6 papers · 1 filter
The Separation Principle and the Dual-Certainty Equivalence Gap in Model Predictive Control
Tren Baltussen, Nathan P. Lawrence, Alexander Katriniok +2
Dual control addresses the trade-off between exploitation and exploration, where control inputs both regulate the system and generate informative data for estimation and identifica…
Dual MPC for Active Learning of Nonparametric Uncertainties
Tren Baltussen, Maurice Heemels, Alexander Katriniok
This manuscript presents a dual model predictive controller (MPC) that balances the two objectives of dual control, namely, system identification and control. In particular, we pro…
Data-Driven Stabilization Using Prior Knowledge on Stabilizability and Controllability
Amir Shakouri, Henk J. van Waarde, Tren M. J. T. Baltussen +1
In this work, we study data-driven stabilization of linear time-invariant systems using prior knowledge of system-theoretic properties, specifically stabilizability and controllabi…
Value Function Approximation for Nonlinear MPC: Learning a Terminal Cost Function with a Descent Property
T. M. J. T. Baltussen, C. A. Orrico, A. Katriniok +2
We present a novel method to synthesize a terminal cost function for a nonlinear model predictive controller (MPC) through value function approximation using supervised learning. E…
A Contingency Model Predictive Control Framework for Safe Learning
Merlijne Geurts, Tren Baltussen, Alexander Katriniok +1
This research introduces a multi-horizon contingency model predictive control (CMPC) framework in which classes of robust MPC (RMPC) algorithms are combined with classes of learnin…
Online Learning of Interaction Dynamics with Dual Model Predictive Control for Multi-Agent Systems Using Gaussian Processes
T. M. J. T. Baltussen, A. Katriniok, E. Lefeber +2
The control of a single agent in complex and uncertain multi-agent environments requires careful consideration of the interactions between the agents. In this context, this paper p…