• Compressor Surge Control Using Lyapunov Neural Networks 

      Neverlien, Åse; Moe, Signe; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      In this paper surge control in a compression system using a close-coupled valve (CCV) is proposed. The control design is based on Lyapunov control theory in combination with neural networks (NNs) and focuses on minimization ...
    • Deep Reinforcement Learning Attitude Control of Fixed Wing UAVs Using Proximal Policy Optimization 

      Bøhn, Eivind Eigil; Coates, Erlend Magnus Lervik; Moe, Signe; Johansen, Tor Arne (Chapter; Peer reviewed, 2019)
      Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types ...
    • Linear Antisymmetric Recurrent Neural Networks 

      Moe, Signe; Remonato, Filippo; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer. This makes them highly suitable for ...
    • 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 ...
    • Path Following, Obstacle Detection and Obstacle Avoidance for Thrusted Underwater Snake Robots 

      Kelasidi, Eleni; Moe, Signe; Pettersen, Kristin Ytterstad; Kohl, Anna M; Liljebäck, Pål; Gravdahl, Jan Tommy (Journal article; Peer reviewed, 2019)
      The use of unmanned underwater vehicles is steadily increasing for a variety of applications such as mapping, monitoring, inspection and intervention within several research fields and industries, e.g., oceanography, marine ...
    • Set-based collision avoidance applications to robotic systems 

      Moe, Signe; Pettersen, Kristin Ytterstad; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      A robotic system can consist of a single or multiple agents with a fixed or mobile base, with full or under-actuation, and possibly redundancy. Collision avoidance is a crucial task for any robotic system and is necessary ...
    • Stable and robust neural network controllers 

      Sterud, Camilla; Moe, Signe; Gravdahl, Jan Tommy (Chapter, 2021)
      Neural networks are expressive function approimators that can be employed for state estimation in control problems. However, control systems with machine learning in the loop often lack stability proofs and performance ...
    • Wire-arc additive manufacturing of structures with overhang: Experimental results depositing material onto fixed substrate 

      Evjemo, Linn Danielsen; Langelandsvik, Geir; Moe, Signe; Danielsen, Morten Høgseth; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2022)
      As additive manufacturing (AM) technology grows both more advanced and more available, the challenges and limitations are also made more evident. Most existing solutions for AM build structures layer by layer using strictly ...