@inproceedings{oveissi2026,
	title = {Thrust {Regulation} in a {Solid} {Fuel} {Ramjet} {Using} {Dynamic} {Mode} {Adaptive} {Control}},
	doi = {10.2514/6.2026-1389},
	abstract = {This paper presents the application of a novel data-driven adaptive control technique, called dynamic mode adaptive control (DMAC), for regulating thrust in a solid fuel ramjet (SFRJ). A high-fidelity computational model incorporating compressible flow theory and equilibrium chemistry is used to simulate the combustion dynamics. An adaptive tracking controller is designed using the DMAC framework, which leverages dynamic mode decomposition to approximate the local system behavior, followed by a tracking controller synthesized around the identified model. Simulation results demonstrate that DMAC provides an effective and reliable approach for thrust regulation in SFRJs. In addition, a systematic hyperparameter sensitivity study is conducted by varying the tuning parameters over several orders of magnitude. The resulting responses show that the closed-loop performance and tracking error remain stable across wide parameter variations, indicating that DMAC exhibits strong robustness to hyperparameter tuning.},
	urldate = {2026-01-23},
	booktitle = {{AIAA} {SCITECH} 2026 {Forum}},
	publisher = {AIAA 2026-1389},
	author = {Oveissi, Parham and Khokhar, Gohar T. and Hanquist, Kyle M. and Goel, Ankit},
	year = {2026},
	keywords = {own},
}

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