Making complex real-world dynamical systems sustainable requires multivariable control that handles multiple inputs, outputs, and state variables, together with optimization based on real-world data. Targeting industrial multi-axis motion systems and energy management systems, we conduct research spanning the theoretical development of control methods based on structured modeling and data-driven optimization through to experimental validation. Our goal is to develop control and optimization approaches that can be applied across systems in different fields.

Pushing beyond the limits of the sustainability trade-offs requires system design that spans multiple sectors, together with coordination among multiple stakeholders that accounts for the constraints of each sector. We conduct research toward building integrated cross-sector systems centered on energy, spanning areas such as electric power, transportation, logistics, communications, and data centers. We are engaged in demonstration research in collaboration with industry, including demand response that coordinates electric vehicles with electricity markets.

In parallel with promoting electrification for the effective utilization of renewable energy, it is also essential to decarbonize fuels and resources in areas that are difficult to electrify, including heat supply and chemical feedstocks. We conduct research toward the social implementation of energy technologies, including techno-economic analysis centered on the simultaneous optimization of economic efficiency, environmental compatibility, and supply stability in low-carbon hydrogen production that leverages renewable energy and electricity markets. Based on the insights gained, we also aim to contribute to policymaking and institutional design.