9 citations · 17 across the 8 of their papers we have counts for
9 papers
Predictive Control with Learning-Based Terminal Costs Using Approximate Value Iteration
Francisco Moreno-Mora, Lukas Beckenbach, Stefan Streif
Stability under model predictive control (MPC) schemes is frequently ensured by terminal ingredients. Employing a (control) Lyapunov function as the terminal cost constitutes a com…
A stabilizing reinforcement learning approach for sampled systems with partially unknown models
Lukas Beckenbach, Pavel Osinenko, Stefan Streif
Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-…
Approximate infinite-horizon predictive control
Lukas Beckenbach, Stefan Streif
Predictive control is frequently used for control problems involving constraints. Being an optimization based technique utilizing a user specified so-called stage cost, performance…
Performance bounds of adaptive MPC with bounded parameter uncertainties
Francisco Moreno-Mora, Lukas Beckenbach, Stefan Streif
Model predictive control is a control approach that minimizes a stage cost over a predicted system trajectory based on a model of the system and is capable of handling state and in…
On performance bound estimation in NMPC with time-varying terminal cost
Lukas Beckenbach, Stefan Streif
Model predictive control (MPC) schemes are commonly designed with fixed, i.e., time-invariant, horizon length and cost functions. If no stabilizing terminal ingredients are used, s…
A reinforcement learning method with closed-loop stability guarantee
Pavel Osinenko, Lukas Beckenbach, Thomas Göhrt +1
Reinforcement learning (RL) in the context of control systems offers wide possibilities of controller adaptation. Given an infinite-horizon cost function, the so-called critic of R…
Model Predictive Control of a Food Production Unit: A Case Study for Lettuce Production
Murali Padmanabha, Lukas Beckenbach, Stefan Streif
Plant factories with artificial light are widely researched for food production in a controlled environment. For such control tasks, models of the energy and resource exchange in t…
Model predictive control with stage cost shaping inspired by reinforcement learning
Lukas Beckenbach, Pavel Osinenko, Stefan Streif
This work presents a suboptimality study of a particular model predictive control with a stage cost shaping based on the ideas of reinforcement learning. The focus of the suboptima…
Practical sample-and-hold stabilization of nonlinear systems under approximate optimizers
Pavel Osinenko, Lukas Beckenbach, Stefan Streif
It is a known fact that not all controllable systems can be asymptotically stabilized by a continuous static feedback. Several approaches have been developed throughout the last de…