Learning-based Adaptive Thrust Regulation of Solid Fuel Ramjet
Parham Oveissi, Arjun Trivedi, Ankit Goel, Özgür Tümüklü, Kyle M. Hanquist, Alireza Farahmandi, Douglas Philbrick
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-2533.vid This paper uses retrospective cost adaptive control to regulate the thrust generated by a solid fuel ramjet engine. A one-dimensional quasi-static model based on the conservation of mass, momentum, and energy, along with a simplified regression model for solid fuel combustion, is used to model the solid fuel ramjet engine. We use the SFRJ model in open-loop simulations to establish the operational envelope of the engine. Then, RCAC is tuned to regulate the thrust produced by the engine in nominal and off-nominal operating conditions. The performance of the adaptive controller is compared with a fixed-gain controller optimized by RCAC under nominal operating conditions. In each case, it is observed that the RCAC significantly improves the transient performance.