ORCID Number

0009-0005-9390-0060

Date of Award

Spring 2026

Access Type

Thesis - Open Access

Degree Name

Master of Science in Aerospace Engineering

Department

Aerospace Engineering

Committee Chair

Hever Moncayo

Committee Chair Email

moncayoh@erau.edu

Committee Advisor

Hever Moncayo

Committee Advisor Email

moncayoh@erau.edu

First Committee Member

Kadriye Merve Dogan

First Committee Member Email

dogank@erau.edu

Second Committee Member

Richard Prazenica

Second Committee Member Email

prazenir@erau.edu

College Dean

James W. Gregory

Abstract

Advanced Air Mobility (AAM) envisions highly automated aircraft that will enable short and medium range transportation. Unlike conventional aviation, these vehicles are expected to operate closer to populated areas and with increased levels of autonomy, making safe operation under abnormal or degraded conditions a critical requirement. Failures or performance degradation can reduce the maneuvering capability of an aircraft, causing trajectories planned under nominal conditions to become dynamically unfeasible.

This thesis presents a trajectory generation and replanning framework designed to maintain safe and feasible flight under reduced flight envelope conditions for a lift+cruise eVTOL aircraft. A unified control architecture based on incremental nonlinear dynamic inversion is implemented to support both pilot-in-the-loop and autonomous operation. Flight envelope limitations are incorporated directly into trajectory planning through motion primitives, allowing generation of dynamically feasible paths. Nominal trajectories are produced using an offline Fast Marching Tree (FMT*) planner, while real-time replanning is achieved using an adapted Real-Time FMT algorithm. For pilot-in-the-loop scenarios, an augmented reality interface is developed to provide intuitive spatial guidance to follow the generated safe trajectories.

The proposed framework is evaluated through different simulations under roll and pitch envelope limitations. Performance is determined by computing control effort, tracking accuracy, and a global performance index, defined as a weighted combination of normalized tracking error and control effort. Results show that the replanned trajectories prevent collisions, reduce control effort, and improve tracking performance compared to nominal trajectories executed under degraded conditions. Additionally, replanned trajectories show consistent performance when executed under both healthy and degraded conditions, demonstrating robustness to a reduced maneuverability.

The results highlight the importance of adapting vehicle motion to available maneuvering capability rather than relying only on fault-tolerant control. By integrating planning that accounts for the flight envelope, real-time replanning, and human-centered guidance, this work contributes toward safer and more reliable operation of future AAM vehicles.

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