Autonomous Autorotation of a Tilt-Rotor Aircraft Using Model Predictive Control

<p>Tilt rotor vehicles are governed by FAA laws also used for conventional helicopters, which require autorotational maneuvering and landing given a total power failure. With low inertia rotors and high disk loading of tilt rotor vehicles, this already difficult task becomes significantly more challenging. In this work, a model predictive controller is developed to autonomously maneuver and land a tilt rotor given complete power loss. A high fidelity model of a tilt rotor vehicle is created and used to simulate the vehicle dynamics and response to control inputs. A reduced order dynamic model is used within a model predictive control algorithm to predict vehicle states on a receding horizon and optimize the control inputs. Constraint and cost functions are designed to promote reliable nonlinear optimization using a recurrent neural network. Simulation results show that the controller works in both normal operation states and in power-off autorotation.</p>

Name thesis:degree_name

Master of Science in Aerospace Engineering

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Aerospace Engineering

Year

2019

Author dc:creator

• Wilson, Elias

• autorotation
• tilt-rotor
• model predictive control
• Aerospace Engineering
• Navigation, Guidance, Control and Dynamics

Repository record dc:identifier

https://commons.erau.edu/edt/495

OAI identifier oai:identifier

oai:commons.erau.edu:edt-1495