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.