Title :
Research on Active Vibration Control Based on Artificial Neural Network
Author_Institution :
Wulan Technol. Co., Ltd., Ningbo, China
Abstract :
In this paper, magneto-rheological active vibration control was researched based on Artificial Neural System, aimed at the research on natural frequency of vibration isolation system and load disturbance vibration suppression, used of feedback and feed forward control method, in order to reduce the resonance of system natural frequency and vibration of load disturbance. By numerical simulation and experimental verification, the study method used in this paper is feasible.
Keywords :
feedback; feedforward; magnetorheology; neurocontrollers; vibration isolation; artificial neural network; artificial neural system; feed forward control method; feedback control method; load disturbance vibration suppression; magneto-rheological active vibration control; vibration isolation system; Acceleration; Artificial neural networks; Coils; Frequency control; Resonant frequency; Vibration control; Vibrations; Active vibration control; Artificial Neural Network; Disturbance; Natural frequency;
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4799-4262-6
DOI :
10.1109/ISDEA.2014.178
