Machine Learning for Cyber-Physical Systems

  • Supervised learning for data-driven modeling: identification of plant models
  • Unsupervised learning for data-pattern recognition: modeling time-varying control specifications
  • Deep reinforcement learning for scalable and safe control of large-scale systems
  • Application: data-driven modeling and control of smart logistic automation systems using networks of AGVs

Discrete-Event Systems

  • Supervisor localization: top-down approach for distributed control
  • Distributed control with communication delays
  • Distributed control under partial observation
  • Relative observability: partially-observed supervisory control
  • Scalable supervisory control
  • Application to warehouse automation served by multiple robots

Networked Multi-Agent Systems

  • Surplus averaging algorithms: solving average consensus over general strongly connected digraphs
  • Eigenstructure assignment: top-down approach for formation control
  • Distributed optimization based on surplus averaging algorithms
  • Distributed internal model principle: general theory of cooperative control
  • Complex networks: algebraic connectivity and controllability
  • Application to formation control of multi-UAV system

Research Grants

  • "Fast and Reliable Risk-Aware Large-Scale Multi-Agent Motion Planning", Hayashi-ULVAC MISTI Seed Fund, 2023-2025
  • "Safe, Privacy-Aware, and Resource-Efficient Control Framework for Cyber-Physical Systems", JSPS Grant-in-Aid for International Research Collaboration (B), 2022-2025
  • "A Mathematical Framework for Synergizing Control Theory and Statistical Learning", JSPS Grant-in-Aid for Scientific Research (A), 2021-2025
  • “A Mathematical Modeling and Control Framework of Cybersecurity”, Osaka City University Strategic Research Grant, 2020-2021
  • “Research and Development of Innovative Network Technologies to Create High-Density, High-Mobility, and Large-Scale Wireless Networks”, National Institute of Information and Communications Technology (NICT), 2016-2021
  • “Data-Driven Control Framework for Intelligent Logistic Automation”, Osaka City University Strategic Research Grant, 2018-2019
  • “Cooperative Synchronization of Networked Multi-Agent Systems”, Collaborative Research Grant, National Institute of Informatics (NII), 2018-2019
  • "Robust and Adaptive Distributed Control of Discrete-Event Systems", JSPS Grant-in-Aid for Young Scientists, 2016-2020
  • "Internal-Model Distributed Control Design for Complex Networks of Dynamic Agents", JSPS Grant-in-Aid for Young Scientists, 2014-2015
  • MEXT Program to Disseminate Tenure Tracking System, 2014-2016