Interconnected Automation Systems (IAS)
At the Chair of Interconnected Automation Systems (IAS) at the University of Siegen, we drive basic and applied research on design automation of software and hardware to improve the reliability, efficiency and sustainability of modern cyber-physical infrastructures - from industrial and mechatronic systems to energy conversion applications and electrical power systems.
Mission statement
We conduct rigorous, open and responsible research on interconnected automation systems and translate sound modeling, control and data-driven methods into trustworthy technologies that increase safety and reliability, reduce energy plus resource consumption and strengthen resilient infrastructures for the benefit of society. In teaching, we qualify engineers and researchers to combine a physical-analytical understanding of systems with computer-aided and data-oriented tools so that they can actively shape future generations of automation and energy systems.
Chair's head
Research profile
We research networked cyber-physical systems in industrial automation and mechatronics as well as in electrified energy technologies. Central fields of application are electric drives, power electronic converters, energy storage systems and charging infrastructures as well as networked electrical energy systems such as microgrids - with the aim of enabling more reliable, efficient and resilient operation under real operating conditions.
Our work covers the entire innovation chain from basic research to industrial transfer. A particular focus is on translating theoretical concepts into practical proof-of-concepts, supported by rapid software and hardware prototyping. Experimental validation, including targeted measurement campaigns on relevant test benches, is an integral part of our research process.
Open science is a cornerstone of our research practice. We publish open source software, reproducible workflows and other open resources to enable transparent evaluation, benchmarking and rapid knowledge transfer for students, researchers and industry partners. Our open source contributions can be found on GitHub: https://github.com/IAS-Uni-Siegen
Focus areas
- Optimal control methods (e.g., reinforcement learning, differential predictive control)
- Hardware design, optimization and testing of power electronic converters (component and system level)
- Hybrid modeling and system identification (combination of expert and data knowledge)
- Condition monitoring, diagnostics and digital twins (e.g. using fault and anomaly detection)
- State and parameter estimation (observer, co-estimator)
- Software-driven automation (reproducible design toolchains, verification and benchmarking)
Latest publications
Electric 2-wheeler drive cycle based drivetrain sizing: A comprehensive analysis
Electric 2-wheeler drive cycle based drivetrain sizing: A comprehensive analysis
Adaptive Operating Strategy for Induction Motors Under Changing Electrical-Thermal Conditions
Adaptive Operating Strategy for Induction Motors Under Changing Electrical-Thermal Conditions
Model Predictive Torque Control for Permanent Magnet Synchronous Motors Using a Stator-Fixed Harmonic Flux Reference Generator in the Entire Modulation Range
Model Predictive Torque Control for Permanent Magnet Synchronous Motors Using a Stator-Fixed Harmonic Flux Reference Generator in the Entire Modulation Range
Experimental Comparison of FPGA-Implemented Model Predictive Voltage Control to Cascaded Proportional Resonant Control for a Three-Phase Four-Wire Three-Level Grid-Forming Inverter of 250 kVA
Experimental Comparison of FPGA-Implemented Model Predictive Voltage Control to Cascaded Proportional Resonant Control for a Three-Phase Four-Wire Three-Level Grid-Forming Inverter of 250 kVA
Steady-State Error Compensation in Reference Tracking and Disturbance Rejection Problems for Reinforcement Learning-Based Control
Steady-State Error Compensation in Reference Tracking and Disturbance Rejection Problems for Reinforcement Learning-Based Control
An Open-Source Transistor Database and Toolbox as a Unified Software Engineering Tool for Managing and Evaluating Power Transistors
An Open-Source Transistor Database and Toolbox as a Unified Software Engineering Tool for Managing and Evaluating Power Transistors
Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations
Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations
A Sustainable Rural Electrification based on Socio-Techno-Economic-Environmental-Political Microgrid Design Framework
A Sustainable Rural Electrification based on Socio-Techno-Economic-Environmental-Political Microgrid Design Framework
An Open-Source FEM Magnetic Toolbox for Calculating Electric and Thermal Behavior of Power Electronic Magnetic Components
An Open-Source FEM Magnetic Toolbox for Calculating Electric and Thermal Behavior of Power Electronic Magnetic Components
Finite Set Sensorless Control With Minimum a Priori Knowledge and Tuning Effort for Interior Permanent Magnet Synchronous Motors
Finite Set Sensorless Control With Minimum a Priori Knowledge and Tuning Effort for Interior Permanent Magnet Synchronous Motors
Improved exploring starts by kernel density estimation-based state-space coverage acceleration in reinforcement learning
Improved exploring starts by kernel density estimation-based state-space coverage acceleration in reinforcement learning
Model Predictive Control of Permanent Magnet Synchronous Motors in the Overmodulation Region Including Six-Step Operation
Model Predictive Control of Permanent Magnet Synchronous Motors in the Overmodulation Region Including Six-Step Operation
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Opening hours secretariat
Opening hours
Postal address
University of Siegen
Chair of Interconnected Automation Systems (IAS)
Hölderlinstraße 3
57076 Siegen
Visitor address
University of Siegen
Chair of Interconnected Automation Systems (IAS)
H-A Level 4
Room: H-A 4106/3
Hölderlinstraße 3
57076 Siegen
Secretariat
Secretary: Lada Lübke
Phone: +49 (0)271 / 740-3305
Fax: +49 (0)271 / 740-13305
Room: H-A 4106/3
E-Mail: IAS-office@eti.uni-siegen.de