Data-based predictive combustion control
نویسندگان
چکیده
An optimal predictive control approach for the suppression of thermo-acoustic instabilities in the combustor chamber is investigated. The approach uses the combustor pressure fluctuations and fuel modulation data for building internal dynamic input-output models and designing the controller. The knowledge of the physical model of the system is not required. This data-based nature of the approach is therefore useful for rapid prototyping to different geometries and new configurations without having to spend time in developing the physical models. The control approach is capable of rejecting unknown periodic disturbances to the system in an implicit manner. This capability is critical in stabilizing the pressure fluctuations in the combustor system, which is characterized by a very high noise to signal ratio. The simulation results illustrating the success of the control approach in stabilizing the pressure fluctuations are presented.
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