Imaduddin Fitrian, Arifin Zaenal, Mahmoud Essam Rabea Ibrahim, Aljabri Abdulrahman
Mechanical Engineering Department, Faculty of Engineering, Islamic University of Madinah, Medina 42351, Saudi Arabia.
Mechanical Engineering Program, Faculty of Engineering, Universitas Sebelas Maret, Surakarta 57126, Indonesia.
Micromachines (Basel). 2025 Jan 26;16(2):144. doi: 10.3390/mi16020144.
The dynamic relationship between current and pressure in magnetorheological (MR) valves is essential for the design of adaptive rehabilitation devices aimed at health rehabilitation for disabled individuals, yet it remains under-explored in existing modeling approaches. Accurately capturing this relationship is vital to predict the pressure drop response to current variations, facilitating the development of effective control systems in such rehabilitation applications. This study employs a linear black-box modeling approach to characterize the current-pressure dynamics of an annular MR valve. Experimental data are used to develop a set of transfer function models, with parameters identified through MATLAB's system identification tools, utilizing invariant variable regression and the Levenberg-Marquardt (LM) iteration. The modeling yielded a 14th-order transfer function, labeled TF14, which closely aligns with experimental data, achieving a root mean square error of 12.64%. These findings contribute valuable insights into the current-pressure dynamics of MR valves and establish a foundational model for adaptive rehabilitation devices designed for individuals with disabilities.
磁流变(MR)阀中电流与压力之间的动态关系对于旨在为残疾人进行健康康复的自适应康复设备的设计至关重要,但在现有的建模方法中仍未得到充分探索。准确捕捉这种关系对于预测压力降对电流变化的响应至关重要,有助于在此类康复应用中开发有效的控制系统。本研究采用线性黑箱建模方法来表征环形MR阀的电流-压力动态特性。实验数据用于开发一组传递函数模型,通过MATLAB的系统识别工具利用不变变量回归和列文伯格-马夸尔特(LM)迭代来识别参数。建模得到了一个14阶传递函数,标记为TF14,它与实验数据紧密吻合,均方根误差为12.64%。这些发现为MR阀的电流-压力动态特性提供了有价值的见解,并为为残疾人设计的自适应康复设备建立了基础模型。