Automatic Control II
Second-cycle course, Department of Information Technology, Uppsala University, 1900
Fall 2023, Spring 2023, Fall 2022, Spring 2022 with Sérgio Pequito and Hans Rosth
About the course
The course covers both continuous-time and discrete-time linear systems. It includes a sampling of continuous-time systems and an introduction to discrete-time systems. Stochastic processes are introduced and used as models for disturbances, and the Kalman filter is introduced as a tool for estimation and prediction. Based on this, LQ/LQG and MPC are presented as examples of optimal controllers.
Learning outcomes
On completion of the course, the student should be able to:
determine relations between multivariable dynamic models in form of state space models and transfer functions
analyse multivariable dynamic systems with respect to stability, sensitivity for disturbances, statistical properties, and controllability and observability
analyse dynamic systems influenced by noise, and to determine stationary variances for given linear models
design optimal observers (Kalman filters)
design controllers for linear multivariable systems based on linear quadratic (LQ) control
account for the principles behind model predictive control (MPC)
evaluate controllers in laboratory work on real processes