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
Direct data-driven control of linear systems: SOS, please
Sum-of-Squares (SOS) relaxation is a beautiful technique to solve nonconvex optimization problems. As computational capabilities continue to increase, so is the scope of engineering challenges that can be tackled with this method. The goal of this project is to exploit the flexibility of SOS relaxations to design new data-driven control methods for linear dynamics, that can more efficiently incorporate prior knowledge on the system and cope with noisy input-output data.
Keywords
Data-driven control, linear systems, Sum-of-Squares optimization, polynomial programming
Labels
Master Thesis , Theory (IfA) , Computation (IfA) , Applications (IfA)
Description
Goal
Contact Details
More information
Published since: 2024-04-16 , Earliest start: 2023-11-29
Organization Automatic Control Laboratory
Hosts Bianchi Mattia , Schneeberger Michael
Topics Mathematical Sciences , Information, Computing and Communication Sciences
Connecting player interaction structure and decision-making dynamics to supply chain stability
In this project, we will investigate how the productivity level of a global supply chain is impacted by local interaction structures and decision-making dynamics via mathematical analysis and simulation. We will extend existing models on the two-player supply chain game to multi-player supply chains with non-trivial connectivity structures modeled via graph theory, and investigate various player dynamics (e.g. consensus, best response, gradient descent) in combination with different interconnection structures(e.g. trees, small-world network, star) to study the stability of the overall supply chain.
Keywords
supply chain, optimization, game theory, stochastic games, gradient descent, consensus,
Labels
Master Thesis
Description
Goal
Contact Details
More information
Published since: 2024-04-05 , Earliest start: 2023-08-28 , Latest end: 2024-06-30
Organization Automatic Control Laboratory
Hosts Hall Sophie , De Pasquale Giulia , Li Hui
Topics Mathematical Sciences , Engineering and Technology
Control in competitive settings: Open-loop or feeedback Nash equilibria?
Many control applications involve the interactions between different autonomous decision makers. Game theory models competition and cooperation between selfish agents. The most prominent solution concepts is the Nash equilibrium, a point at which no individual agent can improve its payoff by unilaterally changing its decision. In this master thesis we want to compare competitive behaviors resulting from feedback NE and open-loop NE understanding on the differences on a theoretical level but also what implications for they have for control in application such as autonomous driving or racing.
Keywords
Control theory, Game theory, Robotics, Autonomous Driving
Labels
Master Thesis , ETH Zurich (ETHZ)
PLEASE LOG IN TO SEE DESCRIPTION
More information
Published since: 2024-04-03 , Earliest start: 2024-05-01 , Latest end: 2025-04-30
Organization Automatic Control Laboratory
Hosts Hall Sophie , Bolognani Saverio
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
How low can you go? Optimal control of buildings with minimal number of sensors
Buildings are a major contributor to global energy consumption. Better building automation can help reduce the energy consumption and thus the operating cost of a building. This, however, comes at the cost of installing additional sensors and actuators. The goal of this project is to find the optimal trade-off between the two with the exciting real-world example of Empa's famous Nest building.
Keywords
energy, building automation, sensors, control, Nest
Labels
Master Thesis , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
More information
Published since: 2024-03-04 , Earliest start: 2024-03-01
Organization Automatic Control Laboratory
Hosts Fischer Claudia
Topics Engineering and Technology
Controller Design for Resilience in Supply Chains
In this project we will design a robust MPC controller for flexibility in supply chains. The objective is to guarantee better response to abrupt changes in demand. Specifically we will design a MPC controller that optimally tunes the flexibility, namely the capability of a firm to substitute and reroute products along existing pathways. By enhancing flexibility the system can effectively mitigate the impact of disruptions.
Keywords
Supply chain, Robust MPC, Resilience, Flexibility.
Labels
Master Thesis
Contact Details
More information
Published since: 2024-02-29 , Earliest start: 2023-10-01
Organization Automatic Control Laboratory
Hosts Soloperto Raffaele , De Pasquale Giulia
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Data Driven Control Approach for Recommender System Design
The objective of this project is the design and analysis of a smart recommender system as a dynamic feedback controller that, given (some of) the opinions in the system (measured outputs), provides news (namely, the control input) which is tailored to it. The recommender system objective is to optimize his performances, e.g., to maximize engagement, reduce polarization, or robustify against malicious agents. In contrast to other works, we will incorporate learning into this design, using methods from Data-Driven Control.
Keywords
Recommender Systems, Data Driven Control
Labels
Master Thesis , ETH Zurich (ETHZ)
More information
Published since: 2024-02-29 , Earliest start: 2024-03-01
Organization Automatic Control Laboratory
Hosts Eising Jaap , De Pasquale Giulia
Topics Information, Computing and Communication Sciences , Engineering and Technology
Primal-dual Feedback Optimization for Power Grid Operation
Feedback optimization is emerging as an important control method for modern power systems, thanks to its robustness and ability to steer the grid to an efficient operating point. In this project, we will design and evaluate novel feedback optimization schemes, based on Lagrangian dual methods, which can handle safety constraints and promise improved robustness to measurement noise.
Keywords
Computational control, optimization, primal-dual methods, smart grid
Labels
Master Thesis , Theory (IfA) , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
More information
Published since: 2024-02-28
Organization Automatic Control Laboratory
Hosts Moffat Keith , Bianchi Mattia
Topics Mathematical Sciences , Information, Computing and Communication Sciences
Joint Energy Hub and Electric-Bus Fleet Management under Bidirectional Charging
Battery-powered electric buses can be interpreted as large-scale, mobile, electricity storage devices. The schedules and locations of electric buses are relatively predictable with regards to fixed routes, such as in the twice daily runs of school buses. When an electric bus is not serving its route, it can schedule its charging/discharging to provide ancillary services to the main grid in exchange for monetary incentives. This is often referred to as Vehicle-to-Grid (V2G). Simultaneously, a fleet of electric buses can play a key role as a source of demand-side flexibility to support the system in managing operational uncertainty, resulting in the generation of new revenue streams. The onsite coupling of electric buses with site resources in a Vehicle-to-Everything (V2X) setting has shown extremely promising performance in terms of both site self-sufficiency maximization and demand-side flexibility provision. This project will investigate economic model predictive control (MPC) to reduce energy costs and maximize service revenues in the scenario of joint control of an energy hub (e.g., depot, school campus, parking lot) and its buses. Flexibility envelopes will be developed to estimate the flexibility potential and the corresponding market revenues generated with this joint control architecture, as compared to unpredictable arrival/departure times and with separate control policies. Since the flexibility provision market is highly regulated, we plan to include Swiss/EU regulations as hard constraints in our formulation. Extensions will include the effects of different depreciation models and cases where the energy hub is equipped with Photovoltaic generation, electricity storage (battery/hydrogen), and/or thermal storage.
Keywords
Bus, Electricity Storage, Battery, Vehicle-to-Grid, Flexibility, Energy Hub, Model Predictive Control
Labels
Semester Project , Master Thesis , ETH Zurich (ETHZ)
Description
Goal
Contact Details
More information
Published since: 2024-02-28 , Earliest start: 2024-03-18 , Latest end: 2024-11-25
Applications limited to ETH Zurich , Empa
Organization Automatic Control Laboratory
Hosts Miller Jared
Topics Engineering and Technology
Scan Path Generation for a Novel Highly Efficient Powder Bed Fusion (PBF) Machine
The collaboration between Advanced Manufacturing Lab (am|z) and Automatic Control Lab (IFA) is centered on developing a novel scan path generator for a laser powder bed fusion (PBF) machine capable of processing multiple materials simultaneously. The aim is to integrate the Machine Control Framework (AMCF) with our machine control system to enhance controlability and reliability.
Keywords
Programming, Software, Architecture, Control, Javascript, Scan path, Laser, Powder bed fusion,
Labels
Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
Description
Goal
Contact Details
More information
Published since: 2024-02-21 , Earliest start: 2024-02-14
Organization Advanced Manufacturing Laboratory
Hosts Balta Efe , Steffen Raphael
Topics Information, Computing and Communication Sciences , Engineering and Technology
Crypto-governance with karma
The revolutionary appeal of cryptocurrencies and the underlying distributed ledgers is that no one owns them. They are highly democratic systems (at least in principle): the community sets the rules of the ledger and maintains it. This has the unique feature of being highly dynamic and adaptable to the latest greatest in technology and societal needs. But to fully deliver on their appeal, distributed ledgers must employ a fair and efficient mechanism for self-governance. Should a ledger change its protocol, e.g., from proof-of-work to proof-of-stake? How should a newly identified bug be resolved? Many distributed ledgers have adopted voting-like mechanisms for this purpose, but crucially, voting rights are associated with the amount of tokens owned, and as a direct consequence, with the wealth of the users, contradicting the most basic principles of democracy. However, unlike in classical political decisions, crypto-governance decisions are highly dynamic and frequent - they almost occur in real-time. This makes them especially suited for a karma economy, which has been recently demonstrated to achieve highly fair and efficient outcomes in repetitive settings in a completely non-monetary manner.
Labels
Semester Project , Master Thesis
Description
Contact Details
More information
Published since: 2024-01-12 , Earliest start: 2024-01-15
Organization Automatic Control Laboratory
Hosts Elokda Ezzat
Topics Information, Computing and Communication Sciences
Robustify Feedback Optimization through Regularization
Optimal steady-state operations are crucial for engineering systems. A promising paradigm called feedback optimization (FO) features autonomous optimality seeking with a minimal requirement on model information, i.e., the input-output sensitivity. In applications, however, uncertainties (e.g., random failures and parameter shifts) may cause a model mismatch, thus resulting in closed-loop sub-optimality. To address this critical issue, we will explore robustifying FO against structured model mismatch through regularization. To this end, we will formulate a min-max closed-loop optimization problem and solve the reformulated regularized problem in an online fashion. We will characterize the optimality and stability of the closed-loop behavior. Furthermore, we will numerically validate the effectiveness of the proposed algorithm.
Keywords
Feedback optimization, robust optimization,power system
Labels
Semester Project , Bachelor Thesis , Master Thesis
Description
Goal
Contact Details
More information
Published since: 2023-12-08 , Earliest start: 2024-01-01 , Latest end: 2024-09-15
Organization Automatic Control Laboratory
Hosts Bolognani Saverio , Moffat Keith , He Zhiyu
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Contact
ETH Zurich
Automatic Control Laboratory
Physikstrasse 3
8092 Zurich
Switzerland