scholarly journals Development, Modeling and Control of a Dual Tilt-Wing UAV in Vertical Flight

Drones ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 71
Author(s):  
Luz M. Sanchez-Rivera ◽  
Rogelio Lozano ◽  
Alfredo Arias-Montano
Keyword(s):  
Dynamic Model ◽  
Attitude Control ◽  
Test Bench ◽  
Aerodynamic Coefficients ◽  
Nonlinear Dynamic Model ◽  
Modeling And Control ◽  
Drag And Lift ◽  
And Control ◽  
Dynamics Method ◽  
Indoor And Outdoor

Hybrid Unmanned Aerial Vehicles (H-UAVs) are currently a very interesting field of research in the modern scientific community due to their ability to perform Vertical Take-Off and Landing (VTOL) and Conventional Take-Off and Landing (CTOL). This paper focuses on the Dual Tilt-wing UAV, a vehicle capable of performing both flight modes (VTOL and CTOL). The UAV complete dynamic model is obtained using the Newton–Euler formulation, which includes aerodynamic effects, as the drag and lift forces of the wings, which are a function of airstream generated by the rotors, the cruise speed, tilt-wing angle and angle of attack. The airstream velocity generated by the rotors is studied in a test bench. The projected area on the UAV wing that is affected by the airstream generated by the rotors is specified and 3D aerodynamic analysis is performed for this region. In addition, aerodynamic coefficients of the UAV in VTOL mode are calculated by using Computational Fluid Dynamics method (CFD) and are embedded into the nonlinear dynamic model. To validate the complete dynamic model, PD controllers are adopted for altitude and attitude control of the vehicle in VTOL mode, the controllers are simulated and implemented in the vehicle for indoor and outdoor flight experiments.

scholarly journals Modeling and Control of a Six Degrees of Freedom Maglev Vibration Isolation System

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3608 ◽  
Author(s):  
Qianqian Wu ◽  
Ning Cui ◽  
Sifang Zhao ◽  
Hongbo Zhang ◽  
Bilong Liu
Keyword(s):  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Degrees Of Freedom ◽  
Vibration Isolation ◽  
Nonlinear Dynamic Model ◽  
Isolation System ◽  
Vibration Isolation System ◽  
Modeling And Control ◽  
And Control ◽  
Isolation Performance

The environment in space provides favorable conditions for space missions. However, low frequency vibration poses a great challenge to high sensitivity equipment, resulting in performance degradation of sensitive systems. Due to the ever-increasing requirements to protect sensitive payloads, there is a pressing need for micro-vibration suppression. This paper deals with the modeling and control of a maglev vibration isolation system. A high-precision nonlinear dynamic model with six degrees of freedom was derived, which contains the mathematical model of Lorentz actuators and umbilical cables. Regarding the system performance, a double closed-loop control strategy was proposed, and a sliding mode control algorithm was adopted to improve the vibration isolation performance. A simulation program of the system was developed in a MATLAB environment. A vibration isolation performance in the frequency range of 0.01–100 Hz and a tracking performance below 0.01 Hz were obtained. In order to verify the nonlinear dynamic model and the isolation performance, a principle prototype of the maglev isolation system equipped with accelerometers and position sensors was developed for the experiments. By comparing the simulation results and the experiment results, the nonlinear dynamic model of the maglev vibration isolation system was verified and the control strategy of the system was proved to be highly effective.

Modeling and control of a mobile manipulator

Robotica ◽  
1998 ◽  
Vol 16 (6) ◽  
pp. 607-613 ◽  
Author(s):  
J. H. Chung ◽  
S. A. Velinsky
Keyword(s):  
Dynamic Model ◽  
Control Method ◽  
Harmful Effect ◽  
Euler Method ◽  
Friction Model ◽  
Mobile Manipulator ◽  
Wheel Slip ◽  
Modeling And Control ◽  
Control Approach ◽  
And Control

This paper concerns the modeling and control of a mobile manipulator which consists of a robotic arm mounted upon a mobile platform. The equations of motion are derived using the Lagrange-d'Alembert formulation for the nonholonomic model of the mobile manipulator. The dynamic model which considers slip of the platform's tires is developed using the Newton-Euler method and incorporates Dugoff's tire friction model. Then, the tracking problem is investigated by using a well known nonlinear control method for the nonholonomic model. The adverse effect of the wheel slip on the tracking of commanded motion is discussed in the simulation. For the dynamic model, a variable structure control approach is employed to minimize the harmful effect of the wheel slip on the tracking performance. The simulation results demonstrate the effectiveness of the proposed control algorithm.

scholarly journals Kane Method Based Dynamics Modeling and Control Study for Space Manipulator Capturing a Space Target

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Yanhua Han
Keyword(s):  
Attitude Control ◽  
Dynamics Modeling ◽  
Attitude Control System ◽  
Constraint Forces ◽  
Inertia Moment ◽  
Modeling And Control ◽  
And Control ◽  
Kane Method ◽  
Control Study ◽  
Space Target

Dynamics modeling and control problem of a two-link manipulator mounted on a spacecraft (so-called carrier) freely flying around a space target on earth’s circular orbit is studied in the paper. The influence of the carrier’s relative movement on its manipulator is considered in dynamics modeling; nevertheless, that of the manipulator on its carrier is neglected with the assumption that the mass and inertia moment of the manipulator is far less than that of the carrier. Meanwhile, we suppose that the attitude control system of the carrier guarantees its side on which the manipulator is mounted points accurately always the space target during approaching operation. The ideal constraint forces can be out of consideration in dynamics modeling as Kane method is used. The path functions of the manipulator’s end-effector approaching the space target as well as the manipulator’s joints control torque functions are programmed to meet the soft touch requirement that the end-effector’s relative velocity to the space target is zero at touch moment. Numerical simulation validation is conducted finally.

scholarly journals The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Dewei Zhang ◽  
Hui Qi ◽  
Xiande Wu ◽  
Yaen Xie ◽  
Jiangtao Xu
Keyword(s):  
Target Tracking ◽  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Tracking Control ◽  
Feedback Linearization ◽  
Control Method ◽  
Measurement Unit ◽  
Control Algorithms ◽  
Nonlinear Dynamic Model ◽  
And Control

A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU). The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

scholarly journals Modeling and Control of Cutter Vibration in the Presence of Random Distribution of Microhardness of Workpiece and Nonlinear Cutting Forces in Lathe Process

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
A. H. El-Sinawi
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Random Distribution ◽  
Orthogonal Cutting ◽  
Nonlinear Dynamic Model ◽  
Linear Quadratic ◽  
Workpiece Material ◽  
Actuator Dynamics ◽  
Modeling And Control ◽  
And Control

This work presents a comprehensive approach to the control of tool's position, in the presence of machine tool structure vibration, nonlinear cutting force, and random tool vibration due to random distribution of microhardness of workpiece material. The controller is combination of Proportional and linear quadratic gaussian- (P-LQG-) type constructed from an augmented model of both tool-actuator dynamics and a nonlinear dynamic model relating tool displacement to cutting forces. The latter model is obtained using black-box system identification of experimental orthogonal cutting data in which tool displacement is the input and cutting force is the output. The controller is evaluated and its performance is demonstrated.

The Spherical Rolling-Flying Vehicle: Dynamic Modeling and Control System Design

2021 ◽  
pp. 1-23
Author(s):  
Stefan Atay ◽  
Matthew Bryant ◽  
Gregory D. Buckner
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Dynamic Modeling ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
High Mobility ◽  
Theoretical Development ◽  
Trajectory Tracking Control ◽  
Modeling And Control ◽  
And Control

Abstract This paper presents the dynamic modeling and control of a bi-modal, multirotor vehicle that is capable of omnidirectional terrestrial rolling and multirotor flight. It focuses on the theoretical development of a terrestrial dynamic model and control systems, with experimental validation. The vehicle under consideration may roll along the ground to conserve power and extend endurance but may also fly to provide high mobility and maneuverability when necessary. The vehicle employs a three-axis gimbal system that decouples the rotor orientation from the vehicle's terrestrial rolling motion. A dynamic model of the vehicle's terrestrial motion is derived from first principles. The dynamic model becomes the basis for a nonlinear trajectory tracking control system suited to the architecture of the vehicle. The vehicle is over-actuated while rolling, and the additional degrees of actuation can be used to accomplish auxiliary objectives, such as power optimization and gimbal lock avoidance. Experiments with a hardware vehicle demonstrate the efficacy of the trajectory tracking control system.

Modeling and Control of Automated Pipe Hoisting in Oil and Gas Well Construction

2015 ◽  
Author(s):  
Parham Pournazari ◽  
Pradeepkumar Ashok ◽  
Eric van Oort
Keyword(s):  
Dynamic Model ◽  
Oil And Gas ◽  
Sliding Mode ◽  
Drill String ◽  
Trajectory Design ◽  
Modeling And Control ◽  
Gas Drilling ◽  
Drilling Operations ◽  
Hoisting System ◽  
And Control

This paper presents a robust control algorithm for automatic hoisting of a drill string in oil and gas drilling operations. We demonstrate an iterative scheme for trajectory design and present a lumped dynamic model of the hoisting system. The trajectory is used along with the dynamic model to design a hybrid sliding mode and gain scheduled PI controller to deal with the frictional nonlinearities of the system. The simulation results demonstrate the feasibility of this approach in optimally performing the pipe hoisting task.

Modeling and control strategy of HPS electronic ballast considering the dynamic model of the lamp

2011 ◽  
Author(s):  
Andre L. Kirsten ◽  
Jacson Hansen ◽  
Paulo C. V. da Luz ◽  
Cassiano Rech ◽  
Ricardo N. do Prado ◽  
...  
Keyword(s):  
Dynamic Model ◽  
Control Strategy ◽  
Modeling And Control ◽  
Electronic Ballast ◽  
And Control

CONTROL OF OBJECTS OF OIL REFINING MODEL

2017 ◽  
pp. 78-82
Author(s):  
L. G. Tugashova ◽  
K. L. Gorshkova
Keyword(s):  
Genetic Algorithm ◽  
Regression Model ◽  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Control Model ◽  
Oil Refining ◽  
Nonlinear Dynamic Model ◽  
Control Actions ◽  
Main Components ◽  
And Control

The approaches to improve the management of processes of oil refining. The description of the control model and the adjustment of the coefficients of the controller by using genetic algorithm. Selected basic adjustable parameters and control actions. The main components of the control circuit for the models are: limitations of the regression model, nonlinear dynamic model, the unit of optimization.

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