A quadcopter is a rotorcraft with a simple mechanical construction. It has the same hovering capability similar to the traditional helicopter, but it is easier to maintain. The quadcopter is hard to control due to its unstable system with highly coupled and non-linear dynamics. In order to design a robust control algorithm, it is crucial to obtain a precise quadrotor flight dynamics through system identification approach. System identification is a method of finding the mathematical model of the dynamics system using the input-output data measurement. Neural network (NN) based system identification is excellent alternative modeling because it reduces development costs and time by avoiding governing equations and large aerodynamic database. NN based system identification has successfully identified the quadcopter dynamics with good accuracy. This paper gives an overview of the characteristic of the quadcopter and presents a comprehensive survey of the modeling techniques used to determine the flight dynamics of a quadrotor with a particular focus on NN based system identification method. The presented research works have been classified into different categories such as the first principle modeling, system identification and implementation of NN based system identification in quadcopter platform. Finally, the paper highlights challenges that need to be addressed in developing efficient NN based system identification model for unmanned quadcopter system.
A quadcopter is a rotorcraft with a simple mechanical construction. It has the same hovering capability similar to the traditional helicopter, but it is easier to maintain. The quadcopter is hard to control due to its unstable system with highly coupled and non-linear dynamics. In order to design a robust control algorithm, it is crucial to obtain a precise quadrotor flight dynamics through system identification approach. System identification is a method of finding the mathematical model of the dynamics system using the input-output data measurement. Neural network (NN) based system identification is excellent alternative modeling because it reduces development costs and time by avoiding governing equations and large aerodynamic database. NN based system identification has successfully identified the quadcopter dynamics with good accuracy. This paper gives an overview of the characteristic of the quadcopter and presents a comprehensive survey of the modeling techniques used to determine the flight dynamics of a quadrotor with a particular focus on NN based system identification method. The presented research works have been classified into different categories such as the first principle modeling, system identification and implementation of NN based system identification in quadcopter platform. Finally, the paper highlights challenges that need to be addressed in developing efficient NN based system identification model for unmanned quadcopter system.
The present work presents a comparative study on the longitudinal dynamic’s stability behavior for two aircraft models, namely the Learjet 24 and the Cessna 182. The longitudinal flight dynamics behaviors are evaluated by introducing a disturbance to the elevator. This device uses a single doublet impulse as well as multiple doublet impulses. The governing equation of longitudinal flight motion, which was derived based on a small perturbation theory and a linearized process by dropping the second order and above to the disturbance quantities, allowed one to formulate the governing equation of flight motion in the form of an equation known as the longitudinal equation of flight motion. This equation describes the flight behavior of an aircraft and can be expressed in the disturbance quantity as translational velocity in the x-direction u, angle of attack 𝛼, and pitch angle 𝜃. The implementation in the case of the Cessna 182 and the Learjet 24, where the Cessna 182 uses a single doublet impulse or a multiple doublet impulse, demonstrates that the aircraft response in these three variable states is better than that of the Learjet 24.
A number of companies are experimenting with multicopter drones to deliver items to clients. Because electric planes have a restricted range, their flight range is usually limited. However, if propelled by gasoline, electric multicopter drones can only travel a short distance because of high power consumption and noise difficulties. Despite their lower aerodynamic efficiency than fixed-wing aircraft, multicopters' ability to perform vertical take-off and landing (VTOL) makes them an ideal delivery vehicles. A hybrid fixed-wing VTOL system with a tilting system that alters the flight mode could be an upgradeto the current design of hybrid fixed wing VTOL. The goal is to effectively manufacture a fixed-wing drone with an appropriate structural design and a functional tilting mechanism that can take off vertically. SolidWorks and SIMNET aero were the two approaches used throughout the design software. The drone's aerodynamic qualities were investigated in order to better understand its behaviour, such as range of flight at a given altitude, stall speed, and maximum lift created, in order to determine the maximum parcel weight the drone can carry. The drone was built using SolidWorks 3D-Solid modelling and SIMNET aero design software. The tilting mechanism is 3D printed with Polylactic Acid (PLA) material since it is both light and strong. The structural strength can also be altered by changing the in-fill. After the drone was manufactured,numerous test flights were made to examine the drone's actual behaviour and enhance its functionality. The drone's theoretical stall speed was determined to be 12.74 m/s with a maximum payload of 500g and 11.43 m/s at no load. The maximum glide distance was estimated to be 1.2 kilometres. The drone yaws to the left during test flights at a rate of 63.43 degrees per second and 4.879 degrees per second at 50% throttle. It slanted to the front, nose down, with a weight of 516 g while support was given at the tip of the left wing. The pitch rate was 2.5 degrees per second without a payload and 3.12 degrees per second with the 516g payload. With further design and calibration advancements, experimental findings that are comparable to theoretical outcomes might be possible.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.