Re­ge­lungs­tech­nik

This course focuses on automating dynamic systems using feedback to influence system behaviour. Examples of real-life control systems include robotics, satellite systems, automobile, automatic anaesthesia control, and many other mechanical, electrical and chemical systems. The ultimate objective of these methods is to drive the system to a desired state by minimising the error between the system’s actual output and desired set point. Various design criteria are considered, including, but not limited to, overshoot, steady-state error, stability, and optimality. Eventually, these methods are used to increase production efficiency, reduce the cost per unit of production, ensure manufacturing consistency, and improve human safety. Control theory is also a part of industry 4.0 technologies, which have been revolutionising manufacturing methods using the internet of things (IoT), cloud computing, artificial intelligence (AI), and next-generation wireless technologies (5G/6G networks). 

This course will cover the following content:

- Description of the system behaviour in the time and frequency domain
- Transient and state-state behaviour of systems
- PID controller
- Closed-loop stability
- Design of SISO control loops
- Root locus
- Basics of digital control