Linear Control of Unmanned Aerial Vehicles

This dissertation presents a comprehensive workflow for the modeling, identification, and control of quadrotor unmanned aerial vehicles (UAVs) operating in windy conditions, covering the complete process from raw data-driven model development to advanced control design and experimental validation. The study begins by introducing a control-oriented system identification methodology aimed at achieving model-based multirotor flight control without the reliance on pre-existing analytical models. The Optimized Predictor-Based Subspace Identification (PBSIDopt) approach is employed on experimental flight data to capture both in-plane and vertical dynamics. The identified models are subsequently utilized to construct a cascade control architecture featuring a PID inner loop and a proportional outer loop. Frequency-domain analysis informs the tuning process to ensure precise trajectory tracking while maintaining robustness, effectively demonstrating the application of identified models in controller design. To address real-world environmental effects, a data-driven wind modeling and estimation framework was developed. Flight data collected under various conditions were converted into equivalent wind forces and velocities, characterized using an ARMAX structure. This data was then employed to synthesize artificial winds for realistic simulations and validation. Building on this framework, Linear Active Disturbance Rejection Control (LADRC) and Generalized Active Disturbance Rejection Control (GADRC) were developed for the regulation of angular rates. While LADRC highlights the typical trade-offs between bandwidth and robustness, GADRC leverages the experimentally identified model to enhance sensitivity shaping. In simulation scenarios, GADRC outperformed both LADRC and PID controllers. However, due to concerns regarding model sensitivity, GADRC was not deployed in flight tests. Instead, LADRC was compared to PID in real wind experiments, demonstrating superior performance. The overall contribution of this work is a cohesive framework that links data-driven modeling, disturbance estimation, and robust control synthesis, providing practical guidance for achieving resilient multirotor flight in windy conditions.

Name thesis:degree_name

Doctor of Philosophy

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Houston

Year dc:date.issued

2025

Author dc:creator

• Wi, Yejin 1995-

Advisor dc:contributor.advisor

• Cescon, Marzia

Committee members dc:contributor.committeemember

• Hoskere, Vedhus
• Grigoriadis, Karolos
• Franchek, Matthew A.
• Chen, Zheng

• Disturbance Rejection Control
• Closed-Loop System Identification
• Unmanned Aerial Vehicles
• Control Systems
• PID Control
• Wind Disturbance Modeling
• Quadrotor

Language dc:language.iso

English

Handle dc:identifier.uri

https://hdl.handle.net/10657/20948

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/20948