136 citations · 169 across the 27 of their papers we have counts for
28 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…
Long-term Safe Reinforcement Learning with Binary Feedback
Akifumi Wachi, Wataru Hashimoto, Kazumune Hashimoto
Safety is an indispensable requirement for applying reinforcement learning (RL) to real problems. Although there has been a surge of safe RL algorithms proposed in recent years, mo…
Synthesis of Event-triggered Controllers for SIRS Epidemic Models
Lichen Ding, Kazumune Hashimoto, Shigemasa Takai
In this paper, we investigate the problem of mitigating epidemics by applying an event-triggered control strategy. We consider a susceptible-infected-removed-susceptible (SIRS) mod…
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms
Akifumi Wachi, Wataru Hashimoto, Xun Shen +1
Safe exploration is essential for the practical use of reinforcement learning (RL) in many real-world scenarios. In this paper, we present a generalized safe exploration (GSE) prob…
Bayesian Meta-Learning on Control Barrier Functions with Data from On-Board Sensors
Wataru Hashimoto, Kazumune Hashimoto, Akifumi Wachi +3
In this paper, we consider a way to safely navigate the robots in unknown environments using measurement data from sensory devices. The control barrier function (CBF) is one of the…
Signal Temporal Logic Meets Convex-Concave Programming: A Structure-Exploiting SQP Algorithm for STL Specifications
Yoshinari Takayama, Kazumune Hashimoto, Toshiyuki Ohtsuka
This study considers the control problem with signal temporal logic (STL) specifications. Prior works have adopted smoothing techniques to address this problem within a feasible ti…
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…
Neural Controller Synthesis for Signal Temporal Logic Specifications Using Encoder-Decoder Structured Networks
Wataru Hashimoto, Kazumune Hashimoto, Masako Kishida +1
In this paper, we propose a control synthesis method for signal temporal logic (STL) specifications with neural networks (NNs). Most of the previous works consider training a contr…
A Lifting Approach to Learning-Based Self-Triggered Control with Gaussian Processes
Wang Zhijun, Kazumune Hashimoto, Wataru Hashimoto +1
This paper investigates the design of self-triggered control for networked control systems (NCS), where the dynamics of the plant is unknown apriori. To deal with the nature of the…
Learning-based Event-triggered MPC with Gaussian processes under terminal constraints
Yuga Onoue, Kazumune Hashimoto, Akifumi Wachi
Event-triggered control strategy is capable of significantly reducing the number of control task executions without sacrificing control performance. In this paper, we propose a nov…
STL2vec: Signal Temporal Logic Embeddings for Control Synthesis With Recurrent Neural Networks
Wataru Hashimoto, Kazumune Hashimoto, Shigemasa Takai
In this paper, a method for learning a recurrent neural network (RNN) controller that maximizes the robustness of signal temporal logic (STL) specifications is presented. In contra…
Collaborative rover-copter path planning and exploration with temporal logic specifications based on Bayesian update under uncertain environments
Kazumune Hashimoto, Natsuko Tsumagari, Toshimitsu Ushio
This paper investigates a collaborative rover-copter path planning and exploration with temporal logic specifications under uncertain environments. The objective of the rover is to…
Event-Triggered Control for Mitigating SIS Spreading Processes
Kazumune Hashimoto, Yuga Onoue, Masaki Ogura +1
In this paper, we investigate the problem of designing event-triggered controllers for containing epidemic processes in complex networks. We focus on a deterministic susceptible-in…
Safe and active parameter exploration for event-triggered control
Kazumune Hashimoto
This paper presents a framework of learning parameter space for event-triggered control. In particular, our goal is to find a set of parameters for the event-triggered condition, s…
Learning-based Symbolic Abstractions for Nonlinear Control Systems
Kazumune Hashimoto, Adnane Saoud, Masako Kishida +2
Symbolic models or abstractions are known to be powerful tools for the control design of cyber-physical systems (CPSs) with logic specifications. In this paper, we investigate a no…
Control of Timed Discrete Event Systems with Ticked Linear Temporal Logic Constraints
Takuma Kinugawa, Kazumune Hashimoto, Toshimitsu Ushio
This paper presents a novel method of synthesizing a fragment of a timed discrete event system(TDES),introducing a novel linear temporal logic(LTL), called ticked LTL. The tick…
Learning self-triggered controllers with Gaussian processes
Kazumune Hashimoto, Yuichi Yoshimura, Toshimitsu Ushio
This paper investigates the design of self-triggered controllers for networked control systems (NCSs), where the dynamics of the plant is \textit{unknown} apriori. To deal with the…
A symbolic approach to the self-triggered design for networked control systems
Kazumune Hashimoto, Adnane Saoud, Masako Kishida +2
In this paper, we investigate novel self-triggered controllers for nonlinear control systems with reachability and safety specifications. To synthesize the self-triggered controlle…
Synthesizing communication plans for reachability and safety specifications
Kazumune Hashimoto, Dimos V. Dimarogonas
We propose control and communication strategies for nonlinear networked control systems subject to state and input constraints. The objective is to steer the state of the system to…
Distributed L1-state-and-fault estimation for Multi-agent systems
Kazumune Hashimoto, Michelle Chong, Dimos V. Dimarogonas
In this paper, we propose a distributed state-and-fault estimation scheme for multi-agent systems. The proposed estimator is based on an -norm optimization problem, which i…
Energy-aware networked control systems under temporal logic specifications
Kazumune Hashimoto, Shuichi Adachi, Dimos V. Dimarogonas
In recent years, event and self-triggered control have been proposed as energy-aware control strategies to expand the life-time of battery powered devices in Networked Control Syst…
Aperiodic Sampled-Data Control via Explicit Transmission Mapping: A Set Invariance Approach
Kazumune Hashimoto, Dimos V. Dimarogonas, Shuichi Adachi
Event-triggered and self-triggered control have been proposed in recent years as promising control strategies to reduce communication resources in Networked Control Systems (NCSs).…