Automatic Control Laboratory

Open Opportunities

Optimizing Quadrotor Trajectories for Robust Vision-based Flight ETH Zurich Automatic Control Laboratory In this thesis, you will develop a method to generate trajectories that reach a desired target location while guaranteeing a good position estimate throughout the flight considering the available visual features in the surroundings of the robot. Systems Theory and Control Master Thesis

Design of a Dynamic Omni-Directional Kick Engine for NAO Bipedal Robots in RoboCup ETH Zurich Automatic Control Laboratory This project aims to design a reliable omni-directional kick engine for the NAO bipedal robot, based on data-driven nonlinear optimal control. The new kick engine will be integrated into the current control and behavior framework of the NomadZ RoboCup Team at ETH Zürich (https://robocup.ethz.ch). Engineering and Technology Master Thesis, Semester Project

Path Generation and Optimization for Stress Aligned 5-axis FDM Printing of Anisotropic Liquid-Cristal-Polymers ETH Zurich Automatic Control Laboratory We optimize the material orientation in a 2.5 to 5-axis FDM 3D printing process using anisotropic materials to improve the manufactured component mechanical properties. Engineering and Technology Bachelor Thesis, Master Thesis, Semester Project

Identification and control of a fuel cell system for peak shaving BEV demand ETH Zurich Automatic Control Laboratory In this project we aim at perform a system identification of the fuel cell at ESI platform (PSI) and use the derived model in the context of stochastic MPC for peak shaving electric vehicles demand. Engineering and Technology Master Thesis, Semester Project

Fast calculation of data-enabled predictive control solutions ETH Zurich Automatic Control Laboratory We focus on a novel data-enabled predictive control (DeePC) algorithm, which relies only on input/output data to learn the behavior of the unknown system and perform safe and optimal control to drive the system along a desired trajectory using real-time feedback. The DeePC algorithm relies on solving an on-line convex optimization problem to obtain the optimal control sequence, which is sometimes computationally expensive for micro-controllers. In this project, we will explore different methods to reduce the computational burden and achieve fast calculation for the optimal control sequence. Engineering and Technology Semester Project

Topics in Distributionally Robust Optimization ETH Zurich Automatic Control Laboratory Many real-world decision problems arising in engineering and management have uncertain parameters, whose probability distributions is unknown. This motivates us to formulate decision problems as a game: the decision-maker first chooses a decision; then, some fictitious adversarial player (e.g., ``nature'') selects a probability distribution from a prescribed ambiguity set with the goal to inflict maximum harm. Under this model, the decision-maker prepares for the worst-case distribution in the ambiguity set. In recent years, there has been significant interest in ambiguity sets including all probability distributions within a given Wasserstein distance from a benchmark distribution (e.g., the empirical distribution defined by observed samples), mainly because of their computational tractability and of their attractive statistical guarantees; see~\cite{peyman}. References: [1] Peyman Mohajerin Esfahani and Daniel Kuhn. Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations. Mathematical Programming, 171(1):115–166, 2018. Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences Master Thesis, Semester Project

Adaptive Control of Networked Dynamical Systems ETH Zurich Automatic Control Laboratory The overarching goal of this SA project is to apply a recently developed distributed adaptive robust MPC algorithm to a relevant engineering distributed system featuring dynamic coupling among the subsystems, e.g. microgrids. Control Engineering, Process Control and Simulation, Systems Theory and Control Semester Project

Data driven techniques to model thermal and electrical demand of energy hub ETH Zurich Automatic Control Laboratory Optimization of a multi-energy system rely on future demand profiles for the energy and heating demand of the hubs. The goal of this project is to evaluate data driven approaches to model hub demand patterns as opposed to first principal models that can be difficult or costly to develop/maintain. Building Science and Techniques, Electrical Engineering, Mechanical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic Applications (IfA), Computation (IfA), Energy (IfA), Master Thesis, Semester Project

SLAM for Robotic State Estimation ETH Zurich Automatic Control Laboratory SnookerBot is a snooker playing robot platform at IfA. This project builds upon it by adding a mobile platform as a base for the current system to move around the table. The student, then needs to explore the state-of-the-art SLAM algorithms to implement one on the testbed for state estimation. Computer Vision, Image Processing, Intelligent Robotics, Mechanical Engineering, Programming Languages, Systems Theory and Control Master Thesis

Process Monitoring and Estimation for Selective Laser Melting ETH Zurich Automatic Control Laboratory The quality of Selective Laser Melting (SLM) 3D printed parts depends on their thermal history. We aim to estimate this history for process monitoring and control purposes using a combination of model-based and data-driven estimation and machine learning techniques. Engineering and Technology Master Thesis, Semester Project