Entry requirements

60 credits science/technology, including Single variable calculus and Linear algebra II.

Learning outcomes

Students who pass the course should be able to

• define basic concepts in automatic control
• determine relations between different model representations
• analyse linear time-invariant systems with respect to relevant properties
• design and implement simple controllers

Content

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, word length, time delays, aliasing, windup).

Instruction

Lectures, problem solving sessions and laboratory work.

Assessment

Written examination at the end of the course. Passed laboratory course is also required.