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.

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.

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 An adaptive hierarchical control for aerial manipulators

Robotica ◽  
2018 ◽  
Vol 36 (10) ◽  
pp. 1527-1550 ◽  
Author(s):  
Francesco Pierri ◽  
Giuseppe Muscio ◽  
Fabrizio Caccavale
Keyword(s):  
Control Algorithm ◽  
Hierarchical Control ◽  
Bottom Layer ◽  
Trajectory Tracking Control ◽  
Aerial Manipulator ◽  
Control Scheme ◽  
Modelling Uncertainties ◽  
Aerial Vehicle ◽  
The Stability

SUMMARYThis paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.

PD Controller With Self Adaptive Gains for Quadrotor Waypoint Navigation

2020 ◽  
Author(s):  
Madhavan Sudakar ◽  
Siddharth Sridhar ◽  
Manish Kumar
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Simple Structure ◽  
Reference Model ◽  
Pd Controller ◽  
Lyapunov Stability Analysis ◽  
Waypoint Navigation ◽  
Novel Method ◽  
Model Reference Adaptive ◽  
Random Gain

Abstract Proportional-Derivative (PD) controllers are commonly used in quadrotors due to their simple structure. Tuning of the gains of the PD controller is often cumbersome due to strong coupling of the dynamics between three linear and three angular degrees of freedom. This paper presents a novel method of auto adjusting the proportional and derivative gains of the quadrotor without the use of any stable reference model (unlike model reference adaptive control). The gains are automatically adjusted throughout the flight based on just the state errors. Lyapunov stability analysis and adaptive gain law is used to formulate the control algorithm to achieve way point navigation. It is shown that our proposed controller achieves effective way point navigation even when started off from random gain values.

Hybrid intelligent adaptive controller for tiltrotor UAV

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jafar Tavoosi
Keyword(s):  
Neural Network ◽  
Position Control ◽  
Control Method ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Content Type ◽  
Flight Mode ◽  
Horizontal Flight ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

PurposeIn this paper, an innovative hybrid intelligent position control method for vertical take-off and landing (VTOL) tiltrotor unmanned aerial vehicle (UAV) is proposed. So the more accurate the reference position signals tracking, the proposed control system will be better.Design/methodology/approachIn the proposed method, for the vertical flight mode, first the model reference adaptive controller (MRAC) operates and for the horizontal flight, the model predictive control (MPC) will operate. Since the linear model is used for both of these controllers and naturally has an error compared to the real nonlinear model, a neural network is used to compensate for them. So the main novelties of this paper are a new hybrid control design (MRAC & MPC) and a neural network-based compensator for tiltrotor UAV.FindingsThe proper performance of the proposed control method in the simulation results is clear. Also the results showed that the role of compensator is very important and necessary, especially in extreme speed wind conditions and uncertain parameters.Originality/valueNovel hybrid control method. 10;-New method to use neural network as compensator in an UAV.

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 Modeling and controlling of quadrotor aerial vehicle equipped with a gripper

2019 ◽  
Vol 52 (5-6) ◽  
pp. 577-587 ◽  
Author(s):  
Zain Anwar Ali ◽  
Xinde Li
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicle ◽  
Degrees Of Freedom ◽  
Control Structure ◽  
Arm Movement ◽  
Transient Behavior ◽  
Model Reference Adaptive Control ◽  
Model Reference ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

Arm mounted unmanned aerial vehicles provide more feasible and attractive solution to manipulate objects in remote areas where access to arm mounted ground vehicles is not possible. In this research, an under-actuated quadrotor unmanned aerial vehicle model equipped with gripper is utilized to grab objects from inaccessible locations. A dual control structure is proposed for controlling and stabilization of the moving unmanned aerial vehicle along with the motions of the gripper. The control structure consists of model reference adaptive control augmented with an optimal baseline controller. Although model reference adaptive control deals with the uncertainties as well as attitude controlling of unmanned aerial vehicle, baseline controller is utilized to control the gripper, remove unwanted constant errors and disturbances during arm movement. The proposed control structure is applied in 6-degree-of-freedom nonlinear model of a quadrotor unmanned aerial vehicle equipped with gripper having (2 degrees of freedom) robotic limb; it is applicable for the simulations to desired path of unmanned aerial vehicle and to grasp object. Moreover, the efficiency of the presented control structure is compared with optimal baseline controller. It is observed that the proposed control algorithm has good transient behavior, better robustness in the presence of continuous uncertainties and gripper movement involved in the model of unmanned aerial vehicle.

Adaptive Hybrid Control Algorithm With Iterative Learning for Robotic In Vitro Biomechanical Testing of Spine

2012 ◽  
Author(s):  
T. F. Bonner ◽  
L. Gilbertson ◽  
R. W. Colbrunn
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Hybrid Control ◽  
Dynamic Testing ◽  
Biomechanical Testing ◽  
Testing Methods ◽  
Robotic Technology ◽  
Control Schemes ◽  
Pure Moment

In spine testing, methods have been developed to apply pure moments to a single axis of the spine to elucidate the mechanical properties of the spine. The application of those concepts continues to be applied with custom loading frames, custom robotics systems, and adaptation of commercial robotic technology. With these systems and pure moment testing, spinal biomechanics variables such as the neutral zone and range of motion can be determined. As more complex testing systems with higher degrees of freedom (DOF) capabilities are developed, dynamic testing becomes a possibility. However, these more complex testing systems require more complex control schemes.

Design of a Control System for Serial Mechanisms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Control System ◽  
Dynamic Equation ◽  
Degrees Of Freedom ◽  
Nonlinear Term ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Hybrid Controller ◽  
Speed Performance ◽  
Convergence Performance ◽  
Model Reference Adaptive

A hybrid control system for multi degrees of freedom robotic manipulator is designed by integrating a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. For the 1-DOF link, because the inertia matrices and nonlinear term of the dynamic equation are constant, we can directly combine the PID and MRAC controller to design the PID+MRAC controller. However, for the more than 1-DOF link case, it is no longer applicable because the inertia matrices and nonlinear term of the dynamic equation are not constant. By using an improved adaptive algorithm and structure, and by combining the PID and improved MRAC controllers, a controller is designed for the more than 1-DOF link case. The convergence performance of the PID controller, MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators are compared.

scholarly journals Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm

Aerospace ◽  
2017 ◽  
Vol 4 (1) ◽  
pp. 3 ◽  
Author(s):  
Zain Ali ◽  
Daobo Wang ◽  
Muhammad Aamir ◽  
Suhaib Masroor
Keyword(s):  
Trajectory Tracking ◽  
Control Algorithm ◽  
Hybrid Control ◽  
Aerial Vehicle
Sign in / Sign up

Export Citation Format

Share Document