230 citations · 1k across the 44 of their papers we have counts for
11 papers · 1 filter
Robust targeted exploration for systems with non-stochastic disturbances
Janani Venkatasubramanian, Johannes Köhler, Mark Cannon +1
We propose a novel targeted exploration strategy designed specifically for uncertain linear time-invariant systems with energy-bounded disturbances, i.e., without any assumptions o…
From Data to Predictive Control: A Framework for Stochastic Linear Systems with Output Measurements
Haldun Balim, Andrea Carron, Melanie N. Zeilinger +1
We introduce data to predictive control, D2PC, a framework to facilitate the design of robust and predictive controllers from data. The proposed framework is designed for discrete-…
Predictive control for nonlinear stochastic systems: Closed-loop guarantees with unbounded noise
Johannes Köhler, Melanie N. Zeilinger
We present a stochastic model predictive control framework for nonlinear systems subject to unbounded process noise with closed-loop guarantees. First, we provide a conceptual shri…
Embedded Hierarchical MPC for Autonomous Navigation
Dennis Benders, Johannes Köhler, Thijs Niesten +3
To efficiently deploy robotic systems in society, mobile robots must move autonomously and safely through complex environments. Nonlinear model predictive control (MPC) methods pro…
Model predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation
Pablo Krupa, Johannes Köhler, Antonio Ferramosca +4
This paper provides a comprehensive tutorial on a family of Model Predictive Control (MPC) formulations, known as MPC for tracking, which are characterized by including an artifici…
Adaptive tracking MPC for nonlinear systems via online linear system identification
Tatiana Strelnikova, Johannes Köhler, Julian Berberich
This paper presents an adaptive tracking model predictive control (MPC) scheme to control unknown nonlinear systems based on an adaptively estimated linear model. The model is dete…