SA/BA/MA projects
Have you heard of industry 4.0, smart grids, smart buildings, smart cities, intelligent traffic systems and intelligent self-driving cars? Did you ever wonder what makes them smart and intelligent?
The answer is control and automation and that’s what we do at the Automatic Control Laboratory (IfA). We use control theory, optimization, machine learning, and game theory to develop controllers and algorithms that are the backbone of nearly all modern technology. At our lab we span the whole area from pure theory to real-world applications and we are looking for you to help us push forward the state of the art. If you want to learn techniques and gain knowledge that enable you to work in any field from medical applications to spacecraft and from electrical grids to finance then the Automatic Control Laboratory is the place for you!
Lists of currently running and recently completed projects can be found in the sub-navigation menu above. Reports for several projects are available through the ETHZ Research Collection:
Open projects
Advanced Volume Control for Pipetting
Improving volume control precision and robustness in automated pipetting remains a challenge, often limited by traditional indirect methods. This project explores direct volume control by leveraging internal air pressure measurements and the ideal gas law. Key obstacles include friction, pressure oscillations, varying liquid viscosities, evaporation, and liquid retention. Collaborating with Hamilton Robotics, the goal is to develop a robust control architecture for their precision pipette (MagPip) suitable for diverse liquids. The approach involves mathematical modeling based on sensor data, designing robust control strategies to handle nonlinearities and disturbances, and validating through simulation and real-world experiments.
Keywords
Modeling, nonlinear control, system identification, learning-based control, state estimation, fluid dynamics
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Semester Project
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Published since: 2025-04-14 , Earliest start: 2025-05-01 , Latest end: 2025-09-01
Organization Automatic Control Laboratory
Hosts Zakwan Muhammad
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Iterative Learning Control for Additive Manufacturing Processes
Additive manufacturing, commonly known as 3D printing, has seen widespread adoption in many engineering fields, including biomedical, aerospace, and automotive applications. Its ability to manufacture complex designs accurately and quickly offers significant advantages in rapid prototyping, customization, and design flexibility for mechanical assembly. As an additive manufacturing technique, fused deposition modeling (FDM) is governed by two key dynamics: motion and extrusion. In FDM, a triple axis system controls the movement of the extrusion head, which melts and deposits plastic filament onto the printing bed. However, these dynamics are inherently coupled, whereby the extrusion width is directly affected by the motion of the system. Given that the printing motion is highly repetitive, it is advantageous to leverage this behavior when designing a control system.
Keywords
Motion control, adaptive control, learning control, robotics
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Semester Project , Master Thesis
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Published since: 2025-03-27 , Earliest start: 2025-03-31
Applications limited to ETH Zurich
Organization Automatic Control Laboratory
Hosts Hoteit Rawan , Zuliani Riccardo , Balta Efe
Topics Engineering and Technology
Feedback Optimization for Freeway Ramp Metering
Online Feedback optimization (OFO) is a beautiful control method to drive a dynamical system to an optimal steady-state. By directly interconnecting optimization algorithms with real-time system measurements, OFO guarantees robustness and efficient operation, yet without requiring exact knowledge of the system model. The goal of this project is to develop faster OFO schemes for congestion control on freeways, in particular by leveraging the monotonicity properties of traffic networks.
Keywords
Feedback optimization, monotone systems, freeway ramp metering, timescale separation
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Master Thesis
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Published since: 2025-03-19 , Earliest start: 2025-01-15 , Latest end: 2025-12-15
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Empa
Organization Automatic Control Laboratory
Hosts Chandrasekaran Sanjay , Bianchi Mattia
Topics Engineering and Technology
Contact
ETH Zurich
Automatic Control Laboratory
Physikstrasse 3
8092 Zurich
Switzerland