![](/files/organization-images/ebf1f7a3-d916-4d67-a31b-32bb644706b9/e153f8e7-bc5c-4361-88e0-b244320b0210.png_200_200.png) Automatic Control LaboratoryOpen OpportunitiesModern buildings today have a complex network of sensors, control systems, and actuators operating together at different levels for satisfactory operation. Some tasks in building control include air quality control, temperature control, and air conditioning. Optimal and efficient operation of building control systems is crucial for occupant comfort, but also for energy efficiency and sustainability metrics. Due to the large energy footprint of buildings, improving operational efficiency through data analytics and control promises a high impact on energy savings and sustainability. In many practical scenarios, efficient control strategies can reduce the CO2 emissions of a building significantly.
- Electrical Engineering, Mechanical Engineering, Systems Theory and Control
- Master Thesis
| 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
| The development of Large Language Models (LLMs), like ChatGPT and GPT-4, has influenced
the field of Natural Language Processing and Artificial Intelligence with their exceptional proficiency in comprehending and generating language, alongside their notable generalization and reasoning abilities. Consequently, recent research efforts have focused on leveraging the capabilities of LLMs to improve recommender systems. Recommender systems significantly influence human behavior by shaping users’ preferences, decision-making processes, and overall engagement with digital content. This project develops on the interpretation of recommender systems (controller) in feedback interaction with the users (system), [3]. By following a similar approach to [2], we will investigate how a careful integration of a LLM with a Model Predictive Control (MPC) framework can enhance recommender systems by ensuring accurate and adaptable recommendations while considering user preferences and constraints.
Understanding the influence of recommender systems over users behaviour and managing it effectively will be enhanced through the MPC framework, which offers a structured and interpretable approach to recommendation optimization. - Automotive Engineering, Computer Communications Networks, Electrical Engineering, Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| 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. - Engineering and Technology
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| Model Predictive Control (MPC) is extensively utilized in industry and academia. However, designing an optimal cost function and constraints for achieving the best closed-loop performance remains an open challenge. This project seeks to bridge this gap by framing the problem as a policy optimization problem and solving it through the application of gradient-based optimization schemes. - Electrical Engineering
- Master Thesis, Semester Project
| In Formula 1 races, the psychology of human drivers plays a significant role in winning. Who is willing to take more risks and act more aggressively to secure victory? In this project, we aim to replicate such edge scenarios in autonomous racing. Until now, autonomous race cars often act conservatively, assuming the opponent's trajectory is fixed and not pushing to the limits of their constraints. Using game-theoretic control, we want to model the strategic, risky decision-making that happens on the race track. Specifically, we will delve into the competitive behaviors emerging from feedback Nash Equilibria (NE) and open-loop NE and explore whether we can encourage agents to be more aggressive with one solution concept over the other. Can we demonstrate the superiority of feedback equilibria theoretically and in simulation? - Intelligent Robotics, Robotics and Mechatronics, Systems Theory and Control, Systems Theory and Control
- ETH Zurich (ETHZ), Master Thesis
| This project aims at automatically learning problem-dependent uncertainty sets by exploiting available data on the uncertain parameters, hence surpassing the limitations of traditional methods such as robust and stochastic optimization approaches that assume the exact knowledge of the support set and of the probability distribution respectively. - Information, Computing and Communication Sciences, Optimisation, Systems Theory and Control
- Master Thesis, Semester Project
| 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. - Dynamical Systems, Optimisation, Systems Theory and Control
- Applications (IfA), Computation (IfA), Master Thesis, Theory (IfA)
| Efficient supply chain management, encompassing the entire process from raw materials to end customer delivery, is essential in today's unpredictable market. This project aims to develop a robust MPC approach to enhance the flexibility of supply chains, defined as the ability to substitute and reroute products efficiently. By ensuring a swift response to sudden demand changes, our MPC strategy will help mitigate disruptions and maintain continuous operations. - Electrical and Electronic Engineering, Information Storage, Retrieval and Management, Information Systems Management, Mathematical Sciences, Mechanical and Industrial Engineering, Systems Theory and Control
- Master Thesis
| 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. - Electrical and Electronic Engineering, Systems Theory and Control
- ETH Zurich (ETHZ), Master Thesis
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