After completing the course, one understands the relevance and building blocks of model-based control design and system analysis. Relying on data-driven approaches, this course provides strong foundations for digital control design considering real-life applications.
1. Control theory of linear time-invariant (LTI) systems in discrete-time (digital control). State-space representation and system analysis in time domain. Controllability, observability and related concepts. Relation of the static state feedback with PID control. Stability in Lyapunov sense. 2. Basics of LTI model identification using data. Model order reduction, model uncertainty. The relevance of LTI theory in the control of nonlinear systems. 3. Laboratory exercises with the Valmet DNA automation system.
Dorf, R. (2010) Modern Control Systems. Prentice-Hall, New York, 1104 s,
Ogata, K (2002) Modern Control Engineering. Prentice-Hall, New York, 964 s.,
Åström, K & Murray, R. (2009) Feedback Systems, An Introduction for Scientists and Engineers. Princeton University Press, New Jersey, 396 s.,
Landau, I. & Zito, G. (2005) Digital Control Systems, Springer. 485 pp.
Åström, K.J. & Wittenmark, B. (1984, 1997) Computer Controlled Systems: Theory and Design. Prentice-Hall International.