Mitigating Flight Performance Errors in UAVs through Hybrid MRAC controller

This research explores modelling, design, and control of quadcopters, focusing on mitigating flight performance errors that compensate the performance of Unmanned Aerial Vehicles (UAVs) performance. It also explores a mathematical model for simulation and a control of rotary-wing UAV systems. Moreover, it describes a design methodology for a micro-sized UAV in CAD software. Adaptive control techniques are then used to design four sub-controllers of UAVs named Altitude Control, Roll, Pitch, and Yaw. It is basically a remodeling of classical Model Reference Adaptive Control (MRAC) scheme, which is named Hybrid MRAC, ensuring a better rise time performance than classical MRAC. The controllers are then analyzed in the presence of disturbances to prove that adaptive controllers are more robust to external disturbances than non-adaptive ones. Lastly for state estimation, an Extended Kalman Filter (EKF) is applied to account for real-world sensor noises that further degrade the performance of UAV

I. Introduction

An Unmanned Aerial Vehicle (UAV) can be described as an aircraft that is without any human pilot (autopilot) mode. A quadrotor is a type of UAV that is characterized by its four rotors. The quadrotor control design is a very famous field of research, and it is used for security, search and rescue purposes, aerial photography/videography, food delivery, surveillance, agriculture, remote sensing, and many other fields. To design a stable quadcopter system, we need to follow some physics, mathematics, and aerodynamics. Drone movement and its inertial motion can be defined through aerodynamics. The mathematical calculation, on the other hand, aids in manipulating the required lift, motion, angular position, force, and trajectory definition. The body of the drone is designed such that it follows its dynamics, and artificial algorithms are applied to make it well-behaved and autonomous. Hardwire system consist of various sensors, electronic equipment, powerful controller unit and so on. The most important feature of UAV systems is the control system, which consists of various algorithms and microprocessors that receive information from sensors and drone's output states to make decisions accordingly.