Neural network compensation of semi-active control for magneto-rheological suspension with time delay uncertainty

• Published in: Smart materials and structures Vol. 18; no. 1; pp. 015014 - 015014 (14)
• Main Authors: Dong, XiaoMin, Yu, Miao, Li, Zushu, Liao, Changrong, Chen, Weimin
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.01.2009; Institute of Physics
• Subjects: Applied sciences; Exact sciences and technology; Machine components; Mechanical engineering. Machine design; Springs and dampers; Human; Time frequency domain method; Pavement; Highway; Frequency domain method; Shock absorbers; Neural network; Passive system; Experimental study; Modeling; Magnetorheological fluid; Uncertain system; Time domain method; Vehicle suspension; Active system; Delay time; Dynamic model; Intelligent control

This study presents a new intelligent control method, human-simulated intelligent control (HSIC) based on the sensory motor intelligent schema (SMIS), for a magneto-rheological (MR) suspension system considering the time delay uncertainty of MR dampers. After formulating the full car dynamic model f...