• Campaign-based modeling for degradation evolution in batch processes using a multiway partial least squares approach 

      Wu, Ouyang; Bouaswaig, Ala; Imsland, Lars Struen; Schneider, Stefan; Roth, Matthias; Moreno Leira, Fernando (Journal article; Peer reviewed, 2019)
      In the process industry, various types of degradation occur in processing plants, resulting in significant economic losses. Modeling of degradation is important because it provides quantitative insights for consideration ...
    • Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes 

      Bradford, Eric; Schweidtmann, Artur M.; Zhang, Dongda; Jing, Keju; del Rio-Chanona, Ehecatl Antonio (Journal article; Peer reviewed, 2018)
      Dynamic modeling is an important tool to gain better understanding of complex bioprocesses and to determine optimal operating conditions for process control. Currently, two modeling methodologies have been applied to ...
    • Global Optimisation of Multi-Plant Manganese Alloy Production 

      Digernes, Martin Naterstad; Rudi, Lars; Andersson, Henrik; Stålhane, Magnus; Wasbø, Stein O.; Knudsen, Brage Rugstad (Journal article; Peer reviewed, 2017)
      This paper studies the problem of multi-plant manganese alloy production. The problem consists of finding the optimal furnace feed of ores, fluxes, coke, and slag that yields output products which meet customer specifications, ...
    • Global optimization of multiphase flow networks using spline surrogate models 

      Grimstad, Bjarne André; Foss, Bjarne Anton; Heddle, Richard; Woodman, Malcolm (Journal article; Peer reviewed, 2016)
      A general modelling framework for optimization of multiphase flow networks with discrete decision variables is presented. The framework is expressed with the graph and special attention is given to the convexity properties ...
    • Optimal production and maintenance scheduling for a multiproduct batch plant considering degradation 

      Wu, Ouyang; Dalle, Ave; Harjunkoski, Iiro; Bouaswaig, Ala; Schneider, Stefan; Roth, Matthias; Imsland, Lars Struen (Peer reviewed; Journal article, 2020)
      Performance decay due to asset degradation is an important constraint in industrial production and therefore needs to be actively considered. This paper focuses on short-term scheduling for multiproduct batch processes ...
    • Output feedback stochastic nonlinear model predictive control for batch processes 

      Bradford, Eric; Imsland, Lars Struen (Journal article; Peer reviewed, 2019)
      Batch processes play a vital role in the chemical industry, but are difficult to control due to highly nonlinear behaviour and unsteady state operation. Nonlinear model predictive control (NMPC) is therefore one of the few ...
    • Petroleum production optimization - A static or dynamic problem? 

      Foss, Bjarne Anton; Knudsen, Brage Rugstad; Grimstad, Bjarne André (Journal article; Peer reviewed, 2018)
      This paper considers the upstream oil and gas domain, or more precisely the daily production optimization problem in which production engineers aim to utilize the production systems as efficiently as possible by for instance ...
    • Plant-wide oscillation detection using multivariate empirical mode decomposition 

      Aftab, Muhammad Faisal; Hovd, Morten; Sivalingam, Selvanathan (Journal article; Peer reviewed, 2018)
      Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may ...
    • Plantwide control of an oil production network 

      Jahanshahi, Esmaeil; Krishnamoorthy, Dinesh; Codas Duarte, Andres; Foss, Bjarne Anton; Skogestad, Sigurd (Peer reviewed; Journal article, 2020)
      In this paper, we consider Real-Time Optimization (RTO) and control of an oil production system. We follow a systematic plantwide control procedure. The process consists of two gas-lift oil wells connected to a pipeline-riser ...
    • Reinforcement Learning for Batch Bioprocess Optimization 

      Petsagkourakis, Panagiotis; Sandoval, Ilya Orson; Bradford, Eric; Zhang, Dongda; del Rio-Chanona, Ehecatl Antonio (Peer reviewed; Journal article, 2020)
      Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to their unsteady-state operation modes and ...
    • Run-To-Run control of the Czochralski process 

      Rahmanpour, Parsa; Sælid, Steinar; Hovd, Morten (Journal article; Peer reviewed, 2017)
      Commercially, the Czochralski process plays a key role in production of monocrystalline silicon for semiconductor and solar cell applications. However, it is a highly complex batch process which requires careful control ...
    • Stochastic data-driven model predictive control using gaussian processes 

      Bradford, Eric; Imsland, Lars Struen; Zhang, Dongda; Chanona del Rio, Ehecatl Antonio (Peer reviewed; Journal article, 2020)
      Nonlinear model predictive control (NMPC) is one of the few control methods that can handle multivariable nonlinear control systems with constraints. Gaussian processes (GPs) present a powerful tool to identify the required ...