its main components and control structure are performed. The study is based on real plant data and a dynamic simulator model. The network consists of eight boilers, in which all deliver high pressure steam into a common header. Steam is continuously drawn from the common header by various steam consumers before it is returned to the boilers as condensate. This behavior makes it easy to obtain step response models of the boilers by performing a step in their inputs, that is increase their combustion. These models are incorporated into the controller which is implemented using the SEPTIC application developed by Statoil. This controller optimizes the future response by solving a quadratic optimization problem, consisting of various weights and constraints on the considered variables in combination with the models of the system, at each control sample. The ideal values of this controller is calculated the optimizer, derived from the mass and energy balances of the steam delivery network. Two different optimizers are derived and considered, one which does not allow for a boiler shutdown, and the second which allows for a boiler shutdown. These are named conservative and strictly economical optimization, respectively. Three different case studies, with increasingly degrees of disturbances, are carried out to study the performance of the model predictive controller compared to the currently used PI control structure. Five additional case studies are performed to illustrate the potential and issues occurring by incorporating an optimizer. The results show improved performance and stability by including a model predictive controller and indicate a significant potential for reduction in both fuel consumption and CO 2 emissions by incorporating an optimizer. However, only the conservative optimizer proved to be robust against model errors and large disturbances.

Optimal and Stable Production of High Pressure Steam

Production of gas condensate from small and remote gas condensate fields require cost-efficient boosting technology for maintaining an economically satisfactory throughput. Wet gas compressors are a new boosting technology enabling boosting of gases containing up to 5% liquid per volume, removing the need for pre/bulk separation, resulting in lower investment and maintenance costs. However, introduction of liquid significantly changes the compression performance from that of dry gas compression, including the process gain and the normal operating region, resulting in a challenging modelling and control problem. Therefore, in this paper, we extend the commonly applied dynamic model of Greitzer for dry gas compression with one additional state and extended polynomial approximation of the compressor characteristic. A nonlinear process control algorithm, using the angular velocity as input, is derived by applying backstepping, and local asymptotic stability proven via Lyapunov analysis. The control performance is studied in different simulations with and without saturation on the control input. The steady-state performance of the dynamic model is quantitatively validated against experimental data.

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Torstein Thode Kristoffersen

Papers

Model-Based and Model-Free Optimal Control of a Gas Liquid Cylindrical Cyclone

Optimal and Stable Production of High Pressure Steam

Modelling and Nonlinear Control of a Wet Gas Centrifugal Compressor

A High-Gain Observer for a Wet Gas Centrifugal Compressor