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Applied Mathematical Systems Lab
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The lab studies the modeling and control of a wide variety of systems using mathematical approaches.
AboutAbout the lab
Controlling systems with mathematical methods
The Applied Mathematical Systems Lab studies the modeling, control, and data analysis of a wide variety of systems using mathematical approaches.
The lab places importance on considering the essential characteristics of its subject and on building accurate models and problem formulations.
Its goal is to establish a theoretical framework for modeling and design that realizes robust cyber-physical systems, and to apply it to real systems.
In addition to individual progress meetings, the lab holds reading seminars on the literature on systems and control, optimization, signal processing, and related topics.
Key terms
- Cyber-physical system
- A system that connects computer-based information processing with machines and environments in the real world.
- Robustness
- The property of maintaining performance even when there are errors or changes in conditions.
- Nonlinear time series analysis
- A set of methods for mathematically investigating the complex changes in data that vary over time.
NewsLab news
Lab introduction sessions held for students preparing for lab assignment (Oct 15, Oct 22, Oct 27)
A paper by a graduate and Prof. Kawabe was published in the Transactions of the Institute of Systems, Control and Information Engineers
A paper by a master's student and Prof. Kawabe was accepted by the Malaysian Journal of Student Advancement
A doctoral student received a student award (President's Award)
A master's student received the SICE Outstanding Student Award from the Society of Instrument and Control Engineers
ResearchResearch themes
Building on systems and control theory, optimization theory, signal processing, nonlinear time series analysis, and machine learning, the lab studies theories and technologies for modeling a wide variety of systems, time series analysis, control system design, and decision-making. Its ultimate goal is to build a unified theoretical framework for modeling and design that realizes robust cyber-physical systems, and to apply it to real systems.
*Illustrative imageFinding Mathematical Structure with AI for Cooperative Control
The lab explores the principles of control design that allow multiple agents to act cooperatively in risky, uncertain environments. By building mathematical constraints such as matroids into deep learning models, it aims to realize safe reinforcement learning (Safe-RL) that takes risk into account while also maintaining safety.
*Illustrative imageControl Technologies for Vehicle Systems
Targeting automobiles, ships, aircraft, and wheeled mobile robots, the lab studies control technologies that improve motion performance, safety, and ride comfort, as well as the automation of cooperative work among multiple mobile robots. It also works on the control of next-generation electric vehicles and on platoon formation control that applies a model of bat flight.
*Illustrative imageTheory and Applications of Nonlinear Time Series Analysis
With the aim of deepening the analysis of time series data and bringing about social change, students work on understanding and predicting large earthquakes and on distinguishing patients, such as those with Parkinson's disease, from healthy people using gait data. The lab says that if the shapes of chromosomes can be understood in detail, it may become possible to characterize tissues and explain diseases.
*Illustrative imageMachine Learning and Optimization for Decision-Making
The lab develops methods that combine machine learning and mathematical optimization to optimize future decisions under uncertainty. To overcome the challenge that prediction errors are unavoidable, it works on developing more robust prediction and optimization methods.
MembersFaculty
Members of the Applied Mathematical Systems Lab consist of faculty members and doctoral, master's, and undergraduate students.As of 2025
- ProfessorTohru Kawabe
- ProfessorYoshito Hirata
- Assistant ProfessorShunnosuke Ikeda
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: “Engine Control Room Harmony of the Seas 2026” Larry D. Moore / CC BY 4.0 (cropped)
- Finding Mathematical Structure with AI for Cooperative Control: “MIREA Interdepartmental educational and scientific laboratory Intelligent Autonomous and multi-agent robotic systems 7” Нечаева Лилия Александровна / CC BY-SA 4.0 (cropped)
- Control Technologies for Vehicle Systems: “Vector3DHD autonomous robot and EnZone wireless charging” PattyK33 / CC BY-SA 4.0 (cropped)
- Theory and Applications of Nonlinear Time Series Analysis: “A U.S. Airman walks on a treadmill during a gait analysis appointment at the 628th Medical Operations Squadron at Joint Base Charleston, S.C 130108-F-GE255-020” Staff Sgt. Anthony Hyatt / Public domain (cropped)
- Machine Learning and Optimization for Decision-Making: “Loading a container ship” Federal Highway Administration / Public domain (cropped)
- Related lab (システム数理研究室): “388 King - server room ( )” Mike Beltzner / CC BY-SA 2.0 (cropped)
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グラフィックス研究室): “Apophysis 3D fractal ball” Garden / CC BY-SA 3.0 (cropped) - Related lab (認知システムデザイン研究室): “Tesla Autopilot Engaged in Model X” Ian Maddox / CC BY-SA 4.0 (cropped)
- Related lab (ブラックボックス最適化研究室): “Server Room Terminals ( )” Jon Parise / CC BY-SA 2.0 (cropped)
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