Studies on Model-Following Control for a class of nonlinear MIMO systems using a quadrotor system as an example

• Autor: Luna Rimayhuamán, Alberto Pablo
• Formato: tesis de maestría
• Fecha de Publicación: 2025
• Institución: Pontificia Universidad Católica del Perú
• Repositorio: PUCP-Tesis
• Lenguaje: inglés
• OAI Identifier: oai:tesis.pucp.edu.pe:20.500.12404/32057
• Enlace del recurso: http://hdl.handle.net/20.500.12404/32057
• Nivel de acceso: acceso abierto
• Materia: Control automático; Vehículos aéreos no tripulados; https://purl.org/pe-repo/ocde/ford#2.02.03

This master thesis is dedicated to the design and simulation of a model following controller for a quadrotor underactuated system. First, the quadrotor is modeled as a nonlinear Multi-Input Multi-Output (MIMO) system in affine form with four inputs (torques and thrust) and for outputs (three axis position and yaw angle). This was made by kinematics and Newton-Euler dynamics formulation. For the design, the model following control is composed by a Model Control Loop (MCL) where an idealized nominal plant model is considered. In this stage the special case of dynamic extension for MIMO systems is considered to obtain the decoupling matrix nonsingular and achieve full relative degree, then the augmented system is transformed in a Byrnes-Isidori-form so feedback linearization technique with state feedback gain can be applied for a reference trajectory. Hence, a second controller that operates on the real plant is designed. This is called a Process Control Loop (PCL). The nonlinear system is considered with external disturbances and is modeled based on the error dynamics between the process output and the nominal model output. The control is designed applying feedback linearization with high-gain state feedback with bounded uncertainty for the robustness. The obtained control law is feedforwarded by the control input of the MCL to make the outputs of the process follow the outputs of the MCL. The control system was compared with a single-loop state feedback pole placement design. The simulations demonstrated the stability under uncertainties and better trajectory tracking.