Neural net controller for noise and vibration reduction
US6493689B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 29, 2000 |
| Grant date | Dec 10, 2002 |
| Priority date | — |
| Expiry date | Dec 29, 2020 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T50/30
- WIPO fieldMechanical elements
- WIPO sectorMechanical engineering
Abstract
Two neural networks are used to control adaptively a vibration and noise-producing plant. The first neural network, the emulator, models the complex, nonlinear output of the plant with respect to certain controls and stimuli applied to the plant. The second neural network, the controller, calculates a control signal which affects the vibration and noise producing characteristics of the plant. By using the emulator model to calculate the nonlinear plant gradient, the controller matrix coefficients can be adapted by backpropagation of the plant gradient to produce a control signal which results in the minimum vibration and noise possible, given the current operating characteristics of the plant.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.