The "Control Engineering" module consists of 3 module elements:
- Fundamentals of Control Engineering,
- Digital Control Engineering,
- Control Engineering Laboratory

The module explains the fundamentals of control engineering in the time domain and in the frequency domain in order to use them for the treatment of linear time-invariant systems in control engineering.
The focus is on the analysis of technical systems in the frequency domain and the synthesis of closed control loops with common control algorithms. The controller is designed using analytical and graphical methods such as the root locus method, the Nyquist locus curve and the Bode diagram. Simple optimization methods for control loops are also presented.
The module concludes with a brief look at the description method in state space and associated solution methods using the matrix e-function.
Control engineering simulation tools are used to support the module.
A problem from the field of control engineering is solved in groups in the laboratory as part of the "Control Engineering Laboratory" module. The module is completed with a written examination, which includes the module elements 'Fundamentals of Control Engineering' and 'Digital Control Engineering'.

The module 'Introduction to Electrical Engineering I'
of the international Master's degree program 'M.Sc. Mechatronics' comprises the module elements:
- Electrical Engineering and
- Linear Control

The module element 'Linear Control' presented here teaches the basics of linear control technology in the frequency domain and, building on this, introduces the system description in the state space (time domain).
The frequency domain methods focus on the description of technical systems using linear, time-invariant transfer elements, as well as the associated controller synthesis with common closed-loop control algorithms. The root locus method, Nyquist locus curves and Bode diagrams are used for controller design.
In the subsequent system description in state space, the mathematical principles are taught using differential equations and normal forms are introduced. This is then used to explain the design of state control systems.
In the 'Linear Control' module, control simulation tools are used as support. Laboratory experiments are offered as an option. The module element 'Linear Control' is completed with a written examination.

The 'Mechatronic Systems' module first provides an overview of the components of mechatronic systems and introduces common mechatronic applications.
It then focuses on stationary robot systems as exemplary standard mechatronic systems. Aspects of the kinematics of rigid bodies and open kinematic chains are covered, as well as the coordinate transformations required to describe movements in the three-dimensional workspace of a stationary robot.
Building on this, procedures for deriving dynamic models are presented, as required for controlling robot movements.
The module then looks at the drive concepts typical of robots and introduces the necessary actuators (motors and gears).
The control loop is completed by presenting the internal sensor systems required to record the current positions, speeds and acting forces/torques of the robot axes.
The lecture is underpinned by suitable exercises for the theoretical part.
As part of the coursework in this module, a problem from the field of robotics is solved in groups in the laboratory.
The module is completed with a written examination.

The module 'Optimal and adaptive control of linear and non-linear systems' of the Master's degree program in Electrical Engineering provides an overview of the treatment of non-linear control systems and presents methods for their control. These are supplemented by considerations on the adaptive control of processes and the design of optimal controllers.
Non-linear systems usually occur in reality. Based on the linear methods of the lecture in the B.Sc. module element "Fundamentals of Control Engineering", more complex non-linear systems are examined here. First, systems are analyzed in the state space; then controller design methods are presented at the phase level. The methods covered are the harmonic balance method, control with 2- and 3-point characteristics and stability studies according to Lyapunov and Popov.
Building on this, general optimization methods in control engineering are examined. Evaluation and controller design criteria are dealt with. Essential methods are the optimization approach according to Lagrange, solution methods of Euler, Lagrange and Hamilton as well as the maximum principle of Pontryagin. Dynamic programming is taught using the Bellmann method. In adaptive control, the methods "Gain Scheduling", "Self Tuning" and "Model Reference" are introduced.
The theoretical part of the module is supported by suitable exercises and simulations.
The module includes laboratory experiments on non-linear control engineering as coursework. The module is completed with an examination (written/oral after prior notice).
Note: Lecture and exercise are held online in this module, the associated laboratory takes place in presence.

The 'Driver assistance systems' module teaches the basics for understanding driver assistance systems.
The following are presented:

• Driving behavior, driving safety, active and passive systems
• Properties of tires, braking processes, anti-lock braking systems (ABS), traction control (ASR)
• Electronic Stability Program (ESP)
• Automatic braking functions (e.g. HHC), electro-hydraulic brake (SBC), electromechanical brake (EMB)
• Adaptive cruise control (ACC)
• Lane departure warning and lane change assistants, active steering
• Occupant protection systems
• Parking aid, vehicle lighting
• Vehicle information systems, navigation
• Automated driving

The exercise in the Driver Assistance Systems module teaches the basics of setting up simulations in the field of driver assistance systems.
The exercise covers the following topics

• Modeling in vehicle dynamics
• Simulations to verify the operation of several
  driver assistance systems

The module is completed with a written examination.

The 'Advanced Driver Assistance Systems' module teaches the basics of understanding driver assistance systems.
The following are presented:

• Driving behavior, driving safety, active and passive systems
• Properties of tires, braking processes, anti-lock braking systems (ABS), traction control (ASR)
• Electronic Stability Program (ESP)
• Automatic braking functions (e.g. HHC), electro-hydraulic brake (SBC), electromechanical brake (EMB)
• Adaptive cruise control (ACC)
• Lane departure warning and lane change assistants, active steering
• Occupant protection systems
• Parking aid, vehicle lighting
• Vehicle information systems, navigation
• Automated driving

The exercise in the Driver Assistance Systems module teaches the basics of setting up simulations in the field of driver assistance systems.
The exercise covers the following topics

• Modeling in vehicle dynamics
• Simulations to verify the operation of several
  driver assistance systems

The module is completed with a written examination.

The "Control Engineering" module consists of 3 module elements:
- Fundamentals of Control Engineering,
- Digital Control Engineering, -Control Engineering Laboratory

The lecture focuses on the treatment of digital control systems. Requirements and design methods for digital controllers are examined. The methods covered include the z-transformation, quasi-continuous controller design, the description of the digital control loop, classic digital controllers and dead-beat controllers.
As part of the "Control engineering laboratory" module, a problem from the field of control engineering is solved in groups in the laboratory. The module is completed with a written examination, which includes the module elements 'Fundamentals of Control Engineering' and 'Digital Control Engineering'.

In the module "Introduction to Control Engineering for Computer Scientists", the relationships between signals in the time domain and in the frequency domain are explained in order to use them for the treatment of linear time-invariant systems in control engineering.
The focus is on the analysis of technical systems in the frequency domain and the synthesis of closed control loops with common control algorithms. The controller is designed using analytical and graphical methods such as the root locus method, the Nyquist locus curve and the Bode diagram. Simple optimization methods for control loops are also presented.
The module is completed with a written examination.

In this compulsory module of the M.Sc. in Electrical Engineering, the description of dynamic systems in the time domain is introduced by setting up the corresponding equations of state in common normal forms. Solution methods using the matrix e-function are explained.
Building on this, the calculation and synthesis of state controllers using pole placement is described and state estimation using deterministic observers is introduced.
The theory of decoupling multivariable systems and associated design methods are then presented. In addition, the module also outlines description options for non-linear systems and their decoupling.
The module also includes insights into the theory of the LQ controller and the KALMAN filter.
In this module, control engineering simulation tools are used for support. The module is completed with an oral examination.

In the module element "Laboratory practical programming", students gain a sound understanding and knowledge of the practical implementation of various aspects of programming microcontrollers and controlling drives. In addition, students learn how to read out various sensors and evaluate them using independently developed algorithms. After completing the "Programming laboratory practical course", students will be able to link, control and regulate various hardware components using their own programming elements.
Prior participation in the course "Algorithms and data structures for electrical engineers" is a prerequisite for this laboratory practical course. The practical laboratory course begins with a short introduction (introduction to the development environment and hardware, as well as the methods to be used). This is followed by the group-based implementation of the specified tasks in self-study. The progress of the work is discussed and documented in regular meetings with the supervisors. The laboratory internship is a course achievement in the B.Sc. degree program in Electrical Engineering.

In this interdisciplinary practical course, students acquire the necessary specialist skills in the field of automation and energy technology at Master's level and acquire methodological skills in their application.
Students are enabled to analyze complex tasks in the field of automation and energy technology and to practically apply what they have learned in the lectures as well as to select and apply suitable procedures for testing and verifying solutions.
The practical course includes laboratory experiments from the following subject groups:
- Reliability of technical systems and electrical measurement technology, - Power electronics and electrical drives, - Control engineering and autonomous robotics (RST), and - Electrical machines, drives and controls.
The laboratory practical course is a course achievement in the M.Sc.Electrical Engineering degree program.

The technical content of the individual seminar paper from the fields of control engineering, automation technology and robotics is agreed with the lecturers. They are secondary to the desired methodological skills (literature research and its summary/condensation) and key qualifications (lecture preparation and presentation in front of an audience) and can, if necessary, prepare and supplement a desired focus for student research projects and theses.
The seminar is an academic achievement in the B.Sc. degree program in Electrical Engineering (FPO 2012).

Only exams possible.

Only exams possible.