Development of Robust Control Laws for Disturbance Rejection in Rotorcraft UAVs

Inherent stability inside the flight envelope must be guaranteed in order to safely introduce private and commercial UAV systems into the national airspace. The rejection of unknown external wind disturbances offers a challenging task due to the limited available information about the unpredictable and turbulent characteristics of the wind. This thesis focuses on the design, development and implementation of robust control algorithms for disturbance rejection in rotorcraft UAVs. The main focus is the rejection of external disturbances caused by wind influences. Four control algorithms are developed in an effort to mitigate wind effects: baseline nonlinear dynamic inversion (NLDI), a wind rejection extension for the NLDI, NLDI with adaptive artificial neural networks (ANN) augmentation, and NLDI with L1 adaptive control augmentation. A simulation environment is applied to evaluate the performance of these control algorithms under external wind conditions using a Monte Carlo analysis. Outdoor flight test results are presented for the implementation of the baseline NLDI, NLDI augmented with adaptive ANN and NLDI augmented with L1 adaptive control algorithms in a DJI F330 Flamewheel quadrotor UAV system. A set of metrics is applied to compare and evaluate the overall performance of the developed control algorithms under external wind disturbances. The obtained results show that the extended NLDI exhibits undesired characteristics while the augmentation of the baseline NLDI control law with adaptive ANN and L1 output-feedback adaptive control improve the robustness of the translational and rotational dynamics of a rotorcraft UAV in the presence of wind disturbances

Comparison of Adaptive Control Architectures for Flutter Suppression

A study is conducted to derive and implement a state feedback model reference adaptive control (MRAC) solutions for a 2-D aeroelastic nonlinear system and in evaluating the robustness of different control strategies to damage leading to the deterioration of the structural stiffness characteristics. The standard MRAC, a modified MRAC and the adaptive controller are the three model reference adaptive control solutions analyzed. The standard direct MRAC solution serves as the threshold to assess whether or not the more complex algorithms are an effective improvement to it

Implementation of adaptive nonlinear model predictive control on a PX4-enabled quad-rotor platform

This thesis aims at developing an adaptive and nonlinear model predictive control Simulink scheme and interfacing it with the popular PX4 drone system. PX4 is one of the most used drone \ac{RTOS} in the context of research, it has many safety and sensor management features, it is open source, and has an extensive and active community of developers making it an excellent platform for \ac{UAVs} control development. The advantages of interfacing it with Matlab/Simulink running on a companion computer are mainly twofold. The first is simplicity: the Simulink block scheme language is easy to use for complex control schemes, also supported by a great collection of libraries and by the baked-in management of PX4 of sensor data that can directly be used as feedback for the controls without additional estimators. The second is the possibility of moving the computational complexity away from the onboard embedded platform to a much more powerful ground station PC. \ac{NMPC} is an excellent example as it makes use of both, there are many implementations available that require only some setup and the model of the plant, it gives great control performance but is computationally expensive and therefore not always usable directly of low-end embedded hardware without some optimizations, which would require a competent and experienced user. Since model predictive control is susceptible to modeling errors that are especially common when dealing with low-cost drone platforms it is paired with a lightweight adaptive scheme that complements the control action to make up for modeling mismatches. The whole infrastructure is then validated through \ac{SITL} simulations across a variety of tasks and conditions, confirming that the interface between Matlab/Simulink works, the \ac{NMPC} scheme is usable in real-time with good trajectory tracking performance and that adaptive control provides a much greater degree of robustness to the system

ℒ1 adaptive control of quadrotor UAVs in case of inversion of the torque direction

This paper presents a method for fault tolerant control of quadrotor UAVs in case of inversion of the torque direction, a situation that might occur due to structural, hardware or software issues. The proposed design is based on multiple-model ℒ1 adaptive control. The controller is composed of a nominal reference model and a set of degraded reference models. The nominal model is that with desired dynamics that are optimal regarding some specific criteria. In a degraded model, the performance criteria are reduced. It is designed to ensure system robustness in the presence of critical failures. The controller is tested in simulations and it is shown that the multiple model ℒ1 adaptive controller stabilizes the system in case of inversion of the control input, while the ℒ1 adaptive controller with a single nominal model fails

Design of Flight Control Laws for a Novel Stratospheric Dual-Aircraft Platform

Dual-aircraft platform (DAP) is a novel concept that features two glider-like unmanned aerial systems (UAS) tethered via a thin adjustable cable allowing them to sail back-and-forth, without propulsion, using vertical wind shear. DAP offers the potential of a low-cost atmospheric satellite. This thesis presents the results of an initiative to demonstrate this novel flight concept through modeling, simulation, and flight testing at Embry-Riddle Aeronautical University (ERAU). A realistic simulation environment, described herein, was developed to support the development and testing of flight control systems. This environment includes nonlinear aerodynamic models for the aircraft, a multi-element cable dynamics model, propeller-motor thrust model, control surface actuator models, and permits time-varying wind profiles. This simulator offers both pilot-in-the-loop control and autonomous sailing flight control, and X-Plane interface to provide visualization cues. An intensive flight test program, described herein, was conducted to support the validation of the DAP concept. MAXA Pro 4m gliders were assembled, instrumented, and flight tested in an effort to physically demonstrate the sailing mode of flight. The flight test program described here focuses on the capability to sail with one aircraft (i.e., fly without propulsion) while towing (i.e., pulling) a moving truck as an intermediate step towards the more complex scenario of sailing with two connected aircraft. Two vital elements of the flight software are implemented and analyzed herein. The accuracy of wind estimation techniques is evaluated using flight testing. The robustness of an L1 adaptive controller is evaluated within the flight simulation environment by comparing its performance with a conventional controller

Learning-based Nonlinear MPC for Quadrotor Control

openThis work aims at investigate the application of different learning based techniques for the enhancement of the Nonlinear Model Predictive Control (NMPC) framework, in the context of trajectory control for a quadrotor unmanned aerial vehicle (UAV). In particular, a gaussian process regression technique and a neural network approach are both taken into account in order to improve the knowledge of the model that constitutes the basis of the effectiveness of the NMPC.This work aims at investigate the application of different learning based techniques for the enhancement of the Nonlinear Model Predictive Control (NMPC) framework, in the context of trajectory control for a quadrotor unmanned aerial vehicle (UAV). In particular, a gaussian process regression technique and a neural network approach are both taken into account in order to improve the knowledge of the model that constitutes the basis of the effectiveness of the NMPC

Control de vibraciones en estructuras flexibles mediante amortiguadores de masa pasivos, adaptativos, semiactivos y activos

Muchas de las estructuras que nos rodean y que en algunos casos usamos de manera habitual en nuestro discurrir diario son estructuras esbeltas. Ejemplos de estas, son estructuras civiles como puentes, pasarelas peatonales, rascacielos y chimeneas industriales, o estructuras metálicas como las grúas torre y las torres de aerogeneradores entre otras muchas. Una característica común en la mayoría de estas es que se mueven o vibran cuando están sometidas a cargas dinámicas bien de naturaleza medioambiental (viento, terremotos,…) o debidas al tráfico rodado y peatonal que circula por ellas. Cuando las propiedades modales de las estructuras están dentro del espectro de frecuencias de las cargas dinámicas y las estructuras entran en resonancia con dichas cargas, el nivel de vibraciones que experimentan las estructuras puede condicionar su uso y en un último caso su integridad. El objetivo de la tesis es el de aunar y dar una guion conductor a los estudios realizados de forma individual y en colaboración en los últimos años dentro de la temática de análisis y control de vibraciones en estructuras esbeltas principalmente civiles y más concretamente en pasarelas peatonales. La gran mayoría de los estudios han sido realizados en la Fundación CARTIF en colaboración con la UVA como parte de proyectos de investigación de convocatorias nacionales, así como estudios internos. El objetivo de dichos estudios fue el desarrollo e implementación de nuevas estrategias para el análisis de vibraciones, la estimación de los parámetros modales y el diseño e implementación de controles de vibración basados en amortiguadores de masa de naturaleza pasiva, adaptativa, semiactiva y activa.Departamento de Construcciones Arquitectónicas, Ingeniería del Terreno y Mecánica de los Medios Continuos y Teoría de EstructurasDoctorado en Ingeniería Industria