Associate Professor, Kumamoto University, Japan | Research Field: Control Theory and Control Engineering
Hiroshi Okajima is an Associate Professor in the Faculty of Advanced Science and Technology at Kumamoto University, Japan. He received his Master's and Ph.D. degrees from the Graduate School of Engineering, Osaka University, in 2004 and 2007, respectively.
His research covers a broad range of control theory, with particular strengths in robust control, convex optimization (LMI-based design), and system identification. He proposed the Model Error Compensator (MEC), a versatile compensation structure that adds robustness to existing control systems. His work spans diverse control domains — including state estimation, quantized control, multi-rate systems, data-driven control, nonlinear systems, and vehicle dynamics — without being confined to a single methodology.
He has published over 80 journal papers and 65 international conference papers. He is a member of IEEE CSS, SICE, and ISCIE.
Model Error Compensator (MEC) The Model Error Compensator is a compensation structure that adds robustness to existing control systems without redesigning the base controller. By minimizing the effect of model errors and disturbances in the input-output relation, MEC can be readily applied to a wide range of systems including nonlinear systems, time-delay systems, non-minimum phase systems, and MIMO systems. → Details
Dynamic Quantizer A dynamic quantizer converts high-resolution signals into lower-resolution signals while minimizing quantization error. Our research focuses on the design of feedback-type dynamic quantizers under communication rate constraints, with applications to networked control systems and AD/DA conversion. → Details
Multi-rate Control Systems In practical control systems, sensors and actuators often operate at different sampling rates. Our research addresses the analysis and design of state observers and feedback controllers for multi-rate systems, formulated using cyclic reformulation and linear matrix inequality (LMI) optimization. → Details
Vehicle Control Our research applies control theory to vehicle dynamics, including direct yaw-moment control for electric vehicles, adaptive cruise control, and platoon driving of welfare vehicles. Model-based approaches including MEC are used to achieve robust and precise vehicle motion control. → Details
MCV Observer for Overcoming Outliers The Median of Candidate Vectors (MCV) Observer is a state estimation method robust to outliers in observation signals. By generating multiple state candidates and selecting via median operation, the observer maintains estimation accuracy even when sensor outputs are contaminated by outliers. → Details
Linear Matrix Inequality (LMI) Linear Matrix Inequality is a powerful mathematical tool widely used in control system analysis and design. This page provides an introductory explanation of LMI and its applications in control engineering, including stability analysis and optimal controller synthesis. → Details
IFAC TC 2.2. Linear Control Systems ifac-control.org
IFAC 2023 Publicity Member (twitter)
SICE JCMSI AE SICE Journal of Control, Measurement, and System Integration Editorial Board
Outreach
Researchmap / ORCID / Google scholar / Researchgate
YouTube (Control main channel, 10700 subscribers)
YouTube (English sub channel, 340 subscribers)
MATLAB File Exchange [Control Animation]
Github (MATLAB, Python codes)
Awards
SICE Education Contribution Award (2023)
SICE 2019 Poster Presentation Award Finalist
ICCAS 2017 Outstanding Paper Award
SICE CPD Point Award (2017)
ICCAS 2016 Outstanding Paper Award
SICE CPD Point Award (2011)
SICE 2010 Young Author Award Finalist
H. Okajima and T. Asai:Performance Limitation of Tracking Control Problem for a Class of References, IEEE Transactions on Automatic Control, Vol.56, No.11, pp.2723-2727 (2011)
H. Okajima, H. Umei, N. Matsunaga and T. Asai:A Design Method of Compensator to Minimize Model Error, SICE Journal of Control, Measurement, and System Integration, Vol.6, No.4, pp.267-275 (2013) (T&F, Open Access)
H. Okajima, K. Sawada and N. Matsunaga:Dynamic Quantizer Design Under Communication Rate Constraints, IEEE Transactions on Automatic Control, Vol.61, No.10, pp.3190-3196 (2016)
H. Okajima, Model Error Compensator for adding Robustness toward Existing Control, Preprints of the IFAC World Congress, pp. 3998 - 4005 (2023)
H. Okajima, Y. Hosoe and T. Hagiwara, State Observer under Multi-rate Sensing Environment and Its Design using l2 -Induced Norm, IEEE ACCESS (2023) (Open Access)
Hiroshi Okajima, Yusuke Fujimoto, Hiroshi Oku and Haruto Kondo, Cyclic Reformulation-Based System Identification for Periodically Time-Varying Systems | IEEE Journals & Magazine | IEEE Xplore , IEEE ACCESS (2025) (Open Access)
→ Full list with abstracts and MATLAB codes: Publications
Model Error Compensator
Dynamic Quantizer
Multi-rate state observer