Module RO4400-KP12

Duration

1 Semester

Turnus of offer

every summer semester

Credit points

12

Course of studies, specific fields and terms:

• Master MES 2020, advanced module, computer science / electrical engineering
• Master MES 2014, advanced module, computer science / electrical engineering

Classes and lectures:

• Practical Course in Control Systems (practical course, 3 SWS)
• Advanced Methods in Control (exercise, 1 SWS)
• Control Systems (exercise, 1 SWS)
• Advanced Methods in Control (lecture, 2 SWS)
• Control Systems (lecture, 2 SWS)

Workload:

• 185 hours private studies
• 135 hours in-classroom work
• 40 hours exam preparation

Contents of teaching:

• Modeling of dynamic systems
• Dynamic behavior of systems
• Feedback concepts
• Controller design in time domain
• System representation in frequency domain
• Stability
• Controller design in frequency domain
• State space models, canonical representations and properties
• Design of state feedback controllers and state observers
• Optimal control and state estimation
• Linear parameter-varying systems
• Model predictive control
• Planning and realization of typical control applications in a team

Qualification-goals/Competencies:

• Students can model physical systems mathematically as well as describe and analyze their dynamic behavior.
• Students know the fundamental tools and can formulate requirements with respect to systems in the time and frequency domain. Students are able to design control loops using time and frequency domain-based tools.
• Students are able to analyze stability of feedback systems and can evaluate the resulting dynamic properties with respect to control performance and robustness.
• Students know how to describe and analyze state space models.
• Students know how to synthesize and design state feedback controllers.
• Students know how to design observers and observer-based controllers.
• Students know the basics about optimal control and how to utilize it.
• Students know the class of linear, parameter-varying systems and the basic principles of controller synthesis for this class of systems.
• Students understand the concept of model-predictive control and know how to implement such a control strategy.
• Students will have comprehensive knowledge of using control algorithms in practice.
• They are able to realize control systems in teamwork and in a self-directed manner.
• They have the communication competency to document and present project results.

Grading through:

• Oral examination

Responsible for this module:

• Prof. Dr. Philipp Rostalski

Teacher:

• Institute for Electrical Engineering in Medicine
• Prof. Dr. Philipp Rostalski
• Prof. Dr.-Ing. Christian Herzog

Literature:

• as described for the module parts :

Language:

• German and English skills required

Notes:

Last Updated:

22.03.2021