50 citations · 249 across the 50 of their papers we have counts for
13 papers · 1 filter
A Linear Parameter-Varying Approach to Data Predictive Control
Chris Verhoek, Julian Berberich, Sofie Haesaert +2
By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-fee…
Energy-Constrained Active Exploration Under Incremental-Resolution Symbolic Perception
Disha Kamale, Sofie Haesaert, Cristian-Ioan Vasile
In this work, we consider the problem of autonomous exploration in search of targets while respecting a fixed energy budget. The robot is equipped with an incremental-resolution sy…
Verifying the Unknown: Correct-by-Design Control Synthesis for Networks of Stochastic Uncertain Systems
Oliver Schön, Birgit van Huijgevoort, Sofie Haesaert +1
In this paper, we present an approach for designing correct-by-design controllers for cyber-physical systems composed of multiple dynamically interconnected uncertain systems. We c…
Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous Driving
Lin-Chi Wu, Zengjie Zhang, Sofie Haesaert +2
Reinforcement learning (RL) is an effective approach to motion planning in autonomous driving, where an optimal driving policy can be automatically learned using the interaction da…
Stochastic Model Predictive Control with Dynamic Chance Constraints
Maico Hendrikus Wilhelmus Engelaar, Sofie Haesaert, Mircea Lazar
This work introduces a stochastic model predictive control scheme for dynamic chance constraints. We consider linear discrete-time systems affected by unbounded additive stochastic…
Bayesian Formal Synthesis of Unknown Systems via Robust Simulation Relations
Oliver Schön, Birgit van Huijgevoort, Sofie Haesaert +1
This paper addresses the problem of data-driven computation of controllers that are correct by design for safety-critical systems and can provably satisfy (complex) functional requ…
Abstracting Linear Stochastic Systems via Knowledge Filtering
Maico Hendrikus Wilhelmus Engelaar, Licio Romao, Yulong Gao +3
In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques. This…
Direct data-driven control with signal temporal logic specifications
Birgit C. van Huijgevoort, Chris Verhoek, Roland Tóth +1
Most control synthesis methods under temporal logic properties require a model of the system, however, identifying such a model can be a challenging task. In this work, we develop…
Automated Formation Control Synthesis from Temporal Logic Specifications
Shuhao Qi, Zengjie Zhang, Sofie Haesaert +1
In many practical scenarios, multi-robot systems are envisioned to support humans in executing complicated tasks within structured environments, such as search-and-rescue tasks. We…
Modularized Control Synthesis for Complex Signal Temporal Logic Specifications
Zengjie Zhang, Sofie Haesaert
The control synthesis of a dynamic system subject to a signal temporal logic (STL) specification is commonly formulated as a mixed-integer linear/convex programming (MILP/MICP) pro…
Direct data-driven state-feedback control of general nonlinear systems
Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert +1
Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL)…
Data-driven Dissipativity Analysis of Linear Parameter-Varying Systems
Chris Verhoek, Julian Berberich, Sofie Haesaert +2
We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of construc…
SySCoRe: Synthesis via Stochastic Coupling Relations
Birgit van Huijgevoort, Oliver Schön, Sadegh Soudjani +1
We present SySCoRe, a MATLAB toolbox that synthesizes controllers for stochastic continuous-state systems to satisfy temporal logic specifications. Starting from a system descripti…