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eess.SY2026
Safe and Near-Optimal Control with Online Dynamics Learning
Manish Prajapat, Johannes Köhler, Melanie N. Zeilinger +1
Achieving both optimality and safety under unknown system dynamics is a central challenge in real-world deployment of agents. To address this, we introduce a notion of maximum safe…
eess.SY2025
Stochastic Model Predictive Control for Sub-Gaussian Noise
Yunke Ao, Johannes Köhler, Manish Prajapat +4
We propose a stochastic Model Predictive Control (MPC) framework that ensures closed-loop chance constraint satisfaction for linear systems with general sub-Gaussian process and me…
eess.SY2025
Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
Manish Prajapat, Johannes Köhler, Amon Lahr +2
Gaussian Process (GP) regression is shown to be effective for learning unknown dynamics, enabling efficient and safety-aware control strategies across diverse applications. However…