The following paper has been published in IET Control Theory & Applications.
M. Sekine, S. Tsuruhara, K. Ito, “Optimized Design of a Pseudo–linearization–based Model Predictive Controller: Direct Data–driven Approach,” IET Control Theory & Applications, Vol. 19, Issue 1, 2025. [Link]
The following paper has been accepted by International Journal of Automation Technology. It will be published soon.
S. Tsuruhara, K. Ito, “Hierarchical-type Model Predictive Control and Experimental Evaluation for a Water-Hydraulic Artificial Muscle with Direct Data-Driven Adaptive Model Matching,” International Journal of Automation Technology Vol. 19, No. 3, pp. ??-?? , 2025, to be published [arXiv]
The following paper has been accepted by IET Control Theory & Applications. It will be published soon.
M. Sekine, S. Tsuruhara, K. Ito, “Optimized Design of a Pseudo–linearization–based Model Predictive Controller: Direct Data–driven Approach,” IET Control Theory & Applications, Vol. ??, No. ??, pp. ??-??, 2025, to be published.
Gave a talk at the integration of model-based and data-driven control at the 39th Multibody Dynamics Research Meeting held on December 4, 2024, at Surugadai Campus of Meiji University in Tokyo.
At The 12th JFPS International Symposium on Fluid Power Hiroshima 2024, we received “Student Presentation Award”. [Link] The awarded papers are as follows:
S. Tsuruhara, K. Ito, “Direct Data-Driven Adaptive Model Matching Based Model Predictive Displacement Control for a Water-Hydraulic Artificial Muscle and Robustness Evaluation to Characteristics Change”, the 12th JFPS International Symposium on Fluid Power in Hiroshima, 1D1-04, 2024.
We presented our research results in two papers at The 12th JFPS International Symposium on Fluid Power Hiroshima 2024 held at Hiroshima International Conference Center from October 22 to 25, 2024.
S. Tsuruhara, K. Ito, “Direct Data-Driven Adaptive Model Matching Based Model Predictive Displacement Control for a Water-Hydraulic Artificial Muscle and Robustness Evaluation to Characteristics Change”, the 12th JFPS International Symposium on Fluid Power in Hiroshima 2024, 1D1-04, 2024.
We participated in 27th International Fluid Power Exhibition (IFPEX2024) at Tokyo Big Sight and presented three research results.
A preprint of the following title is now available on arXiv.
S. Tsuruhara, K. Ito, “Discrete-time Indirect Adaptive Control for Systems with State-Dependent Disturbances via Directional Forgetting: Concurrent Learning Approach,” arXiv preprint arXiv:2409.09316, 2024. [arXiv]
A preprint of the following title is now available on arXiv.
「Hierarchical-type Model Predictive Control and Experimental Evaluation for a Water-Hydraulic Artificial Muscle with Direct Data-Driven Adaptive Model Matching」[arXiv]
The following two papers (first: first author, second: co-author) were accepted to The 12th JFPS International Symposium on Fluid Power Hiroshima 2024. The papers will be presented in Hiroshima from October 22 to 25.
・「Direct Data-Driven Adaptive Model Matching Based Model Predictive Displacement Control for a Water-Hydraulic Artificial Muscle and Robustness Evaluation to Characteristics Change」
・「Ultra-Local Model Based Data-Driven Control for McKibben-type Artificial Muscles with Control Parameter Optimization Using VRFT」
The paper “Adaptive FRIT-based Recursive Robust Controller Design with Forgetting Factors” presented at the 32nd Mediterranean Conference on Control Automation (MED) is now available.
https://ieeexplore.ieee.org/document/10566181
I gave a presentation entitled “Concurrent Learning-based Linear Approximation Model and Adaptive Displacement Control for a Water-Hydraulic Artificial Muscle” at the 2024 Spring Fluid Power Systems Conference held at the Japan Society for the Promotion of Machine Industry in Tokyo on June 20 and 21.
I gave a presentation entitled “Adaptive FRIT-based Recursive Robust Controller Design Using Forgetting Factors” at “The 32nd Mediterranean Conference on Control and Automation” held in Chania (Crete, Greece) on June 11-14.
This is the first article.