Feedforward control of sound and vibration using a neural network-based control system is considered, with the aim being to derive an architecture / algorithm combination which is capable of supplanting the commonly used finite impulse response filter / filtered-x least mean square (LMS) linear arrangement for certain nonlinear problems. An adaptive algorithm is derived which enables stable adaptation of the neural controller for this purpose, while providing the capacity to maintain causality within the control scheme. The algorithm is shown to be simply a generalization of the linear filtered-x LMS algorithm. Experiments are undertaken which demonstrate the utility of the proposed arrangement, showing that it performs as well as a linear control system for a linear control problem. The experiments also lead to the conclusion that more work is required to improve the predictability and consistency of the performance before the neural network controller becomes a practical alternative to the current linear feedforward systems.
Active control of vibration using a neural network
Aktive Vibrations-Regelung mit einem neuronalen Netz
IEEE Transactions on Neural Networks ; 6 , 4 ; 819-828
1995
10 Seiten, 14 Bilder, 1 Tabelle, 25 Quellen
Aufsatz (Zeitschrift)
Englisch
A neural network based active vibration absorber with state feedback control
Online Contents | 1996
|Active Vibration Isolation Using Fuzzy CMAC Neural Networks
British Library Conference Proceedings | 1995
|Vibration control of suspension systems using a proposed neural network
Online Contents | 2004
|