Teaching

The course introduces you to safety and security aspects of modern control systems arising due to your digital and networked implementation. The main course body consists of basic concepts, approaches to and methods of modelling, analysis, and detection of faults and attacks in control systems.

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.

System models: State-space forms and the solution of the state-space equation in discrete and continuous time. Sampling. Transfer functions and transfer operators. Model transformations from transfer functions to state-space models and vice versa. System properties: Controllability and observability. Static gain. Step and impulse responses in discrete and continuous time. Frequency domain properties (connection to sampling). Stability in discrete and continuous time; asymptotic stability, bounded-input bounded-output stability, the Nyquist criterion. Controller design: Pole placement in state-space form. State feedback with observer. PID controllers. Stability margins. Sensitivity functions. The notion of robustness. Computer implementation (sampling, aliasing).