Title :
Real-time vibration control using CMAC neural networks with weight smoothing
Author :
Kraft, L.G. ; Pallotta, Jeremy
Author_Institution :
Dept. of Electr. & Comput. Eng., New Hampshire Univ., Durham, NH, USA
Abstract :
The CMAC neural network concept is applied to real-time active vibration control at audio rates. A new weight smoothing CMAC is used in the control loop to cancel a disturbance input
Keywords :
CAMAC; active noise control; closed loop systems; learning (artificial intelligence); neurocontrollers; real-time systems; CMAC neural networks; active vibration control; audio rates; closed loop systems; learning; real-time systems; weight smoothing; Equations; Function approximation; Neural networks; Open loop systems; Process control; Signal processing; Smoothing methods; State-space methods; Training data; Vibration control;
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-5519-9
DOI :
10.1109/ACC.2000.876961
