SFRJ

Data-driven, Learning-based, Adaptive Control of Solid Fuel Ramjet

The project aims to develop a learning-based adaptive control system for regulating the thrust of solid-fuel ramjets (SFRJs) under realistic flight conditions and in the presence of model uncertainties. By combining multi-fidelity computational modeling, adaptive control synthesis, and integrated multi-physics simulation, the research seeks to enable real-time thrust regulation and prevent engine unstart events. A simplified quasi-steady SFRJ model, derived from analytical ramjet theory and NASA’s chemical equilibrium analysis, is being validated against experimental data from China Lake and embedded within a Retrospective Cost Adaptive Control (RCAC) framework to demonstrate model-free, learning-based thrust regulation. An integrated simulation environment couples the SFRJ dynamics with flight and control system models to emulate realistic flight scenarios, while benchmark controllers such as LQG and reduced-order models provide performance baselines. Ultimately, the work aims to demonstrate that a controller trained on simplified models can adapt online to high-fidelity, dynamically coupled simulations, thereby paving the way for robust, learning-based propulsion control in next-generation hypersonic systems.

Team

  • Principal Investigator – Dr. Ankit Goel, Assistant Professor, University of Maryland, Baltimore County
  • Co-Principal Investigator – Dr. Kyle Hanquist, Assistant Professor, Purdue University
  • Co-Principal Investigator – Dr. Brian Reitz, NAWCWD, China Lake, CA
  • Co-Principal Investigator – Dr. Alireza Farahmandi, NAWCWD, China Lake, CA
  • Student Members
    • Parham Oveissi, PhD Candidate, University of Maryland, Baltimore County
    • Alex Dorsey, Undergraduate Research Assistant, University of Maryland, Baltimore County
    • Alex Boueri, PhD Candidate, Purdue University
  • Past Team Members
    • Joshua McBeth, PhD Candidate, University of Arizona
    • Avery White, PhD Candidate, University of Arizona
    • Dr. Raghava Davuluri, Postdoctoral Research Fellow, University of Arizona
    • Dr. Gohar T. Khokhar, Postdoctoral Research Fellow, University of Arizona
    • Dr. Ozgur Tumuklu, Assistant Professor, RPI

Publications

  1. Oveissi, P., Trivedi, A., Goel, A., Tumuklu, O., Hanquist, K. M., Farahmandi, A., and Philbrick, D., “Learning-Based Adaptive Thrust Regulation of Solid Fuel Ramjet,” AIAA SciTech 2023 Forum, AIAA Paper 2023-2533, January 2023. DOI: https://doi.org/10.2514/6.2023-2533
  2. Oveissi, P., Goel, A., Tumuklu, O., and Hanquist, K. M., “Adaptive Combustion Regulation in Solid Fuel Ramjet,” AIAA SciTech 2024 Forum, AIAA Paper 2024-0743, January 2024. DOI: https://doi.org/10.2514/6.2024-0743
  3. Oveissi, P., Dorsey, A., Khokhar, G. T., Hanquist, K. M., and Goel, A., “Adaptive Combustion Regulation in High-Fidelity Computational Model of Solid Fuel Ramjet,” AIAA SciTech 2025 Forum, AIAA Paper 2025-0352, January 2025. DOI: https://doi.org/10.2514/6.2025-0352
  4. Khokhar, G. T., McBeth, J., Hanquist, K. M., Oveissi, P., and Goel, A., “Investigation of Solid Fuel Ramjets Using Analytical Theory and Computational Fluid Dynamics,” AIAA SciTech 2025 Forum, AIAA Paper 2025-0392, January 2025. DOI: https://doi.org/10.2514/6.2025-0392
  5. Oveissi, P., Dorsey, A., McBeth, J., Hanquist, K. M., and Goel, A., “Learning-Based Thrust Regulation of Solid-Fuel Ramjet in Flight Conditions,” AIAA SciTech 2025 Forum, AIAA Paper 2025-2805, January 2025. DOI: https://doi.org/10.2514/6.2025-2805
  6. DeBoskey, R., Oveissi, P., Narayanaswamy, V., and Goel, A., “An In-Situ Solid Fuel Ramjet Thrust Monitoring and Regulation Framework Using Neural Networks and Adaptive Control,” 2025 IEEE Conference on Control Technology and Applications (CCTA), IEEE, August 2025, pp. 377–382. DOI: 10.1109/CCTA53793.2025.11151497
  7. [Accepted] Dorsey, A., Oveissi, P., Barton, J. D., and Goel, A., “Swarm-optimized Adaptive Augmentation of Missile Autopilot,” AIAA SciTech 2026 Forum, January 2026.
  8. [Accepted] Dorsey, A., and Goel, A., “Feedback Linearization-based Guidance Law for Guaranteed Interception,” AIAA SciTech 2026 Forum, January 2026.
  9. [Accepted] Oveissi, P., Khokhar, G. T., Hanquist, K. M., and Goel, A., “Thrust Regulation in a Solid Fuel Ramjet using Dynamic Mode Adaptive Control,” AIAA SciTech 2026 Forum, January 2026.
  10. [Accepted] McBeth, J., Hanquist, K. M., Oveissi, P., and Goel, A., “RANS-Fidelity Modeling and Control of Solid Fuel Ramjets,” AIAA SciTech 2026 Forum, January 2026.
  11. [Under review] Khokhar, G. T., Hanquist, K. M., Oveissi, P., and Goel, A., “Computational Modeling and Learning-Based Adaptive Control of Solid-Fuel Ramjets,” AIAA Journal.
  12. [Under review] DeBoskey, R., Oveissi, P., Narayanaswamy, V., and Goel, A., “Evaluation of In-situ Adaptive Thrust Monitoring and Regulation Framework for Solid-Fuel Ramjets,” AIAA Journal.
  13. [In preparation] Dorsey, A., and Goel, A., “A Generalized Guidance Law for Missile Interception,” Journal of Guidance, Navigation, & Control.