Title :
MRF Damper Control Based on Fuzzy Neural Network
Author :
Zhanhui, Yan ; Liqiang, Li ; Xiaodong, Li
Author_Institution :
Changchun Inst. of Technol., Changchun, China
Abstract :
Semi-active fuzzy neural network control is presented in terms of nonlinear characteristic of MRF(magneto-rheological fluid) damper, simulating results show that semi-active control using fuzzy neural network can effectively reduce MRF damper´s vibration displacement and acceleration response. Simulation examples verify the effectiveness and practicability of proposed method, the body and tires´ acceleration response value is only 59.0% of passive control.
Keywords :
fuzzy control; fuzzy neural nets; magnetorheology; neurocontrollers; shock absorbers; tyres; vehicle dynamics; vibration control; MRF damper control; magneto-rheological fluid; semiactive fuzzy neural network control; tire acceleration response; vibration displacement; Automatic control; Control systems; Damping; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Neural networks; Shock absorbers; Vehicles; Vibration control; Control; Fuzzy; MRF Damper; Neural Network;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.551
