The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
This paper proposes a disturbance-based control parametrization under the Model Predictive Control framework for constrained linear discrete time systems with bounded additive dis...
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true d...
A neural model-based predictive control scheme is proposed for dealing with steady-state offsets found in standard MPC schemes. This structure is based on a constrained local inst...
This paper deals with hierarchical model predictive control (MPC) of distributed systems. A threelevel hierarchical approach is proposed, consisting of a high level MPC controller,...
Jan Dimon Bendtsen, Klaus Trangbaek, Jakob Stoustr...