4 papers · 1 filter
Risk-sensitive Actor-free Policy via Convex Optimization
Ruoqi Zhang, Jens Sjölund
Traditional reinforcement learning methods optimize agents without considering safety, potentially resulting in unintended consequences. In this paper, we propose an optimal actor-…
Aiding reinforcement learning for set point control
Ruoqi Zhang, Per Mattsson, Torbjörn Wigren
While reinforcement learning has made great improvements, state-of-the-art algorithms can still struggle with seemingly simple set-point feedback control problems. One reason for t…
Robust nonlinear set-point control with reinforcement learning
Ruoqi Zhang, Per Mattsson, Torbjörn Wigren
There has recently been an increased interest in reinforcement learning for nonlinear control problems. However standard reinforcement learning algorithms can often struggle even o…
Observer-Feedback-Feedforward Controller Structures in Reinforcement Learning
Ruoqi Zhang, Per Mattson, Torbjörn Wigren
The paper proposes the use of structured neural networks for reinforcement learning based nonlinear adaptive control. The focus is on partially observable systems, with separate ne…