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Full-Text Articles in Mechanical Engineering
A Reinforcement Learning Approach To Spacecraft Trajectory Optimization, Daniel S. Kolosa
A Reinforcement Learning Approach To Spacecraft Trajectory Optimization, Daniel S. Kolosa
Dissertations
This dissertation explores a novel method of solving low-thrust spacecraft targeting problems using reinforcement learning. A reinforcement learning algorithm based on Deep Deterministic Policy Gradients was developed to solve low-thrust trajectory optimization problems. The algorithm consists of two neural networks, an actor network and a critic network. The actor approximates a thrust magnitude given the current spacecraft state expressed as a set of orbital elements. The critic network evaluates the action taken by the actor based on the state and action taken. Three different types of trajectory problems were solved, a generalized orbit change maneuver, a semimajor axis change maneuver, …
Optimization Methodology For Cvt Ratio Scheduling With Consideration Of Both Engine And Cvt Efficiency, Steven Beuerle
Optimization Methodology For Cvt Ratio Scheduling With Consideration Of Both Engine And Cvt Efficiency, Steven Beuerle
Masters Theses
A transmission ratio schedule is developed to optimize the fuel consumption for an automotive continuously variable transmission (CVT) connected to an internal combustion engine (ICE). Although the optimal operating line (OOL) generated from an engine brake specific fuel consumption (BSFC) map can be used to generate a CVT ratio schedule that yields maximum engine efficiency, it was found that OOL-based CVT ratio scheduling does not necessarily offer the best fuel economy because optimal CVT efficiency does not always correspond to OOL tracking. To develop a CVT ratio schedule that can offer the best fuel economy, a novel ratio-scheduling methodology is …
A Genetic Algorithm Incorporating Design Choice For The Preliminary Design Of Unmanned Aerial Vehicles, Kenneth Michael Mull
A Genetic Algorithm Incorporating Design Choice For The Preliminary Design Of Unmanned Aerial Vehicles, Kenneth Michael Mull
Masters Theses
Unmanned Aerial Vehicles (UAVs) are currently at the forefront of aerospace technologies. The design of these aircraft is complex and often performance characteristics are coupled to multiple design attributes. At the early design phase both discrete and continuous design choices are present limiting the feasibility of traditional derivative based optimization techniques. In place of these methods, the design space can be explored using a genetic algorithm that mimics the process of natural selection, providing a capable and reliable base airframe constructed from the required performance metrics. By incorporating a genetic multidisciplinary optimization algorithm early in the conceptual design phase, aircraft …