TITLE:
Group Method of Data Handling for Modeling Magnetorheological Dampers
AUTHORS:
Khaled Assaleh, Tamer Shanableh, Yasmin Abu Kheil
KEYWORDS:
System Identification; Magneto-Rheological Dampers; Group Method of Data Handling; Polynomial Classifier
JOURNAL NAME:
Intelligent Control and Automation,
Vol.4 No.1,
February
18,
2013
ABSTRACT: This paper proposes the use of Group Method of Data Handling (GMDH) technique for modeling Magneto-Rheological (MR) dampers in the context of system identification. GMDH is a multilayer network of quadratic neurons that offers an effective solution to modeling non-linear systems. As such, we propose the use of GMDH to approximate the forward and inverse dynamic behaviors of MR dampers. We also introduce two enhanced GMDH-based solutions. Firstly, a two-tier architecture is proposed whereby an enhanced GMD model is generated by the aid of a feedback scheme. Secondly, stepwise regression is used as a feature selection method prior to GMDH modeling. The proposed enhancements to GMDH are found to offer improved prediction results in terms of reducing the root-mean-squared error by around 40%.