Motivation:

In modern automation, robotics, and control engineering, the ability to manage unstable systems in real time is a theoretical and practical challenge. The self-balancing robot serves as a control benchmark for its inherently unstable, nonlinear dynamics and the requirements for fast, feedback-based control.
This practical course offers master students the opportunity to bridge theoretical knowledge with practical implementation. Through the integration of embedded programming, sensor fusion, simulation development, and control system design, participants will develop a deep understanding of real-time control systems while enhancing their skills in problem-solving, teamwork, and innovation.
In addition to its academic value, the project aims to enhance the student’s industry insight, particularly regarding mobile and hydraulic systems. The self-balancing robot serves as a simplified model to inspire solutions for real-world challenges in autonomous mobile machines and intelligent hydraulic control systems.

Objectives:

• Understand closed-loop (feedback-based) controlled systems
• Model and analyze nonlinear and multi-input multi-output (MIMO) systems
• Use a given simulation tool to analysis the system behavior and validate control strategies
• Design, tune, and implement real-time control algorithms for experiments
• Evaluate system performance under disturbances and uncertainties
• Explore advanced nonlinear model-based / learning-based control strategies (optional)  
• Gain insight into industrial relevance, particularly for mobile robotics and hydraulic systems

B. Helian, G. Schmitt, M. Yang, Y. Bian and M. Geimer, "Reinforcement Learning-Based Control for Electrohydraulic Actuators: A Case Study on an Inverted Pendulum Testbench," in IEEE Transactions on Industrial Electronics, doi: 10.1109/TIE.2025.3587123.

• Kick-off-Meeting: 31.10.2025, 9:45–11:15, Building 70.04. Room 220 Campus East
• Midterm-Meeting: 18.12.2025, 13:00–14:30, Building 70.04. Room 219 Campus East
• Oral Exam: 12.02.2026, 13:00–18:00, Building 70.04. Room 219 Campus East
• Flexible weekly reports (approx. once every two weeks)