Sökning: "Håkan Hjalmarsson"
Visar resultat 11 - 15 av 29 avhandlingar innehållade orden Håkan Hjalmarsson.
11. Module identification in dynamic networks: parametric and empirical Bayes methods
Sammanfattning : The purpose of system identification is to construct mathematical models of dynamical system from experimental data. With the current trend of dynamical systems encountered in engineering growing ever more complex, an important task is to efficiently build models of these systems. LÄS MER
12. Dual control concepts for linear dynamical systems
Sammanfattning : We study simultaneous learning and control of linear dynamical systems. In such a setting, control policies are derived with respect to two objectives: i) to control the system as well as possible, given the current knowledge of system dynamics (exploitation), and ii) to gather as much information as possible about the unknown system that can improve control (exploration). LÄS MER
13. Robust learning and control of linear dynamical systems
Sammanfattning : We consider the linear quadratic regulation problem when the plant is an unknown linear dynamical system. We present robust model-based methods based on convex optimization, which minimize the worst-case cost with respect to uncertainty around model estimates. LÄS MER
14. Modeling, Control and Optimization of theTransient Torque Response in DownsizedTurbocharged Spark Ignited Engines
Sammanfattning : Increasing demands for lower carbon dioxide emissions and fuel consumption drive technological developments for car manufacturers. One trend that has shown success for reducing fuel consumption in spark ignited engines is downsizing, where the engine size is reduced to save fuel and a turbocharger is added to maintain the power output. LÄS MER
15. Least Squares Methods for System Identification of Structured Models
Sammanfattning : The purpose of system identification is to build mathematical models for dynamical systems from experimental data. With the current increase in complexity of engineering systems, an important challenge is to develop accurate and computationally efficient algorithms. LÄS MER