IRT-Institute of Automatic Control
Head of the Institute
Univ.-Prof. Dr.-Ing. Dirk Abel
Field of Study
all (control engineering is a compulsory subject for all fields of study of faculty 4)
Together with the Chair of Process Control Engineering and the Chair of CS11 (Embedded Software), the institute of Automatic Control coordinates the interdisciplinary Master program Automation Engineering.
The Institute of Automatic Control has been representing control and automation engineering in the Faculty of Mechanical Engineering at RWTH Aachen University since 1957. The chair sees itself as a representative of control theory in the diverse application areas of control and automation technology within mechanical engineering and other engineering, natural and life sciences. Current methodological emphases are model-based predictive control, robust control, the study of digitally networked control systems, sensor fusion and machine learning in industrial control engineering.
The guiding principle of the Institute of Automatic Control is based on the technical transfer of the theoretical principles of control engineering to concrete applications on a practical scale and is divided into the groups of biomedical engineering, energy process engineering, mobility, industrial systems, navigation solutions, production systems and wind energy in accordance with its core areas.
The "Biomedical Engineering" group is dedicated to novel technologies for the healthcare of the future. The research efforts focus on new technical solutions for patients as well as on the support of medical personnel. The group develops mathematical models of the human body across the various applications. Increasingly, data-supported approaches from machine learning and artificial intelligence are also being used.
The "Energy Process Engineering" working group conducts research on innovative, model-based control concepts that enable efficient and safe operation of complex energy systems. On the one hand, research efforts focus on the economic and ecological provision of energy for mobile applications and the fuel cell. In addition, stationary applications such as solar thermal power plants, storage-based hybrid energy systems and gas turbines are also the subject of current investigations.
The "Mobility" group researches the cross-modal automation of, for example, road vehicles, ships, trains and multicopters. Research focuses on modeling vehicle dynamics, planning safe and goal-oriented trajectories, and tracking a desired trajectory using modern control methods. As an important basis for vehicle automation, ambient and vehicle data are also obtained with the aid of comprehensive sensor technology and linked in a useful way, for example, to assess the current traffic situation and carry out a risk assessment.
The "Industrial Systems" group conducts research on a wide range of topics relating to the automation of industrial systems and plants in order to increase their performance and effectiveness. The focus is on process modeling and control, with the goal of transferring theoretical control engineering approaches to industrial applications. Conventional approaches of physical modeling are extended by current methods of machine learning. This combination allows the high model quality of data-based approaches to be combined with existing expert knowledge. The use of model-based controllers also allows increasing safety and quality requirements in the industrial context to be explicitly taken into account and integrated into the controller design.
The "Production Systems" group conducts research on a wide range of automation technology issues in the context of various production and manufacturing processes. The goal of intelligent manufacturing systems requires autonomous process control and monitoring in order to achieve high reproducibility even in the case of changing process conditions. For this purpose, the group also investigates the tracking of higher-level process and quality variables in addition to machine-related control loops. Adaptive control concepts allow the cyclic nature of many production processes to be mapped and an iterative improvement of process control to be realized. In the course of the digitalization of modern production plants, data-based approaches are also increasingly being used to supplement the mostly physical process description. Advanced methods for model-based optimization are being investigated for increased process stability in the manufacturing environment.
The "navigation solutions" group prepares the basis for autonomous driving systems using satellite navigation and inertial sensor technology, with explicit use of the European navigation system Galileo. Furthermore, an evaluation of the integrity of the determined navigation solution and its confidence level plays a key role for the application in safety-critical areas. Overall, the focus is on improving important localization properties, such as availability, reliability and accuracy through sensor fusion and the inclusion of external data, in order to derive a reliable statement about the dynamic state of the vehicle under consideration. This state in turn forms the basis for trajectory determination and control in the context of vehicle automation.
The research focus of the "Wind Energy" group lies in the area of innovative model-based control methods in the multifaceted topic of wind energy. Within this thematic framework, the research group develops model-based predictive control and estimation methods for wind turbines in order to simultaneously achieve power maximization and load minimization while maintaining operating limits. Also, novel hardware-in-the-loop methods for virtualization of physical components are investigated in order to integrate megawatt-class wind turbines into multi-physical test benches.
IRT - Institute of Automatic Control
52074 Aachen / GERMANY