RectorateOpen OpportunitiesWe consider a novel model for dynamical systems that gave rise to new and highly performant data-driven control methods recently. Even though these methods are typically limited to linear time-invariant systems, recent work has proposed adapting the model online using tools for subspace tracking. This project aims to demonstrate the method’s effectiveness through case studies, highlighting its potential for superior performance in practical applications. - Engineering and Technology
- Semester Project
| The objective of this project is the design and analysis of recommender systems as optimization algorithms representing a robust feedback controller. We aim to design recommender system algorithms that identify influential users using observable data from users (for example: clicks/ time spent on a page/ likes etc.) in a social network and provide recommendations accordingly. - Engineering and Technology, Mathematical Sciences
- Master Thesis, Semester Project
| 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. - Systems Theory and Control
- Master Thesis, Semester Project
| In this project, we study Iterative Learning Control (ILC), which is a repetitive controller that uses feedback to improve performance over iterations. We formulate the ILC problem as an optimization problem with the physical system as a constraint. Specifically, we seek to apply ILC algorithms to practical applications in robotics and manufacturing.
Some potential applications include 3D printing of polymers or metals; Learning-based drone flight path optimization; Closed-loop control of planar and non-planar extrusion-based additive manufacturing; Robot-based machining processes; and Precision motion control.
The project will extend existing methods and specialize them for the application domain to provide a full demonstration of the potential of the controllers in various realistic scenarios. The specific application will be decided on the student's background and interests. The output of the project is the development and demonstration of learning controllers for various tasks. This project is part of the Research Explanation and Application Lab (REAL) initiative; a special focus will be put on research explanation and presentation skills; students working on the project will receive dedicated training. - Electrical and Electronic Engineering, Manufacturing Engineering, Mechanical and Industrial Engineering
- Applications (IfA), Master Thesis, Semester Project
| This project deals with the design and analysis of fertilization control strategies. The goal is to minimize over-fertilization while ensuring sufficient nutrification of the crops. Therefore, it is required to study literature on dynamical models of nitrogen in soil, extract a suitable model and implement it in a simulation. Then, design a suitable, formally verifyable control algorithm and analyse the potential of optimal fertilization strategies in agriculture. The control tools may range from dynamic programming (with a-priori guarantees) to reinforcement learning (with statistical a-posteriori guarantees) and beyond. - Systems Theory and Control, Systems Theory and Control
- Master Thesis
| Karma games belong to the class of Dynamic Population Games (DPG). They are formulated as repeated auction-like games for a population of self-interested agents and ensure fair and efficient resource allocation in such a population.
Motivated by its application for priority distribution among Connected and Automated Vehicles (CAVs), we are interested in designing a karma game for proportional resource allocations in populations with variable clusters.
The research question is described with an example of CAV traffic. Assume CAVs are assigned into clusters based on safety criteria and jointly take actions to avoid collisions. Every time a new collision is detected, a new cluster is formed, lasting until the threat is solved. The number of CAVs within a cluster and the cluster duration are variable. CAVs compete to win priority values inside clusters. How can we design a karma game to distribute priority fairly and efficiently among all the CAVs?
The applications of such a game are not limited to CAVs; they can be further extended for other applications of proportional resource allocations, such as shared servers.
- Control Engineering, Electrical Engineering
- Master Thesis, Semester Project
| 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. - Electrical Engineering
- Master Thesis, Semester Project
| 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 learning-based algorithms 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. - Intelligent Robotics, Systems Theory and Control, Systems Theory and Control
- Master Thesis
| Computational tools for finding Lyapunov functions are the core of many control design and verification tasks, such as choosing terminal ingredients in MPC, or formally guaranteeing stability for complex nonlinear systems. We have recently proposed a new method for finding Lyapunov functions, based on Bregman divergences. The goal of this project is to test, validate and further develop this method, via numerical experiments, and application to toy examples as well as to challenging problems in power systems. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Markov Jump Linear Systems (MJLS) are dynamical systems that switch randomly among different dynamics, according to a Markov chain. One example is provided by energy microgrids, which operate in islanded or grid-tied modes, depending on some stochastic events. The goal of this project is to develop data-driven controllers for this type of systems, that can guarantee stability despite the switching between different operating conditions. - Engineering and Technology
- Master Thesis, Semester Project
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