scholarly journals Design and Simulation of Eight-Rotor Unmanned Aerial Vehicle Based on Hybrid Control System

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xueqiang Shen ◽  
Jiwei Fan ◽  
Haiqing Wang
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Hybrid Control ◽  
Dynamic Performance ◽  
System Response ◽  
Hybrid Controller ◽  
Aerial Vehicle ◽  
Switching Method ◽  
Hybrid Control System

In order to control the position and attitude of unmanned aerial vehicle (UAV) better in different environments, this study proposed a hybrid control system with backstepping and PID method for eight-rotor UAV in different flight conditions and designed a switching method based on altitude and attitude angle of UAV. The switched process of hybrid controller while UAV taking off, landing, and disturbance under the gust is verified in MATLAB/Simulink. A set of appropriate controllers always matches to the flight of UAV in different circumstances, which can speed up the system response and reduce the steady-state error to improve stability. The simulation results show that the hybrid control system can suppress the drift efficiently under gusts, enhance the dynamic performance and stability of the system, and meet the position and attitude of flight control requirements.

scholarly journals HYBRID CONTROL SYSTEM IN BIONIC LEG USING MYOWARE SENSOR

2021 ◽  
Vol 56 (4) ◽  
pp. 104-116
Author(s):  
W. Widhiada ◽  
M.A. Parameswara ◽  
I.G.N.N. Santhiarsa ◽  
I.N. Budiarsa ◽  
I.M.G. Karohika ◽  
...  
Keyword(s):  
Control System ◽  
Steady State ◽  
Hybrid Control ◽  
Persons With Disabilities ◽  
Hybrid Controller ◽  
Innovation Product ◽  
Programming Software ◽  
Hybrid Control System ◽  
System Time ◽  
State Error

A bionic robot leg (BRL) is a contrivance used to supersede a loss component of the lower limb due to amputation or congenital disability. Hybrid control of BRL is opted to obtain the maximum performance of BRL equipped with precise forms of kineticism and expeditious response by truncating the error and maximum overshoot and reducing time settle. This research aims to create a BRL innovation product for persons with disabilities at the Bali Puspadi Foundation. The novelty of this BRL is the implementation of the algorithm as outlined in the hybrid control system in the Arduino support package. The BRL utilizes a MyoWare sensor and an Arduino Mega 2560 microcontroller equipped with Matlab/Simulink R2020a programming software. The sensor is utilized to read the angular movement of the DC motor between 0 - 60° degrees and vice versa, following the concept of the gate cycle. The results obtained from the hybrid control simulation are 0.0713% on maximum overshoot, 0.0415% on steady-state error, and 1.292s on system time settle. Furthermore, the results obtained from the hybrid controller experiment are 0.627% on maximum overshoot, 0.257% on steady-state error, and 0.8s on system time settle.

scholarly journals The Design of an Automatic Flight Control System and Dynamic Simulation for Fixed-Wing Unmanned Aerial Vehicle (UAV) using X-Plane and LabVIEW

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Nur Ezzyana Ameera Mazlan ◽  
◽  
Syariful Syafiq Shamsudin ◽  
Mohammad Fahmi Pairan ◽  
Mohd Fauzi Yaakub ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Pid Controller ◽  
Pole Placement ◽  
Flight Simulator ◽  
Flight Control System ◽  
Labview Software ◽  
Controller Gain ◽  
Aerial Vehicle

This research focuses on developing an automatic flight control system for a fixed-wing unmanned aerial vehicle (UAV) using a software-in-the-loop method in which the PID controller is implemented in National Instruments LabVIEW software and the flight dynamics of the fixed-wing UAV are simulated using the X-Plane flight simulator. The fixed-wing UAV model is created using the Plane Maker software and is based on existing geometry and propulsion data from the literature. Gain tuning for the PID controller is accomplished using the pole placement technique. In this approach, the controller gain can be calculated using the dynamic parameters in the transfer function model and the desired characteristic equation. The proposed controller designs' performance is validated using attitude, altitude, and velocity hold simulations. The results demonstrate that the technique can be an effective tool for researchers to validate their UAV control algorithms by utilising the realistic UAV or manned aircraft models available in the X-Plane flight simulator.

scholarly journals MODELLING OF THE UNMANNED AERIAL VEHICLES FLIGHT CONTROL SYSTEM

Aviation ◽  
2021 ◽  
Vol 25 (2) ◽  
pp. 79-85
Author(s):  
Mirosław Adamski
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Aerodynamic Drag ◽  
Unmanned Aircraft ◽  
Simulation Program ◽  
Flight Control System ◽  
Aerial Vehicles ◽  
Aerial Vehicle

The article is an independent work containing the author’s ingenious research methodology and the model of the control system of Unmanned Aerial Vehicles. Furthermore a unique and world first mathematical model of an Unmanned Aerial Vehicle was developed, as well as a simulation program which enabled to investigate the control system of any Unmanned Aerial Vehicles in the tilt duct pitch (altitude), bank (direction), deviation and velocity, depending upon the variable values of the steering coefficient, reinforcement coefficient and the derivative constant. The research program was written in the language of the C++ as the MFC class, on the MS Visual Studio 2010 platform. The main issue resolved in the article is the pioneering research of the process of control during manual and semi-automatic guidance of the Unmanned Aerial Vehicle, with a jet propulsion system to the coordinates of preset points of the flight route. Modelling of the flight control system takes into account: the logical network of operations of the simulation program, the pilot-operator model, the set motion and control deviations as well as the flight control laws. In addition, modeling of the control system takes into account the drive model, engine dynamics, engine thrust, the model of steering actuators and the model of external loads. In contrast, the external load model takes into account the external forces acting on the unmanned aircraft, including gravitational forces and moments, aerodynamic forces and moments, aerodynamic drag, aerodynamic lateral forces, aerodynamic lift forces, aerodynamic heeling moment, mechanism of local angle of attack from damping torque and forces and moments from the engine.

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