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Department of Information Technology

Research at Systems and Control

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Modeling, inference and control in complex dynamical systems

Current projects

Automatic control and System identification

Dynamical systems, physical and others, can be described by a variety of mathematical models. We develop methods for modeling and estimation of dynamical systems based on measurements of input/output data. The models can be used for analysis, in order to better understand the properties of the system, or for control, to automatically regulate a process without human interaction. Contact person: Alexander Medvedev

Read more about System identification

Statistical Machine Learning

Many interesting phenomena around us are complex, dynamical and stochastic in nature, and the available data are inherently uncertain. We develop theory and tools for learning, reasoning and acting based on probabilistic models and measured data, methods that allow humans and machines to better understand the surrounding world. Contact person: Thomas Schön

Read more on Thomas Schön's website

Signal Processing

The goal of signal processing is to extract information from measured quantities, or signals. This broad concept ranges from simple linear filtering of time series to reduce noise, to nonlinear parameter estimation based on high-dimensional data using statistical models. Estimation theory, optimization, and statistics, play central roles. Contact person: Thomas Schön

Read more about Signal Processing

Important application areas

Biomedical systems

The theory and methods of dynamical systems, control, identification and signal processing have much to offer research and clinical practice in modern medicine. We develop methods used in the diagnosis, assessment, and treatment of medical conditions, based on dynamical models of physiological and biological systems. Currently we have projects on Parkinson's disease, breast cancer, diabetes and balance impairment. Contact person: Alexander Medvedev

Read more about Biomedical systems

Wastewater engineering

Water quality and treatment of water is a growing concern around the world. Demands on quality and increasing loads call for optimized operation of wastewater treatment plants. Applied research in automatic control is an important tool in improving the performance of treatment plants. We are developing control and estimation strategies for wastewater treatment plants that improve pollutant removal, reduce the chemicals consumption and yield energy savings. Contact person: Bengt Carlsson

Read more: Modelling and automatic control of wastewater treatment plants

Recent publications

More comprehensive list of publications

Updated  2022-09-07 14:28:08 by Victor Kuismin.