Active Adaptive Combustion Control Using Neural Networks

Abstract

The suppression of pressure oscillations in combustion chambers through the use of active feedback control is a new technology with high potential. In this article, we present a feedback control strategy based on an Internal Model Control System for nonlinear plants that uses artificial neural networks. This control system uses two neural networks: The Internal Model which approximates the plant forward dynamic; and a controller which gives the appropriate control input. The controller's parameters are updated adaptively for that purpose. We demonstrate numerically the capabilities of the developped control system in a numerical simulation of control of combustion instabilities. Then, we demonstrate the ability of this neural networks based control system to actively damp instabilities in a Rijke-tube burner.

Keywords:

• adaptive control
• neural networks
• combustion instabilities

Additional information

Notes on contributors

R. BLONBOU

E-mail: [email protected] [email protected]

S. ZALESKI

E-mail: [email protected]