Canvas course page 2022 | CEQ reports

Old Canvas course page (2021)

Official Course syllabus

General Information

Compulsory for: MMSR2
Elective for: B5, C4, D4-ssr, E4-ra, F4, F4-r, I4, I4-pvs, K5, M4, N4, Pi4-ssr
Language of instruction: The course will be given in English

Aim

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 optimization can be used as a design tool, both offline and online. The course covers both continuous-time and discrete-time control systems.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

• 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.

Competences and skills
For a passing grade the student must

• be able to independently formulate technical specifications based on understanding of how 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.

Judgement and approach
For a passing grade the student must

• 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.

Contents

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.

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written exam (5 hours), three laboratory exercises, one hand-in assignment. In case of less than 5 registered students the retake exams may be given in oral form.

Admission

Required prior knowledge: FRTF05 Automatic Control, Basic Course, or FRTN25 Automatic Process Control.

Reading list

• 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).

Contact and other information

Course coordinator: Anton Cervin, anton.cervin@control.lth.se