English

If sufficient demand

The course gives an in-depth treatment of design of linear control systems with limitations. Special attention is given to design trade-offs and fundamental limitations, and how mathematical optimziation can be used as a design tool, both offline and online. The course covers both continuous-time and discrete-time control systems.

The control design process, stability, sensitivity, robustness, the small-gain theorem, transfer function matrices, non-minimum-phase systems, disturbance models in the time domain and frequency domain, frequency-domain specifications, fundamental limitations and trade-offs, controller structures, the Youla parameterization and internal model control, sampled-data control, linear-quadratic optimization of state feedback and Kalman filter, model-predictive control, controller synthesis using convex optimization.

be able to translate between, and intelligently select among, different representations for continuous-time and discrete-time systems, in particular transient responses, transfer functions, and state-space descriptions.
be able to derive properties of interconnected systems from the properties of their subsystems, and to characterize and quantify the role of the different subsystems.
be able to formulate constraints on input signals and output signals of a control system and to relate these to conditions on the matrices that describe the system.
be able to analyse how process characteristics put limitations on the control performance that can be achieved.

be able to independently formulate technical specifications based on understanding of the control system should be used and interact with the external environment.
be able to select control design methods and model structures, and translate specifications into mathematical optimization problems to be solved online or offline.
draw conclusions from numerical calculations about the correctness of models and specifications, and about the consequences for the interaction between the system and the environment.

understand relationships and limitations when simplified models are used to describe a complex and dynamic reality
show ability to teamwork and group collaboration at laboratories.

Lectures

Laboratory exercises

Written exam

Failed, pass

FRTF05 Automatic Control, Basic Course or FRTN25 Automatic Process Control.

 

Lecture slides, exercise material and laboratory manuals are available on the course homepage.
Lecture Notes in Automatic Control, Advanced Course. Department of Automatic Control, LTH (compendium).
Torkel Glad, Lennart Ljung: Control Theory: Multivariable and Nonlinear Methods, Taylor & Francis, 2000, ISBN 0748408789 (optional reading).

FRTN55F

2020-11-13

Professor Thomas Johansson