Our laboratory conducts research at the intersection of systems control, energy, and information and communication technologies. Building on a broad range of academic disciplines—including
Systems and Control Theory, Informatics, Big Data Science, Mathematical Optimization, and Software Engineering
—we study the mathematical foundations that enable future social infrastructure systems. Our work focuses particularly on:
Smart Grids = Next-generation power systems that maximize the utilization of renewable energy
Beyond 5G/6G = Next-generation information and communication networks beyond fifth-generation mobile systems
The “mathematical science” we pursue is not merely the manipulation of equations. Instead, it is a discipline that uncovers the essential principles and structural mechanisms behind complex phenomena using mathematics. By extracting and understanding the hidden structure of modern large-scale social systems, we aim to design optimal and sustainable infrastructure for the future.
Major Research Topics
(We challenge ourselves to advanced research topics for smart society)
We are studying retrofit control theory for modular design of large-scale control systems where multiple independent entities make their own decision for local system management. Current work is on data-adaptive control based on machine learning techniques. [more]
Commendation for Science and Technology by MEXT
We are developing an energy system simulator to support students and researchers in systems and control community for starting energy-related research work, named GUILDA: Grid & Utility Infrastructure Linkage Dynamics Analyzer. [more]
We are conducting a mathematical study of inverter control that uses the equilibrium-independent passivity of synchronous generators to make renewable energy a companion of grid-forming generators. This is closely related to the principle of frequency synchronization of the Kuramoto model in nonlinear science. [more]
We are developing an energy management method robust against the volatility of renewable power generation, modeled as confidence intervals and stochastic variables. [more]
We are studying a systems control theory for complex systems based on the notion of set-based modeling, towards designing smart human and social systems. [more]
We are developing a spatio-temporal energy market model in terms of an adjustable robust convex program towards smart management of distributed energy resources. Numerical simulations are conducted for analyzing optimal share of future energy resources. [more]
We are studying a model reduction theory for large-scale network systems and distributed control systems, where the notion of data clustering is applied. [more]
We are conducting R&D of distributed time synchronization technology in anticipation of the widespread use of atomic clock chips. Ultra-high precision time synchronization is also positioned as the basis for realizing Beyond 5G. [more]