scholarly journals Robust Hybrid Control Algorithm for Tuning the Altitude and Attitude of Unmanned Aerial Vehicle

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Bohang Wang ◽  
Daobo Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Hybrid Control ◽  
Pole Placement ◽  
Robust Controller ◽  
State Behavior ◽  
Nonlinear Parameters ◽  
Six Degrees Of Freedom ◽  
Aerial Vehicle

In this article, a new and novel robust hybrid control algorithm is designed for tuning the parameters of unmanned aerial vehicle (UAV). The quadrotor type UAV mathematical model is taken to observe the effectiveness of our designed robust hybrid control algorithm. The robust hybrid control algorithm consists of H∞ based regulation, pole-placement and tracking (RST) controller along with mixed sensitivity function is applied to control the complete model of UAV. The selected rotor craft is under-actuated, nonlinear and multivariable behavior in nature along with six degrees of freedom (DOF). Due to all these aforementioned issues its stabilization is quite difficult as compared to fully actuated systems. For the tuning of nonlinear parameters of the UAV, we designed, robust hybrid control algorithm is used. Moreover, the performance of the designed controller is compared with robust controller. The validity and effectiveness of the designed controllers are simulated in MATLAB and Simulink, in which the designed controller shows better steady state behavior, robustness and converges quickly in specific amount of time as compared to robust controller.

Modeling and Controlling the Dynamic Behavior of an Aerial Manipulator

2021 ◽  
pp. 2150044
Author(s):  
Zain Anwar Ali ◽  
Li Xinde
Keyword(s):  
Dynamic Behavior ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Control Mechanism ◽  
Hybrid Control ◽  
External Noise ◽  
Pole Placement ◽  
Aerial Manipulator ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

Unmanned Aerial Vehicles (UAVs) installed with a gripper is an effective and robust way to grab the wanted object from inaccessible locations. In this study, we develop a novel control mechanism to regulate the nonlinear dynamics of the aerial manipulator. In this research, hex-rotor UAV is chosen in order to fulfill the mission requirement in terms of size and weight of the object. It is equipped with a manipulator and the gimbal-based camera that will help to see the desired object and then transport it. The aerial vehicle has six-degrees-of-freedom (6-DOF) and the installed manipulator has 4-DOF which in total makes the 10-DOF aerial manipulator vehicle. At the time of clutching the desired object to eliminate or reduce the external noise, and stabilize the dynamic behavior of the aerial manipulator, we need a robust and efficient controller. To solve the aforementioned problems, this study develops a hybrid control mechanism that tracks and controls the altitude and attitude of UAV after clutching the desired object. The main contribution of this study is to design a control mechanism that includes Model Reference Adaptive Control with an Integrator (MRACI) in conjunction with regulation, pole-placement and tracking (RST) control algorithm. On one hand, the simulation results using MATLAB demonstrate the efficiency of the proposed control mechanism. On the other hand, to cross verify the validity of the proposed control algorithm, we perform the experiment by clutching the desired object at hovering and normal flight operation.

Design and Experimental Results of a Quad-Rotor Control System

2013 ◽  
Vol 284-287 ◽  
pp. 1799-1805
Author(s):  
Tae Sam Kang ◽  
Gi Gun Lee ◽  
Jung Hwan Kim
Keyword(s):  
Nonlinear Dynamics ◽  
Control System ◽  
Linear Model ◽  
Attitude Control ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Six Degrees Of Freedom ◽  
Aerial Vehicle ◽  
Attitude Controller ◽  
Rotor Control

Multi-rotor is one of the emerging Unmanned Aerial Vehicle platforms. This paper covers the design, fabrication, modeling and testing of a quad-rotor control system. To take into account the salient nonlinearities, a model with six degrees of freedom nonlinear dynamics and some linear approximation of the aerodynamic part are used when extracting a linear model and designing a attitude controller. We obtained a linear model from experimental data using system identification method and developed attitude control algorithm. The control algorithm was realized using an on a board microprocessor and verified through experiment in real environment.

scholarly journals Attitude and Altitude Control of Trirotor UAV by Using Adaptive Hybrid Controller

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Zain Anwar Ali ◽  
Daobo Wang ◽  
Suhaib Masroor ◽  
M. Shafiq Loya
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Kinematic Model ◽  
Nonlinear Behavior ◽  
Pole Placement ◽  
Hybrid Scheme ◽  
Hybrid Controller ◽  
Aerial Vehicle ◽  
6 Degrees Of Freedom

The paper presents an adaptive hybrid scheme which is based on fuzzy regulation, pole-placement, and tracking (RST) control algorithm for controlling the attitude and altitude of trirotor UAV. The dynamic and kinematic model of Unmanned Aerial Vehicle (UAV) is unstable and nonlinear in nature with 6 degrees of freedom (DOF); that is why the stabilization of aerial vehicle is a difficult task. To stabilize the nonlinear behavior of our UAV, an adaptive hybrid controller algorithm is used, in which RST controller tuning is performed by adaptive gains of fuzzy logic controller. Simulated results show that fuzzy based RST controller gives better robustness as compared to the classical RST controller.

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.

Autopilot design for tilt-rotor unmanned aerial vehicle with nacelle mounted wing extension using single hidden layer perceptron neural network

2016 ◽  
Vol 231 (11) ◽  
pp. 1979-1992 ◽  
Author(s):  
Youngshin Kang ◽  
Nakwan Kim ◽  
Byoung-Soo Kim ◽  
Min-Jea Tahk
Keyword(s):  
Neural Network ◽  
Unmanned Aerial Vehicle ◽  
Lyapunov Equation ◽  
Pole Placement ◽  
Dynamic Inversion ◽  
North West ◽  
Tilt Rotor ◽  
Neural Network Controller ◽  
Aerial Vehicle ◽  
Hidden Layer

Single hidden layer perceptron neural network controllers combined with dynamic inversion are applied to the tilt-rotor unmanned aerial vehicle and its variant model with the nacelle mounted wing extension. The bandwidths of the inner loop and outer loop of the controller are designed using the timescale separation approach, which uses the combined analysis of the two loops. The bandwidth of each loop is selected to be close to each other using a combination of the pseudo-control-hedging and the pole-placement method. Similar to the previous studies on sigma-pi neural network, the dynamic inversion at hover conditions of the original tilt-rotor model is used as a baseline for both aircraft, and the compatible solution to the Lyapunov equation is suggested. The single hidden layer perceptron neural network minimizes the error of the inversion model through the back-propagation adaptation. The waypoint guidance is applied to the outermost loop of the neural network controller for autonomous flight which includes vertical take-off and landing as well as nacelle conversion. The simulation results under the two wind conditions for the tilt-rotor aircraft and its variant are presented. The south and north-west wind directions are simulated in order to compare with the results from the existing sigma-pi neural network, and the estimation results of the wind are presented.

A Dual-Stage Planar Cable Robot: Dynamic Modeling and Design of A Robust Controller with Positive Inputs

2004 ◽  
Vol 127 (4) ◽  
pp. 612-620 ◽  
Author(s):  
So-Ryeok Oh ◽  
Kalyan Mankala ◽  
Sunil K. Agrawal ◽  
James S. Albus
Keyword(s):  
Degrees Of Freedom ◽  
Robust Controller ◽  
Two Stage ◽  
End Effector ◽  
Six Degrees Of Freedom ◽  
Cable Robot ◽  
Unknown Disturbances ◽  
Dual Stage ◽  
Loading And Unloading ◽  
Skin To Skin

Cable robots have potential usage for loading and unloading of cargo in shipping industries. A novel six-degrees-of-freedom two-stage cable robot has been proposed by NIST for skin-to-skin transfer of cargo. In this paper, we look at a planar version of this two-stage cable robot. The disturbance motion from the sea is considered while modeling the dynamics of robot. The problem of robust control of the end-effector in the presence of unknown disturbances, along with maintaining positive tensions in the cables, is tackled using redundancy of cables in the system. Simulation results show the effectiveness of the control strategy.

Dynamic Modeling for a Miniature Six-Rotor Unmanned Aerial Vehicle

2013 ◽  
Vol 321-324 ◽  
pp. 819-823 ◽  
Author(s):  
Qi Dong Ma ◽  
Zhen Guo Sun ◽  
Jing Ran Wu ◽  
Wen Zeng Zhang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Driving Force ◽  
Pid Controller ◽  
Control Algorithm ◽  
Driving Forces ◽  
Euler Angles ◽  
Unstable System ◽  
Nonlinear Dynamic Model ◽  
Aerial Vehicle ◽  
Simulation Results

A nonlinear dynamic model of a miniature Six-Rotor is presented. A 4 channels PID controller is designed to operate the under actuated and dynamically unstable system with 6 inputs. Driving forces of 6 rotors are divided into four components such as throttle, roll, pitch and yaw. The control algorithm is simulated with Design Optimization Toolbox in Matlab. After observing the corresponding responses of Euler angles, the altitude and the driving force for each motor, the simulation results show good performance.

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