4 papers
Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems
Junya Ikemoto, Satoshi Maruyama, Kazumune Hashimoto
This paper proposes a deep reinforcement learning (DRL)-based event-triggered controller design for networked artificial pancreas (AP) systems. Although existing DRL-based AP contr…
Robust Neural Policy Distillation of Long-Horizon FCS-MPC for Flying-Capacitor Three-Level Boost Converters
Jinjian Sheng, Kazumune Hashimoto, Shuang Zhao +1
Long-horizon finite-control-set model predictive control (FCS-MPC) can improve transient regulation and flying-capacitor balancing in flying-capacitor three-level boost converters…
Data-Driven Synthesis of Probabilistic Controlled Invariant Sets for Linear MDPs
Kazumune Hashimoto, Shunki Kimura, Kazunobu Serizawa +3
We study data-driven computation of probabilistic controlled invariant sets (PCIS) for safety-critical reinforcement learning under unknown dynamics. Assuming a linear MDP model, w…
STLCCP: Efficient Convex Optimization-based Framework for Signal Temporal Logic Specifications
Yoshinari Takayama, Kazumune Hashimoto, Toshiyuki Ohtsuka
Signal temporal logic (STL) is a powerful formalism for specifying various temporal properties in dynamical systems. However, existing methods, such as mixed-integer programming an…