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Sadamoto Lab
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The lab studies data utilization and power systems with control theory at its core.
AboutAbout the lab
Solving data and power challenges with control theory.
The Sadamoto Lab conducts interdisciplinary research that combines control-theoretic machine learning with power engineering.
Theoretical research means presenting methodologies for solving problems together with their justification, for example by proposing and verifying algorithms or by giving mathematical answers to problems.
Recently, the lab has been working on new data-driven control methods (including reinforcement learning) and on international research aimed at solving social issues such as smart grids.
At present, most of the research is completed through mathematics and simulation, and the lab conducts almost no experiments.
Key terms
- Control theory
- A theory that uses mathematics to design the inputs needed to make machines and equipment operate as intended
- Power system
- The entire system that generates electricity at power plants and delivers it to homes through substations
- Power flow
- The state of electricity flowing through a power grid. The stability of the grid depends heavily on this state
NewsLab news
A master's student received an Outstanding Student Award
A paper by Associate Professor Sadamoto and others has been accepted for publication in Systems and Control Letters
A paper by a master's student and Associate Professor Sadamoto has been accepted for publication in the Transactions of the Institute of Systems, Control and Information Engineers
A paper from joint research between Associate Professor Sadamoto and North Carolina State University has been accepted for publication in IEEE Transactions on Smart Grid
A paper from joint research between Associate Professor Sadamoto and North Carolina State University has been accepted for publication in IEEE Transactions on Control Systems Technology
ResearchResearch themes
From the standpoint of control theory, the lab studies the prediction and control of large-scale systems where only limited information is available, and the control of power systems with a growing share of renewable energy sources. Its themes are to clarify mathematically how much data is needed and what can be achieved, and to build methodologies for power systems that can accommodate change while maintaining stability.
*Illustrative imagePrediction and control with limited information
In large-scale systems, the data that can be collected and the information that can be used are limited. The lab builds a mathematical foundation for answering how much data is needed and what can be achieved with limited information, covering cases where only part of the internal state can be observed and cases where only partial knowledge of the target system is available.
*Illustrative imagePower system control in the age of renewable energy
With the spread of renewable energy sources such as solar power, power systems are becoming more complex. The lab is developing power engineering based on control theory that can maintain supply-demand balance and stability while making use of renewable energy. Examples of collaborative research include searching for power flows that achieve both economic efficiency and stability, and analyzing the conditions under which suppressing the vibration of wind turbines becomes difficult.
MembersFaculty
The Sadamoto Lab consists of faculty members, master's and undergraduate students, and administrative staff.As of 2026
- Associate ProfessorTomonori Sadamoto
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Switchyard of electric substation 750kV” Novoklimov / CC BY 4.0 (cropped)
- Prediction and control with limited information: “Davit control panel HMS Albion” Antti Leppänen / CC BY 4.0 (cropped)
- Power system control in the age of renewable energy: “D&Y Apartelle Resort Solar PV System” AndieART / CC0 (cropped)
- Related lab (Kaneko Lab): “Feedback control system” Controlsystemintro / CC BY-SA 4.0 (cropped)
- Related lab (Kogiso Lab): “RotaryInvertedPendulum” Quanser Inc. / CC BY 2.5 (cropped)
- Related lab (Funato Lab): “CerebellumSlice” Caldwbr / CC0 (cropped)
- Related lab (Tanaka Lab): “Quadrotor drone in blue ski 03” Игоревич / CC BY-SA 3.0 (cropped)
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