TY - JOUR
T1 - Artificial neural networks in vibration control of rotor-bearing systems
AU - Al-Nassar, Yaagoub N.
AU - Siddiqui, Mohsin
AU - Al-Garni, Ahmed Z.
PY - 2000/3/15
Y1 - 2000/3/15
N2 - A neural network controller is described and implemented for controlling the vibration of a rotor-bearing system. A multi-layered neural network is used to model the inverse dynamics or the rotor-bearing system on-line. It is learnt by a backpropagation algorithm, and a delta rule, in which the difference between the actual control input to the plant, which is generated from the neural controller, and the input estimated from the inverse-dynamics model by using an actual plant output, is minimized. The results show a satisfactory diminished response of the rotor-bearing system when the controller is applied to the system.
AB - A neural network controller is described and implemented for controlling the vibration of a rotor-bearing system. A multi-layered neural network is used to model the inverse dynamics or the rotor-bearing system on-line. It is learnt by a backpropagation algorithm, and a delta rule, in which the difference between the actual control input to the plant, which is generated from the neural controller, and the input estimated from the inverse-dynamics model by using an actual plant output, is minimized. The results show a satisfactory diminished response of the rotor-bearing system when the controller is applied to the system.
UR - https://www.scopus.com/pages/publications/0034653073
U2 - 10.1016/S0928-4869(00)00004-5
DO - 10.1016/S0928-4869(00)00004-5
M3 - Article
AN - SCOPUS:0034653073
SN - 0928-4869
VL - 7
SP - 729
EP - 740
JO - Simulation Practice and Theory
JF - Simulation Practice and Theory
IS - 8
ER -