Open Master's Thesis Positions
On this page you will find a selection of possible Master Thesis opportunities, some notified to us directly by the research groups of MEST Tutors and some listed on the SiROP database.
This list is not exhaustive, other Thesis projects might exist, please check the respective listings of Departments and research groups you are particularly interested in.
See also Internship opportunities.
None currently to display.
Projects from the SiROP Database
ETH Zurich uses SiROP to publish and search scientific projects. Here is a selection of projects currently available which may be suitable for MEST students. For more information visit external pagesirop.orgcall_made.
Design and Control of a Hydroponics System
Hydroponics is a technique to grow plants without soil, but therefore in nutrient rich solutions. This project aims to construct a small scale fully automated hydroponics system, including the hardware, controller and filter designs, and software implementation. The implementation will finally be validated by growing actual plants. Hydroponics offers an alternative to conventional agriculture, minimizing water usage, fertilization and space requirements and allowing to create optimal environments for plants to grow. Combined it offers a potential future technology to fight food limitations in the face of a rising world population and climate change. Show details
Keywords
Control Theory, Engineering, Hydroponics
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Master Thesis
Description
Goal
Contact Details
Applications limited to: ETH Zurich
Organization: Automatic Control Laboratory
Hosts: Schmid Niklas
Topics: Mathematical Sciences , Engineering and Technology
Details: Open this project...
Reinforcement Learning Control with Probabilistic Safety
When controlling a system we typically aim to make the system carry out specific tasks, like remaining in a set of states, or reaching a set of states, or both. Recent advances allow to formulate controllers using dynamic programming that trade off such specifications optimally against costs, such as energy consumption. However, these methods rely on full model knowledge; it is the aim of this project to explore model-free attempts towards achieving these objectives. The approach will be validated on the Ball-on-a-Plate system, which is a mechanically actuated plate with a ball on it. Show details
Keywords
Machine Learning, Reinforcement Learning, Control Theory, Safety, Stochastic Systems
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Master Thesis
Description
Goal
Contact Details
Applications limited to: ETH Zurich
Organization: Automatic Control Laboratory
Hosts: Schmid Niklas
Topics: Mathematical Sciences , Engineering and Technology
Details: Open this project...
Robotic 3D printing Microbial Biocement
The project investigates different bio-inks for extruding large-scale 3D printing bio-cementation structures. The extruded paste will host microorganisms such as S.Pasteurii, capable of precipitating calcite (MICP) to create bio-concrete structures. A robotic paste 3D printing platform will be used for the fabrication process; the bio-paste will be precipitated and calcified by the bacterial activity reinforcing the material. Show details
Keywords
Living materials, bio-inks, 3D printing, hydrogel, architecture, bio-cementation, MICP
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Semester Project , Internship , Master Thesis , ETH Zurich (ETHZ)
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Earliest start: 2024-03-31
Latest end: 2024-07-31
Organization: Digital Building Technologies
Hosts: Antorveza Karen
Topics: Engineering and Technology , Biology , Architecture, Urban Environment and Building
Details: Open this project...
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. Show details
Keywords
energy, building automation, sensors, control, Nest
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Master Thesis , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
Earliest start: 2024-03-01
Organization: Automatic Control Laboratory
Hosts: Fischer Claudia
Topics: Engineering and Technology
Details: Open this project...
Mycelium bound composites based on textiles
The project aims to explore the bio-fabrication of mycelium-based composites and knitted textiles for architecture and construction. Specifically the textile is used as a growing substrate for mycelium material, offering a sustainable and biodegradable building material and structural system that is strong in both tension and compression. Show details
Keywords
mycelium,textiles,performance,construction, bio-fabrication
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Semester Project , Internship , Bachelor Thesis , Master Thesis , Other specific labels , ETH Zurich (ETHZ)
Description
Goal
Contact Details
Earliest start: 2024-04-01
Latest end: 2024-11-01
Organization: Digital Building Technologies
Hosts: Dillenburger Benjamin
Topics: Engineering and Technology
Details: Open this project...
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. Show details
Keywords
Supply chain, Robust MPC, Resilience, Flexibility.
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Master Thesis
Contact Details
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
Details: Open this project...
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. Show details
Keywords
Recommender Systems, Data Driven Control
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Master Thesis , ETH Zurich (ETHZ)
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
Details: Open this project...
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. Show details
Keywords
Computational control, optimization, primal-dual methods, smart grid
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Master Thesis , Theory (IfA) , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
Organization: Automatic Control Laboratory
Hosts: Moffat Keith , Bianchi Mattia
Topics: Mathematical Sciences , Information, Computing and Communication Sciences
Details: Open this project...
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. Show details
Keywords
Bus, Electricity Storage, Battery, Vehicle-to-Grid, Flexibility, Energy Hub, Model Predictive Control
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
Description
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Contact Details
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
Details: Open this project...
Data-driven policy iteration schemes based on linear programming
Learning how to optimally regulate a dynamical system from data is a fundamental problem in control theory. This project focuses on investigating new theory and methods about policy iteration schemes based on linear programming. Show details
Keywords
Optimization, Approximate Dynamic Programming, Policy Iteration, Linear Programming
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Semester Project
Description
Goal
Contact Details
Earliest start: 2024-05-01
Latest end: 2024-09-30
Organization: Automatic Control Laboratory
Hosts: Falconi Lucia
Topics: Information, Computing and Communication Sciences
Details: Open this project...
Development of a Conceptual Framework for Resilience Assessment of Smart Energy Systems
In the era of climate change and growing global energy demand, smart energy systems have become pivotal in ensuring sustainable, efficient, and reliable energy delivery. These systems, characterized by the integration of advanced metering infrastructure, renewable energy sources, and innovative demand response technologies, form the backbone of modern energy strategies aimed at reducing carbon footprints and enhancing energy security. The Swiss Confederation, cognizant of these imperatives, advocates for a robust transition towards intelligent energy networks, setting the ambitious goal of a net-zero carbon economy by 2050. As we push the boundaries of energy system innovation, the imperative of resilience cannot be overstated. Resilience in this context refers to the smart energy system's capacity to anticipate, withstand, and recover from various forms of disruption like environmental phenomena, technical failures, or human-induced events. This project acknowledges the complexity and interdependence of the smart energy ecosystem, encompassing residential buildings equipped with the latest in energy-efficient technologies, user interfaces that allow for dynamic interaction with the energy grid, and decentralized renewable energy generation units that contribute to a sustainable energy mix. Electric vehicles (EVs), Heating, Ventilation, and Air Conditioning (HVAC) systems, and domestic appliances represent significant loads within the residential sector that can be managed to foster resilience. The bi-directional flow of energy in smart grids, facilitated by smart meters, allows for sophisticated energy management strategies that not only respond to system demands but also to user behaviors and preferences. The resilience of such an interconnected system hinges on its ability to maintain stability and operation despite unpredictable renewable energy generation patterns, potential cyber-physical threats, fluctuations in the energy market due to instability in the neighboring countries, and changes in user behavior. The Swiss energy paradigm provides an exemplary context for studying and enhancing the resilience of smart energy systems. By developing a conceptual framework for resilience assessment tailored to this context, this thesis aims to contribute to the body of knowledge that will empower stakeholders to design, implement, and maintain robust energy systems. Show details
Keywords
Resilience Assessment; Smart Energy System; Extreme social events
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Semester Project , Master Thesis
Description
Goal
Contact Details
Earliest start: 2024-03-01
Latest end: 2024-12-31
Organization: Urban Energy Systems
Hosts: Chatterjee Arnab
Topics: Information, Computing and Communication Sciences , Architecture, Urban Environment and Building
Details: Open this project...
Non-Intrusive Load Monitoring and Customer Segmentation assisted demand flexibility provision in Swiss Households
Switzerland is committed to transitioning to a renewable energy system. The Swiss government has set a target of achieving net-zero carbon emissions by 2050. This will require a significant increase in the use of renewable energy sources. The Swiss power grid is also vulnerable to imbalances be-tween supply and demand. Demand flexibility can help to mitigate this risk and ensure the reliable operation of the power grid. Demand flexibility is the ability to shift or reduce energy use in response to changes in sup-ply or price. This is becoming increasingly important as the power grid transitions to renewable energy sources, such as solar and wind power, which are intermittent and less predictable. Demand flexibility can help to balance the grid and reduce the need for expensive and polluting backup power plants. Non-Intrusive Load Monitoring (NILM) and customer segmentation modeling are powerful tools that can be used to develop demand flexibility programs. NILM can be used to identify high-energy-consuming appliances and to track their energy usage over time. Customer segmentation modeling can be used to identify different groups of customers based on their energy consumption patterns. This information can then be used to develop targeted demand flexibility programs that are more likely to be effective for each group of customers. Show details
Keywords
Non-Intrusive Load Monitoring; Customer Segmentation; Machine Learning; Demand Flexibility; Black-box Modelling
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Master Thesis
Description
Goal
Contact Details
Earliest start: 2024-01-08
Latest end: 2024-09-30
Applications limited to: Empa , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization: Urban Energy Systems
Hosts: Chatterjee Arnab
Topics: Information, Computing and Communication Sciences , Architecture, Urban Environment and Building
Details: Open this project...
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. Show details
Keywords
Programming, Software, Architecture, Control, Javascript, Scan path, Laser, Powder bed fusion,
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Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
Description
Goal
Contact Details
Earliest start: 2024-02-14
Organization: Advanced Manufacturing Laboratory
Hosts: Balta Efe , Steffen Raphael
Topics: Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Sheet Estimator for Laser Cutting Machine
In sheet metal laser cutting, the correct distance between the nozzle and the sheet is crucial for a stable cutting process. The nozzle distance control utilizes a capacitive signal generated between the sheet and the nozzle and calculates the current distance based on prerecorded calibration data. Steadily increasing laser power allows higher feed rates, which poses increasing challenges for the nozzle distance control. One approach to achieve superior control consists of generating a digital mapping of the sheet geometry allowing for predictive control. A “Sheet Estimator” would support the nozzle distance control and reduce the reaction delay in case of local changes in the sheet geometry. In addition, it could also detect situations where a cut-out part is tilted (crash risk) or the sheet metal starts to vibrate (poor cut) and thereby enable an adequate reaction. Show details
Keywords
data acquisition, machine calibration, pose estimation
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Semester Project , Bachelor Thesis
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Earliest start: 2024-04-02
Latest end: 2024-08-31
Organization: Automatic Control Laboratory
Hosts: Nobar Mahdi
Topics: Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Should humans fly in aerial vehicles?
In the majority of urban air mobility planning, goods such as Amazon packages and food are the targeted cargo population that urban air traffic will predominantly transport. Furthermore, this traffic will likely be conducted autonomously or in a semi-supervised style. This is in stark contrast to ground transportation, in which human-operated vehicles are the dominant population of ground transportation users. However, humans may wish to fly and/or navigate aerial vehicles themselves — for legal liability, for improvements in safety/efficiency, and/or for recreational purposes. While human-operated vehicles are most definitely less efficient than autonomous UAVs, it is not immediately obvious that the efficiency of overall air traffic will decrease when introducing human-operated aerial vehicles. Will air traffic efficiency decrease when human-navigated aerial vehicles operate alongside autonomous aerial vehicles in urban skies, and are there situations in which introducing human traffic will improve air traffic efficiency? Show details
Keywords
game theory, Markov decision process, traffic management, Braess paradox, optimization, routing games, aerospace engineering
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Semester Project , Master Thesis
Description
Goal
Contact Details
Organization: Automatic Control Laboratory
Hosts: Li Hui
Topics: Mathematical Sciences , Engineering and Technology , Economics
Details: Open this project...
Self-learning non-linear adaptive heating curve adjustment for intuitive optimization
The aim is to extend an existing linear self-learning algorithm that optimizes the heating curve depending on building physics and external parameters in terms of indoor comfort and energy efficiency. For this purpose, we are working together with one of our industrial partners in the building technology sector in order to be able to test executable prototypes under real conditions in their facilities in addition to the theoretical simulations. Show details
Keywords
Gaussian process modelling and Bayesian Optimization Optimization Dynamic heating curve adjustment Self-learning algorithm Industry related project Reduction of energy consumption while maintaining room comfort Generalization error - generic solution for use in all heating curve controlled heating systems Machine Learning
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Semester Project , Bachelor Thesis , Master Thesis
Description
Goal
Contact Details
Earliest start: 2024-02-11
Latest end: 2024-09-30
Organization: Urban Energy Systems
Hosts: Tell Alessandro , Locher Michael
Topics: Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Plug and play distributed control of energy networks using clustering strategies
In this project, we want to explore clustering methods for the plug and play distributed control of energy hubs and prosumer networks as well as distributed optimization methods that are blind to the local network. While standard distributed optimization method works well for a small number of hubs with a fixed network topology, changes in topology requires all the hubs in the network to modify their control and communication scheme and the optimization problem of each hub also grows drastically requiring a longer computation time. The goal is to develop strategies that mitigate these issues and can adapt to a rapidly changing energy network. Show details
Keywords
Optimization, Large-scale systems, Energy hub, multi-energy systems, networked system, distributed control, bi-level games
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Collaboration , Master Thesis , ETH Zurich (ETHZ)
Description
Goal
Contact Details
Organization: Urban Energy Systems
Hosts: Behrunani Varsha
Topics: Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Plug and play distributed control of energy networks using clustering strategies
In this project, we want to explore clustering methods for the plug and play distributed control of energy hubs and prosumer networks as well as distributed optimization methods that are blind to the local network. While standard distributed optimization method works well for a small number of hubs with a fixed network topology, changes in topology requires all the hubs in the network to modify their control and communication scheme and the optimization problem of each hub also grows drastically requiring a longer computation time. The goal is to develop strategies that mitigate these issues and can adapt to a rapidly changing energy network. Show details
Keywords
Optimization, Large-scale systems, Energy hub, multi-energy systems, networked system, distributed control, bi-level games
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Collaboration , Master Thesis , Computation (IfA) , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
Earliest start: 2023-09-03
Latest end: 2024-05-31
Organization: Automatic Control Laboratory
Hosts: Behrunani Varsha
Topics: Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Transfer Learning for Building Thermal Modeling
Buildings appear as significant energy consumers, especially due to the management of heating, ventilation, and air-conditioning (HVAC). Each building has unique characteristics such as varied geometries, floor layouts, construction properties, age, climatic regions, orientation, and service systems. Better control of indoor temperature in buildings seems to be a means of energy savings. Traditional approaches rely on building modeling for this purpose. While physics-based models may be precise and aligned with expected physical behaviors, their complex design can limit their application and scalability. An alternative modeling approach based solely on sensor data (temperature, solar irradiance, etc.) aims to be more flexible and is generating increasing interest. However, these approaches require diverse data in sufficient quantity to train the model parameters and might demand more computing power than what buildings can accommodate. The complexity of models, their instability, or the lack of data poses obstacles when attempting to model a new building. The primary goal of this project is to leverage the flexibility of data-driven methods to model the thermal behavior of buildings, emphasizing the development of a transferable model. This approach aims to streamline the modeling process by enabling the initial learning of a model for one building and its subsequent adaptation to other buildings. Show details
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Semester Project , Master Thesis
Description
Goal
Contact Details
Organization: Urban Energy Systems
Hosts: Montazeri Mina
Topics: Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
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. Show details
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Semester Project , Master Thesis
Description
Contact Details
Earliest start: 2024-01-15
Organization: Automatic Control Laboratory
Hosts: Elokda Ezzat
Topics: Information, Computing and Communication Sciences
Details: Open this project...
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. Show details
Keywords
Data-driven control, linear systems, Sum-of-Squares optimization, polynomial programming
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Master Thesis , Theory (IfA) , Computation (IfA) , Applications (IfA)
Description
Goal
Contact Details
Earliest start: 2023-11-29
Organization: Automatic Control Laboratory
Hosts: Bianchi Mattia , Schneeberger Michael
Topics: Mathematical Sciences , Information, Computing and Communication Sciences
Details: Open this project...
Optimal Design of Green Methane Production Sites to Achieve Cost-Effective Long-Term Energy Storage
Future energy systems are foreseen to rely on multiple green fuels. Synthetic methane appears as a promising candidate, as it can be produced from excess carbon dioxide and can be directly deployed in the current energy infrastructures. A smart use of synthetic methane can help decouple energy demand from supply, enabling flexible operation and greater integration of renewable energy sources (RES). However, the intermittency and seasonal behaviour of RES makes the design of green methane production sites challenging. This work aims to simultaneously optimize sizes and operation of a green methane production site with the goal of minimizing the synthetic methane cost of production. To handle uncertainty related to demand, production and price, a stochastic optimization algorithm based on Mixed Integer Linear Programming (MILP) will be implemented. Show details
Keywords
Optimization, design, energy systems, renewable energy, green energy, energy storage, synthetic methane
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Master Thesis
Description
Goal
Contact Details
Earliest start: 2024-01-08
Organization: Urban Energy Systems
Hosts: Koirala Binod
Topics: Engineering and Technology
Details: Open this project...
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. Show details
Keywords
Feedback optimization, robust optimization,power system
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Semester Project , Bachelor Thesis , Master Thesis
Description
Goal
Contact Details
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
Details: Open this project...
Smart mobility: Optimising energy efficiency for autonomous trains
To improve the understanding about the potential of different control methods for automatic train operation in terms of energy efficiency and punctuality, a commercial train simulator shall be extended to allow for real-time control by third-party software. Depending on the interest of the student, the implemented control algorithms may vary from heuristic approaches found in patent databases to novel optimization-based algorithms published in academic literature. Show details
Keywords
Automatic train operation, benchmarking, model predictive control.
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Semester Project , Bachelor Thesis , Master Thesis , Computation (IfA) , Energy (IfA) , Applications (IfA)
Description
Goal
Contact Details
Earliest start: 2023-12-10
Organization: Automatic Control Laboratory
Hosts: Fischer Claudia
Topics: Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...
Best Intervention for Recommender Systems
In this project, we will investigate the impact of a recommender system on the opinions of social network users, through the lens of game theory and using the BIG Hype algorithm as a tool. Show details
Keywords
bilevel optimization, first-order methods, recommender systems, networked systems,
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Master Thesis
Description
Goal
Contact Details
Earliest start: 2024-02-15
Organization: Automatic Control Laboratory
Hosts: De Pasquale Giulia , Belgioioso Giuseppe , Grontas Panagiotis
Topics: Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Details: Open this project...