no code implementations • 11 Oct 2021 • M. Hotvedt, B. Grimstad, D. Ljungquist, L. Imsland
The experiments are conducted with synthetic data where properties of the underlying data generating process are known and controlled.
no code implementations • 14 Aug 2021 • E. Bradford, L. Imsland, M. Reble, E. A. del Rio-Chanona
Nonlinear model predictive control (NMPC) is an efficient approach for the control of nonlinear multivariable dynamic systems with constraints, which however requires an accurate plant model.
no code implementations • 9 Mar 2021 • E. Bradford, L. Imsland
In this paper we introduce a new algorithm to explicitly consider time-invariant stochastic uncertainties in optimal control problems.
no code implementations • 5 Aug 2019 • E. Bradford, L. Imsland, D. Zhang, E. A. del Rio-Chanona
Nonlinear model predictive control (NMPC) is one of the few control methods that can handle multivariable nonlinear controlsystems with constraints.