10 citations · 23 across the 4 of their papers we have counts for
6 papers · 1 filter
Towards a constructive framework for control theory
Pavel Osinenko
This work presents a framework for control theory based on constructive analysis to account for discrepancy between mathematical results and their implementation in a computer, als…
Stacked adaptive dynamic programming with unknown system model
Pavel Osinenko, Thomas Göhrt, Grigory Devadze +1
Adaptive dynamic programming is a collective term for a variety of approaches to infinite-horizon optimal control. Common to all approaches is approximation of the infinite-horizon…
Nonsmooth stabilization and its computational aspects
Pavel Osinenko, Patrick Schmidt, Stefan Streif
This work has the goal of briefly surveying some key stabilization techniques for general nonlinear systems, for which, as it is well known, a smooth control Lyapunov function may…
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 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…