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System Mathematics Lab
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The lab analyzes and designs dynamical systems using control theory and optimization theory.
AboutAbout the lab
Solving dynamical systems with the mathematics of control and optimization
The System Mathematics Lab studies the analysis and design of dynamical systems, mainly using control theory and optimization theory.
In recent years, the lab has been working on building foundational technologies that guarantee the reliability and stability of machine learning and deep learning algorithms and neural networks.
The lab actively pursues joint research with research institutions and companies in Japan and with research institutions overseas, aiming to train researchers and engineers who can work internationally.
Key terms
- Dynamical system
- A system whose state changes over time, expressed and handled using mathematical equations
- Control theory
- A mathematical theory for making machines and devices operate as intended
- Optimization theory
- A theory for mathematically finding the best solution under given conditions
- Neural network
- A computational structure modeled on the neural circuits of the brain. It is used in machine learning and deep learning.
NewsLab news
Paper accepted at the international conference IFAC World Congress 2026
Paper wins the Multi-Symposium Award (Fundamental Category) of the Control Division of the Society of Instrument and Control Engineers (SICE)
A master's student received the Outstanding Presentation Award at the 68th Joint Automatic Control Conference
ResearchResearch themes
The lab conducts broad research on the analysis and design of dynamical systems, using methods of mathematical engineering centered on control theory and optimization theory. In recent years, it has been actively working on building foundational technologies that guarantee the reliability and stability of machine learning and deep learning algorithms and neural networks.
*Illustrative imageAnalysis and Design of Dynamical Systems
The lab studies the analysis and design of dynamical systems, using methods of mathematical engineering centered on control theory and optimization theory. In recent years, it has been focusing on building foundational technologies that guarantee the reliability and stability of machine learning and deep learning algorithms and neural networks.
*Illustrative imageVerifying AI Reliability with Control Theory
This project, under the JST ASPIRE framework, builds the mathematical foundations of cyber-physical dynamical systems. The Kyushu University team is responsible for research that verifies the reliability of AI using control theory.
MembersFaculty
The members of the System Mathematics Lab consist of faculty, technical staff, secretaries, and doctoral and master's students.As of 2026
- ProfessorYoshio Ebihara
VoicesStudent voices
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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: “Main Control Room at ESA's Space Operations Centre ESA11252261” European Space Agency / CC BY-SA 3.0 igo (cropped)
- Analysis and Design of Dynamical Systems: “PHX control tower 20250508” Designism / CC0 (cropped)
- Verifying AI Reliability with Control Theory: “The ESA Seeker autonomous rover during tests at Paranal” ESA/RAL Space/ESO / CC BY 3.0 (cropped)
- Related lab (超伝導理工学研究室): “V3GaWire-es” Pitana / CC BY 4.0 (cropped)
- Related lab (制御と
最適化の 研究室): “Robots header” RealAws / CC BY-SA 4.0 (cropped) - Related lab (文化知能科学研究室): “Jacques-Louis David - Oath of the Horatii - Google Art Project” Anne-Louis Girodet / After Jacques-Louis David / Public domain (cropped)
- Related lab (サイバーフィジカル・コンピューティング研究室): “Superconducting Quantum-Limited Amplifier Chip in Navaho” OJB Quantum / CC BY 4.0 (cropped)
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