Browsing NTNU Open by Author "Seel, Katrine"

Now showing items 1-12 of 12

    • Autonomous navigation of an ROV using tightly coupled integration of inertial and pseudo-range measurements 

      Seel, Katrine (Master thesis, 2017)
      Underwater navigation is one of the key issues that need to be addressed in order to make operation of underwater vehicles more autonomous. This thesis investigates two different methods for integration of inertial and ...

    • Convex Neural Network-Based Cost Modifications for Learning Model Predictive Control 

      Seel, Katrine; Kordabad, Arash Bahari; Gros, Sebastien; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2022)
      Developing model predictive control (MPC) schemes can be challenging for systems where an accurate model is not available, or too costly to develop. With the increasing availability of data and tools to treat them, ...

    • Learning for Model Predictive Control 

      Seel, Katrine (Doctoral theses at NTNU;2023:261, Doctoral thesis, 2023)
      This thesis focuses on learning-based control, with an emphasis on control designs for which we can analyze stability and robustness properties. The topic is motivated by the lack of available controllers for complex, ...

    • Learning-based Robust Model Predictive Control for Sector-bounded Lur'e Systems 

      Seel, Katrine; Haring, Mark A. M.; Grøtli, Esten Ingar; Pettersen, Kristin Ytterstad; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2021)
      For dynamical systems with uncertainty, robust controllers can be designed by assuming that the uncertainty is bounded. The less we know about the uncertainty in the system, the more conservative the bound must be, which ...

    • A Levenberg-Marquardt Algorithm for Sparse Identification of Dynamical Systems 

      Haring, Mark A. M.; Grøtli, Esten Ingar; Riemer-Sørensen, Signe; Seel, Katrine; Hanssen, Kristian Gaustad (Peer reviewed; Journal article, 2022)
      Low complexity of a system model is essential for its use in real-time applications. However, sparse identification methods commonly have stringent requirements that exclude them from being applied in an industrial setting. ...

    • Neural Network-based Model Predictive Control with Input-to-State Stability 

      Seel, Katrine; Grøtli, Esten Ingar; Moe, Signe; Gravdahl, Jan Tommy; Pettersen, Kristin Ytterstad (Peer reviewed; Journal article, 2021)
      Learning-based controllers, and especially learning-based model predictive controllers, have been used for a number of different applications with great success. In spite of good performance, a lot of these cases lack ...

    • Robotic Bin-Picking under Geometric End-Effector Constraints: Bin Placement and Grasp Selection 

      Gravdahl, Irja; Seel, Katrine; Grøtli, Esten Ingar (Chapter, 2019)
      In this paper we demonstrate how path reachability can be taken into account when selecting among predetermined grasps in a bin-picking application, where grasps are supplied independently of the robot at hand. We do this ...

    • Robust Reasoning for Autonomous Cyber-Physical Systems in Dynamic Environments 

      Håkansson, Anne; Saad, Aya; Sadanandan Anand, Akhil; Gjærum, Vilde Benoni; Robinson, Haakon; Seel, Katrine (Peer reviewed; Journal article, 2021)
      Autonomous cyber-physical systems, CPS, in dynamic environments must work impeccably. The cyber-physical systems must handle tasks consistently and trustworthily, i.e., with a robust behavior. Robust systems, in general, ...

    • Robustness and Stability of Long Short-Term Memory Recurrent Neural Networks 

      Peci, Edmond (Master thesis, 2021)
      Denne masteroppgaven har som mål å studere robusthet og stabilitet i lys av den populære rekurrente nevrale nettverkstypen 'lang kortidsminne' (long short-term memory) i møte med perturbert inngangsdata and pertubasjoner ...

    • Safe Learning for Control using Control Lyapunov Functions and Control Barrier Functions: A Review 

      Sadanandan Anand, Akhil; Seel, Katrine; Gjærum, Vilde Benoni; Håkansson, Anne; Robinson, Haakon; Saad, Aya (Peer reviewed; Journal article, 2021)
      Real-world autonomous systems are often controlled using conventional model-based control methods. But if accurate models of a system are not available, these methods may be unsuitable. For many safety-critical systems, ...

    • Uncertainty estimation in autoregressive exogenous networks and nonlinear autoregressive exogenous neural networks 

      Eilertsen, Ingeborg Kristine (Master thesis, 2021)
      Autoregressive eksogene (ARX) nettverk og ikke-lineære autoregressive eksogene (NARX) nevrale nettverk er avhengige av et mål på usikkerhet hvis de skal brukes til sikkerhets kritiske oppgaver, der feil valg i det verste ...

    • Variance-Based Exploration for Learning Model Predictive Control 

      Seel, Katrine; Bemporad, Alberto; Gros, Sebastien Nicolas; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2023)
      The combination of model predictive control (MPC) and learning methods has been gaining increasing attention as a tool to control systems that may be difficult to model. Using MPC as a function approximator in reinforcement ...