Identification and verification of a MR damper using a nonlinear black box model Truong D.Q., Ahn K.K., Yoon J.I., Thanh T.Q. School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan 680-749, South Korea; Hochiminh City University of Technology, Viet Nam Abstract: Nowadays, magneto-rheological (MR) fluid dampers (MRD) are widely used for the semi-active suspension control in vibration community. However, the inherent nonlinear nature of the MRD causes challenges for damping control of the suspension system using this device with high performance. Therefore, the development of an accurate modeling method for a MRD is necessary to take advantage of its unique characteristics. This paper focuses on the development of a nonlinear black box model to identify and verify behaviors of a MR damper. The model is built by using an online self tuning fuzzy (OSTF) method based on neural technique. The behavior of the MRD is directly estimated through the box. A series of experiments and modeling analysis had been done on test rigs to validate the effectiveness of the design nonlinear black box in predicting the damping force. Index Keywords: Accurate modeling; Black boxes; Black-box model; Damping control; Damping forces; Magnetorheological fluid damper; Modeling analysis; MR dampers; Neural techniques; Nonlinear nature; Selftuning; Semi active suspension; Suspension system; Test rigs; Damping; Robotics; Suspensions (components) Year: 2009 Source title: Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA Art. No.: 5423167 Page : 435-440 Link: Scorpus Link Correspondence Address: Ahn, K. K.; School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan 680-749, South Korea; email:
[email protected] Conference name: 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2009 Conference date: 15 December 2009 through 18 December 2009 Conference location: Daejeon Conference code: 79970 DOI: 10.1109/CIRA.2009.5423167 Language of Original Document: English Abbreviated Source Title: Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA Document Type: Conference Paper Source: Scopus
Authors with affiliations: 1. Truong, D.Q., School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan 680-749, South Korea 2. Ahn, K.K., School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan 680-749, South Korea 3. Yoon, J.I. 4. Thanh, T.Q., Hochiminh City University of Technology, Viet Nam
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