Austin Nash
Austin Nash received B.S. and M.S. degrees in mechanical engineering from Rose-Hulman in 2013 and 2015, respectively, and a Ph.D. in mechanical engineering from Purdue University in 2019. His academic background includes expertise in dynamics and control systems as well as thermal-fluid systems and aerospace systems. His teaching interests encompass a range of disciplines from dynamics and control to thermodynamics. His research explores the use of integrated design and control methods aimed at broadening the performance envelope of a variety of energy-related systems. Away from the classroom, he enjoys staying active through running, cycling, and strength training.

Academic Degrees

  • B.S. Mechanical Engineering, Rose-Hulman Institute of Technology, 2013
  • M.S. Mechanical Engineering, Rose-Hulman Institute of Technology, 2015
  • Ph.D. Mechanical Engineering, Purdue University, 2019

Personal

Away from the classroom, he enjoys staying active through running, cycling, and strength training.

Publications & Presentations

  • A. L. Nash, "Model Predictive Tracking Control With Parameter Estimation for Spin-Stabilized Indirect Fire Symmetric Projectiles," in ASME. Letters Dyn. Sys. Control, Vol. 2(3), 2022.
  • P. Krane, A. L. Nash, et al., "Dynamic modeling and control of a two-reactor metal hydride energy storage system," in Applied Energy, Vol. 325, 2022.
  • A. L. Nash, H. C. Pangborn, N. Jain, "Robust Control Co-Design with Receding-Horizon MPC," 2021 American Control Conference (ACC), New Orleans, LA, USA, 2021.
  • A. L. Nash, N. Jain, "Hierarchical Control Co-Design Using a Model Fidelity-Based Decomposition Framework." in ASME. J. Mech. Des., Vol. 143(1), 2021.
  • A. L. Nash, N. Jain, "Combined Plant and Control Co-Design for Robust Disturbance Rejection in Thermal-Fluid Systems," in IEEE Transactions on Control Systems Technology, Vol. 28(6), 2020.

Research Experiences

  • Control Co-Design
  • Model Predictive Control
  • Thermal/Energy Management
  • Design Optimization

Teaching Interests

  • Control Systems
  • Dynamic Modeling
  • Optimization
  • Thermodynamics
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