Dynamics Modeling and Control of a Quadrotor with Swing Load

Nowadays, aerial robots or Unmanned Aerial Vehicles (UAV) have many applications in civilian and military fields. For example, of these applications is aerial monitoring, picking loads and moving them by different grippers. In this research, a quadrotor with a cable-suspended load with eight degrees of freedom is considered. The purpose is to control the position and attitude of the quadrotor on a desired trajectory in order to move the considered load with constant length of cable. So, the purpose of this research is proposing and designing an antiswing control algorithm for the suspended load. To this end, control and stabilization of the quadrotor are necessary for designing the antiswing controller. Furthermore, this paper is divided into two parts. In the first part, dynamics model is developed using Newton-Euler formulation, and obtained equations are verified in comparison with Lagrange approach. Consequently, a nonlinear control strategy based on dynamic model is used in order to control the position and attitude of the quadrotor. The performance of this proposed controller is evaluated by nonlinear simulations and, finally, the results demonstrate the effectiveness of the control strategy for the quadrotor with suspended load in various maneuvers.

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Modeling and control of an unmanned underwater vehicle using a mass moving system

Modern Physics Letters B ◽

10.1142/s021798491540014x ◽

2015 ◽

Vol 29 (06n07) ◽

pp. 1540014 ◽

Cited By ~ 1

Author(s):

Seung-Woo Byun ◽

Donghee Kim ◽

Hyeung-Sik Choi ◽

Joon-Young Kim

Keyword(s):

Degrees Of Freedom ◽

Underwater Vehicle ◽

Control Algorithms ◽

Dynamics Model ◽

Modeling And Control ◽

Pitch Control ◽

Unmanned Underwater Vehicle ◽

Point Tracking ◽

Heading Control ◽

And Control

This paper describes the mathematical modeling and control algorithms of an unmanned underwater vehicle (UUV) named Minekiller. This UUV has two longitudinal thrusters, one vertical thruster, and an internal mass moving system, which can control the pitch rate. The UUV is equipped with a movable mass for pitch control. It is different from other common UUVs, in that it can maintain a static pitch angle. The UUV's 6-DOF (Degrees of Freedom) dynamics model is derived from the hydrodynamic forces and moments acting on it. We applied these hydrodynamic coefficients to dynamic modeling for numerical simulations by MATLAB/SIMULINK©. To compare the performance in various cases, we used a PID controller for depth and heading control. Also, the navigation controller can analyze the way-point tracking performance. These simulation results show the performance of the control algorithms and maneuvering performance of the underwater vehicle.

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Multi-Body Dynamics Modeling and Control for Strapdown Inertially Stabilized Platforms Considering Light Base Support Characteristics

Applied Sciences ◽

10.3390/app10207175 ◽

2020 ◽

Vol 10 (20) ◽

pp. 7175

Author(s):

Zhongshi Wang ◽

Dapeng Tian ◽

Lei Shi ◽

Jinghong Liu

Keyword(s):

Disturbance Compensation ◽

Dynamics Modeling ◽

Tracking Accuracy ◽

Dynamics Model ◽

Modeling And Control ◽

Body Dynamics ◽

Feedforward Controller ◽

Multi Body ◽

And Control ◽

Compound Disturbance

The dynamics model used for inertially or strapdown inertially stabilized platforms is based on the rotor and motor load, and it either does not consider the stator or it implicitly assumes a fixed stator. It has been determined that vibrations occur in the system when a controller is used in strapdown inertially stabilized platforms with a light base support. As the system is also affected by multi-source disturbances, which are the main factors that affect the control accuracy. For the above two problems, this paper originally establishes a multi-body dynamics model including the controller. The composite controller not only suppresses the vibration successfully, but also greatly improves the disturbance compensation and tracking performance of the strapdown inertially stabilized platforms. Specifically, a modified feedback controller is used to suppress the vibrations analyzed according to the dynamics model. The friction feedforward and residual disturbance observer facilitates the design of compound disturbance compensation on the basis of composite hierarchical anti-disturbance control. To emphasize the advantages of strapdown inertially stabilized platforms, the feedforward controller employs feedforward angular velocity and acceleration. The results of the numerical analysis and experiments indicate that vibrations are successfully suppressed and tracking accuracy and disturbance isolation ability are improved.

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Development of a Special Inertial Measurement Unit for UAV Applications

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4007122 ◽

2012 ◽

Vol 135 (1) ◽

Cited By ~ 2

Author(s):

Khaled S. Hatamleh ◽

Ou Ma ◽

Angel Flores-Abad ◽

Pu Xie

Keyword(s):

Degrees Of Freedom ◽

Measurement Unit ◽

Dynamics Modeling ◽

Dynamics Model ◽

Inertial Measurement ◽

Six Degrees Of Freedom ◽

On Line ◽

Measurement Units ◽

Sensor Models ◽

And Control

Dynamics modeling is becoming more and more important in the development and control of unmanned aerial vehicles (UAV). An accurate model of a vehicle requires good knowledge of the dynamics properties and motion states, which are usually estimated with the help of integrated inertial measurement units (IMUs). This work develops a special six degrees of freedom IMU, which has the capability of measuring the angular accelerations. This paper introduces the design of the new IMU along with its sensor models and calibration procedures. The work introduces two experimental methods to verify the calibrated IMU readings. The IMU was designed to support an on-line methodology to estimate the parameters of UAV’s dynamics model that is currently being developed by the authors.

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Modeling and control of an underactuated tractor–trailer wheeled mobile robot

Robotica ◽

10.1017/s0263574716000886 ◽

2017 ◽

Vol 35 (12) ◽

pp. 2297-2318 ◽

Cited By ~ 12

Author(s):

Asghar Khanpoor ◽

Ali Keymasi Khalaji ◽

S. Ali A. Moosavian

Keyword(s):

Mobile Robot ◽

Control Algorithm ◽

Degrees Of Freedom ◽

Wheeled Mobile Robot ◽

Robot Kinematics ◽

Wheeled Mobile Robots ◽

Modeling And Control ◽

Pure Rolling ◽

The Stability ◽

And Control

SUMMARYTrajectory tracking is one of the main control problems in the context of Wheeled Mobile Robots (WMRs). Control of underactuated systems has been focused by many researchers during past few years. In this paper, tracking control of a Tractor–Trailer Wheeled Mobile Robot (TTWMR) has been discussed. TTWMR includes a differential drive WMR towing a passive spherical wheeled trailer. Spherical wheels in contrast with standard wheels make the robot highly underactuated with severe non-linearities. Underactuation is due to the use of spherical wheeled trailer to increase robots' maneuverability and degrees of freedom. In fact, standard wheels are subjected to non-holonomic constraints due to pure rolling and non-slip conditions, which reduce robot maneuverability. In this paper, after introducing the robot, kinematics and kinetics models are obtained. Then, based on a physical intuition, a novel control algorithm is developed for the robot, i.e. Lyapunov-PID control algorithm. Subsequently, singularity avoidance of the proposed algorithm is discussed and the stability of the algorithm is analyzed. Finally, simulation and experimental results are presented which reveal the effectiveness of the proposed algorithm.

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A Switching System oriented Modeling and Control Strategy for Idle Speed Control of a Hybrid Powertrain

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.924 ◽

2020 ◽

Vol 53 (2) ◽

pp. 14028-14033

Author(s):

Micha S. Obergfell ◽

Steven X. Ding ◽

Frank Wobbe ◽

Christoph-Marian Goletz ◽

Michael Folkers ◽

...

Keyword(s):

Control Strategy ◽

Speed Control ◽

Switching System ◽

Hybrid Powertrain ◽

Modeling And Control ◽

Idle Speed ◽

Idle Speed Control ◽

And Control

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Biostability in distribution systems in one city in southern China: Characteristics, modeling and control strategy

Journal of Environmental Sciences ◽

10.1016/s1001-0742(13)60422-2 ◽

2014 ◽

Vol 26 (2) ◽

pp. 323-331 ◽

Cited By ~ 13

Author(s):

Pinpin Lu ◽

Xiaojian Zhang ◽

Chiqian Zhang ◽

Zhangbin Niu ◽

Shuguang Xie ◽

...

Keyword(s):

Control Strategy ◽

Distribution Systems ◽

Southern China ◽

Modeling And Control ◽

And Control

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NEURAL MODELING AND CONTROL OF DYNAMIC SYSTEMS WITH HYSTERESIS

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2007-0008 ◽

2007 ◽

Vol 31 (1) ◽

pp. 127-141

Author(s):

Yonghong Tan ◽

Xinlong Zhao

Keyword(s):

Dynamic Systems ◽

Control Strategy ◽

Neural Modeling ◽

Modeling And Control ◽

Control Scheme ◽

The Neural Networks ◽

Adaptive Control Strategy ◽

Set Up ◽

Modeling Strategy ◽

And Control

A hysteretic operator is proposed to set up an expanded input space so as to transform the multi-valued mapping of hysteresis to a one-to-one mapping so that the neural networks can be applied to model of the behavior of hysteresis. Based on the proposed neural modeling strategy for hysteresis, a pseudo control scheme is developed to handle the control of nonlinear dynamic systems with hysteresis. A neural estimator is constructed to predict the system residual so that it avoids constructing the inverse model of hysteresis. Thus, the control strategy can be used for the case where the output of hysteresis is unmeasurable directly. Then, the corresponding adaptive control strategy is presented. The application of the novel modeling approach to hysteresis in a piezoelectric actuator is illustrated. Then a numerical example of using the proposed control strategy for a nonlinear system with hysteresis is presented.

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The Research of Air Precooling System Based on Generalize Predictive Control Strategy

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.433-435.1091 ◽

2013 ◽

Vol 433-435 ◽

pp. 1091-1098

Author(s):

Wei Bo Yu ◽

Cui Yuan Feng ◽

Ting Ting Yang ◽

Hong Jun Li

Keyword(s):

Predictive Control ◽

Control Strategy ◽

Control Algorithm ◽

Exchange Process ◽

Generalized Predictive Control ◽

Matlab Simulation ◽

Control Effect ◽

Heat Exchange Process ◽

Complex Control System ◽

And Control

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.

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