Title :
Linearization of magnetorheological behaviour using a neural network
Author :
Kim, Byeonghwa ; Roschke, Paul N.
Author_Institution :
Texas A&M Univ., College Station, TX, USA
Abstract :
A magnetorheological (MR) damper is a recently invented electromechanical semi-active control device that holds promise for applications to ameliorate structural vibration. However, nonlinear characteristics of MR dampers are delaying field installation. This paper provides a linearization scheme for MR damper behaviour using a neural network that is applicable for an online control environment
Keywords :
backpropagation; damping; linearisation techniques; magnetorheology; neurocontrollers; structural engineering; vibration control; backpropagation; damping; electromechanical devices; linearization; magnetorheological damper; magnetorheology; neural network; semiactive control; structural vibration control; Civil engineering; Damping; Friction; Hysteresis; Magnetic devices; Mathematical model; Neural networks; Shock absorbers; Stress; Vibrations;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.786437
