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Full-Text Articles in Engineering
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Student Works
The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …
Optimal Sizing And Control Of Hybrid Rocket Vehicles, Srija Ryakam
Optimal Sizing And Control Of Hybrid Rocket Vehicles, Srija Ryakam
Doctoral Dissertations and Master's Theses
In the present work, a genetic algorithm is used to optimize a hybrid rocket engine in order to minimize the propellant required for a specific mission. In a hybrid rocket engine, the mass flow rate of the oxidizer can be throttled to enhance the performance of the rocket. First, an analysis of the internal ballistics and the ascent trajectory has been carried out for different mass flow rates of the oxidizer as a function of time, for a fixed amount of oxidizer, in order to study the effect of throttling. Two equivalent problems are considered: in the first problem the …