Main research topics at the Institute of Mechatronic Systems (imes) include design, simulation, optimization, and control of complex mechatronic systems. Therefore, latest modelling, control theory, parameter identification, state observer, as well as numerical optimization techniques are applied. Thanks to the institute’s electrical and mechanical workshops test stands and prototypes can be easily built and used for validation. The above mentioned methods are applied in numerous state and industry funded projects which are described in the following.
Identification & Control
The requirements for passenger cars and commercial vehicles regarding safety, comfort, and environmental performance have continuously increased during the last decades. Examples for this development are various mechatronic control systems such as ABS, ASR, ABC, and ESP. These systems require an exact knowledge of the vehicle state at any time in order to take corrective actions if necessary. Therefore, model-based estimation of the car’s state variables is needed as currently available sensors do not provide sufficient information. Within this context, the imes is developing robust and reliable methods for the identification and control of mechatronic systems in motor vehicles in close cooperation with industrial partners.
Medical Technology & Image Processing
Today's surgical interventions are characterized by a high level of complexity as a result of the continuously rising demands on the surgeon. In order to conduct surgeries on smaller anatomical structures as well as to minimize postoperative trauma for the patients innovative tolls are needed. They combine highly sophisticated components from areas such as information technology, image technology, and mechatronics. In close cooperation with medical experts, engineers and computer scientists the research group Medical Technology & Image Processing works on innovative projects in the field of instrument engineering and computer assisted high precision surgery
Robotics & Autonomous Systems
The research group Robotics & Autonomous Systems focuses on kinematic and dynamic modeling as well as motion planning for complex mechatronic systems, with the emphasis on multi-body systems and autonomous, mobile (service) robots. Exemplary fields of work are the study of flexibly usable robot concepts and the development and implementation of customized, application-specific mechatronic solutions, e. g. for mechatronics-assisted surgery. Further, the topics of universal modeling and identification methods are explored and used for model-based control approaches or (energy) optimal motion planning to meet the continuously rising demands of economical, highly accurate, yet highly dynamic systems.
Integrated Systems & Machine Learning
Besides embedded computing capacity and intelligence today‘s mechatronic systems feature increasing degrees of interconnection, integration into other levels of industrial production processes and internet access. In this context the new research group for Integrated Systems & Machine Learning is concerned with current issues arising from the continuously proceeding digitization of industrial production. The key activities are the system wide acquisition, preparation and allocation of system, process and sensor data from the field and machine levels. Besides enhanced functionality of monitoring and analysis, e. g. methods of machine learning lead to possibilities for the prediction of machine and process failure and, hence, to the planning of preventive maintenance intervals. In combination with data mining methods, gain in additional information and added values by analysis if big data is expected. Versatile possibilities for plant and process optimization arise, amongst others including the objectives of increased productivity, flexibility and resource efficiency. The institute’s manifold competence and expertise, e. g. in the fields of modelling and parameter identification, planning of energy efficient motion and process sequences as well as model based control methods shall be transferred to integrated system modules. The aim are mechatronic systems with cognitive capabilities to manage automated self-diagnosis, -configuration and -optimization.