Group Method of Data Handling for Modeling Magnetorheological Dampers  

作　　者：Khaled Assaleh Tamer Shanableh Yasmin Abu Kheil 

机构地区：[1]Department of Computer Science and Engineering, American University of Sharjah, Sharjah, United Arab Emirates [2]Department of Electrical Engineering, American University of Sharjah, Sharjah, United Arab Emirates [3]Mechatronics Graduate Program, American University of Sharjah, Sharjah, United Arab Emirates

出　　处：《Intelligent Control and Automation》2013年第1期70-79,共10页智能控制与自动化（英文）

摘　　要：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%.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%.

关 键 词：System IDENTIFICATION Magneto-Rheological DAMPERS GROUP Method of Data HANDLING POLYNOMIAL CLASSIFIER 

分 类 号：R73[医药卫生—肿瘤]