1 citations · 1 across the 7 of their papers we have counts for
8 papers
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…
Verification and Synthesis of Discrete-Time Control Barrier Functions
Erfan Shakhesi, W. P. M. H. Heemels, Alexander Katriniok
Discrete-time Control Barrier Functions (DTCBFs) have recently attracted interest for guaranteeing safety and synthesizing safe controllers for discrete-time dynamical systems. Thi…
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…
Counterexample-Guided Synthesis of Robust Discrete-Time Control Barrier Functions
Erfan Shakhesi, Alexander Katriniok, W. P. M. H. Heemels
Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, sinc…
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…
Synthesis of Discrete-time Control Barrier Functions for Polynomial Systems Based on Sum-of-Squares Programming
Erfan Shakhesi, W. P. M. H. Heemels, Alexander Katriniok
Discrete-time Control Barrier Functions (DTCBFs) are commonly utilized in the literature as a powerful tool for synthesizing control policies that guarantee safety of discrete-time…
Optimization-based Verification of Discrete-time Control Barrier Functions: A Branch-and-Bound Approach
Erfan Shakhesi, W. P. M. H. Heemels, Alexander Katriniok
Discrete-time Control Barrier Functions (DTCBFs) form a powerful control theoretic tool to guarantee safety and synthesize safe controllers for discrete-time dynamical systems. In…
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…