Active Control of Longitudinal Combustion Instability in Bluff-Body Stabilized Premixed Flames with Multiple Neural Network Controller

The suppression performance of multiple neural network controller on the longitudinal combustion instability is investigated in the Volvo bluff-body stabilized premixed flame. Two controlled plant models, e.g. one-dimensional (1D) reduced order acoustic network model and three-dimensional (3D) large eddy simulation model are adopted to verify this control strategy. In order to build the reduced order Volvo acoustic network model, large eddy simulation is adopted to extract the characteristics of system heat release under wide bandwidth and construct the flame transfer functions. For the 1D acoustic network model, this controller can completely eliminate the pressure oscillation using fuel valve as actuator. For the 3D large eddy simulation model that mimics the real-time oscillating characteristics, clustered prediction method and amplitude limiting method are adopted in multiple neural network control strategy to better account for the nonlinear characteristics of the 3D Volvo flame. This control strategy enables the modulation of the phase relationship between the heat release rate oscillation and pressure oscillation by introducing small perturbations to the inlet equivalence ratio, and attenuates the amplitude of the second harmonic of the unstable mode effectively.