Stabilization Of Quadrotor Research Articles

Labview and Remotexy Integration for Quadrotor Stabilization and Control

Abstract Nowadays, Small quadcopters have made significant advancements in recent years, thanks to the development of control systems, the availability of sensors, and affordable and reliable materials for their production. Additionally, programs have been developed to model and analyze these aircraft before production. The professional applications of quadcopters are seemingly endless due to their many advantages. The aim of this research is to build a quadcopter and test its stability utilizing Arduino Mega, IMU sensor (Inertial Measurement Unit) and MPU-6050 in LabVIEW environment. The objective is to select the suitable PID parameters and create a remote-control program that can be operated using a smartphone and RemoteXY app on Android OS.

Stochastic Estimator Based Adaptive Sliding Mode Control for a Quadrotor in Rainy Flight Conditions

Novel modeling of the raindrops impact forces on a quadrotor has been developed and implemented in this work. These forces are meant to generate dispersed displacement disturbances in the vertical axis [Formula: see text] and dispersed rotation disturbances around roll and pitch axis. The proposed model is derived using the stochastic characteristics of the raindrops combined with classical quadrotor dynamics to address the issue of the adopted sliding mode controller, which shows lack of robustness while tracking the desired path, resulting in sensitive fluctuations. These fluctuations are increasingly visible for disturbances generated by raindrops with an average diameter greater than 2 mm. To deal with these types of disturbances, a novel control law based on an adaptive sliding mode approach and the estimated parameters of the stochastic disturbances (average and variance) was employed. This control law has been synthesized based on the sliding mode approach and Lyapunov principle to ensure quadrotor stability and robustness purposes. The adopted estimation of the average and variance of the disturbances was carried out by filtering the difference between the system state and a reference model state. The adopted control law has been implemented on MATLAB/SIMULINK, yielding satisfactory results and minimizing the fluctuations.

On the Polytopic Modelling & Robust H∞ Control of Nonlinear Systems Subject to Cyber-attack: Application to Attitude Stabilization of Quadrotor

On the Polytopic Modelling & Robust H∞ Control of Nonlinear Systems Subject to Cyber-attack: Application to Attitude Stabilization of Quadrotor

A Comparative Study of Control Methods for X3D Quadrotor Feedback Trajectory Control

Unmanned aerial vehicles (UAVs), particularly quadrotor, have seen steady growth in use over the last several decades. The quadrotor is an under-actuated nonlinear system with few actuators in comparison to the degree of freedom (DOF); hence, stabilizing its attitude and positions is a significant challenge. Furthermore, the inclusion of nonlinear dynamic factors and uncertainties makes controlling its maneuverability more challenging. The purpose of this research is to design, implement, and evaluate the effectiveness of linear and nonlinear control methods for controlling an X3D quadrotor’s intended translation position and rotation angles while hovering. The dynamics of the X3D quadrotor model were implemented in Simulink. Two linear controllers, linear quadratic regulator (LQR) and proportional integral derivate (PID), and two nonlinear controllers, fuzzy controller (FC) and model reference adaptive PID Controller (MRAPC) employing the MIT rule, were devised and implemented for the response analysis. In the MATLAB Simulink Environment, the transient performance of nonlinear and linear controllers for an X3D quadrotor is examined in terms of settling time, rising time, peak time, delay time, and overshoot. Simulation results suggest that the LQR control approach is better because of its robustness and comparatively superior performance characteristics to other controllers, particularly nonlinear controllers, listed at the same operating point, as overshoot is 0.0% and other factors are minimal for the x3D quadrotor. In addition, the LQR controller is intuitive and simple to implement. In this research, all control approaches were verified to provide adequate feedback for quadrotor stability.

Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops

In this paper, a robust control technique is developed to achieve the quadrotor stabilization against unmodeled matching vanishing dynamics. The synthesis of the proposed robust control is based on the Lyapunov approach and the backstepping method allowing to construct an iterative control algorithm. To compare the performance of the proposed controller, a Proportional Derivative (PD) controller is used to obtain experimental results in an outdoor environment. To compare the closed-loop system responses with both controllers, the Integral Absolute Error is computed and several tests are conducted to calculate the error standard deviation. Ultimately, employing the robust backstepping control approach in pest recognition in maize crops, which is a specific task of precision agriculture, demonstrates its effectiveness in improving the trajectory tracking of the vehicle while it captures images of the crops.

Quadrotor stabilization under time and space constraints using implicit PID controller

In this paper, the quadrotor stabilization under time and state constraints is studied. The objective is to design a nonlinear controller under time and state constraint for quadrotor. The nonlinear quadrotor model is built by the Euler-Lagrange approach while ignoring the Coriolis terms, hub moment and force. Based on quadrotor’s dynamic model, a nonlinear feedback controller is designed for the quadrotor stabilization under time and state constraints. This feedback is an implicit PID controller where the feedback gains are obtained from LMIs (Linear matrix inequalities). LMI system characterizing the system stability and convergence properties is built based on convex embedding approach and implicit Lyapunov function method. To demonstrate the application prospects of implicit PID controller, robustness analysis is provided to show the property of implicit PID controller under external disturbance. The key novelty of this paper is that the implicit PID controller is proven feasible for applying to the quadrotor under time and state constraints, which is also the main outcome.

Positionable Rotor Quadrotor: Dynamic Modeling and Adaptive Finite-Time Sliding-Mode Controller Design

This paper introduces a positionable rotor structure for a quadcopter allowing each of its rotors to be positioned independently in a finite course and in forward and backward movement to increase robustness against disturbances such as wind. At first, the quadrotor motion dynamics are analyzed, and its dynamic model is derived by calculating translational and angular momenta. A hybrid controller with dual interconnected units is designed to achieve acceptable performance. The primary unit determines the common quadruplet control inputs of the quadrotor by an adaptive finite-time sliding-mode algorithm for all the translational and rotational degrees of freedom. The secondary unit uses primary controller outputs to specify each rotor’s suitable position to enhance the drone performance and robustness. Some correction steps are used to calculate more feasible rotor positions. Besides showing the proposed control system’s performance, simulations verify the effectiveness of rotor positioning on the quadrotor stability in harsh conditions. For the case study, up to 70% increase in the capacity of disturbance rejection and an over 30% reduction in power consumption compared to conventional drones are observed.

Control Methods for Quadrotor’s Stability

Quadrotor unmanned aerial vehicle (UAV) has become more and more popular due to its high maneuverability, vertical take-off, landing and hovering capability, and ease of operation. However, it is subject to various disturbances during the flight, such as turbulence. This paper provides a comprehensive survey of control methods proposed for quadrotor stability. According to the relationship between the controller and the controlled model, this paper divides the quadrotor stability control methods into three categories, namely classical control, optimal control, and intelligent control, for detailed discussion.

Attitude Stabilization of Quadrotor Using Adaptive Fuzzy Proportional Integral Derivative Controller

Quadrotor is an unmanned aerial robot from multi-rotor drones group that has high maneuverability, vertical take-off, and landing and stationary flight capabilities. In the most practical applications, the quadrotor system is subjected to external disturbance forces due to wind and unbalanced weight or inertia of the payload. To maintain balance and hold the position, attitude stabilization of the quadrotor is necessary for the presence of disturbances and unbalanced forces. Using conventional controllers with constant gains is not very efficient to eliminate variable disturbances that affect quadrotor motion in different conditions. In this paper, an adaptive fuzzy proportional integral derivative controller is designed for quadrotor attitude stabilization in which controller gains are regulated continuously based on the adaptive laws and the fuzzy inference system. The performance of the proposed controller is examined in the disturbance rejection test and is compared to the conventional proportional integral derivative controller. Also, the performance of the proposed controller is approved by hardware in the loop experimental tests using a 3 degree of freedom pilot platform. The experimental results will show the effectiveness of the adaptive fuzzy proportional integral derivative controller compared with the conventional proportional integral derivative controller.

Design of path planning and tracking control of quadrotor

<p style='text-indent:20px;'>In this paper, we first design a motion planning system based on the Batch Informed Trees (BIT*) algorithm for quadrotor and a linear model predictive control (LMPC) is applied to solve the path tracking problem for a quadrotor. BIT* algorithm is used to plan a barrier-free trajectory quickly in an obstructed environment. Then we apply linear model predictive control for the full state quadrotor system model to track the generated trajectory. Finally, the BIT* algorithm simulation case is presented using RVIZ visual interface and some simulation cases are presented using MATLAB / Simulink. The results demonstrate the capability and the effectiveness of the control strategy in fast path tracking and the quadrotor stability, while the desired performance is achieved.</p>

Robust Adaptive Global Time-varying Sliding-mode Control for Finite-time Tracker Design of Quadrotor Drone Subjected to Gaussian Random Parametric Uncertainties and Disturbances

The quadrotor has many potential applications such as infrastructure predictive maintenance in mining tunnels of the railway. In order to navigate through those environments by using the quadrotor drone, there are many challenges such as aerodynamics disturbances, parametric uncertainties, and noise measurements. A robust adaptive global time-varying sliding-mode controller (RAGTVSMC) is proposed to address the quadrotor path in the presence of the random disturbances and uncertainties. In order to eliminate the reaching phase and reduce the initial control effort, a novel time-varying sliding mode (TVSM) surface is presented for the quadrotor system. Moreover, the TVSM surface is designed to meet the impact time requirement with a global sliding mode. Adaptive laws are developed to address the upper bound of the additives disturbances on the quadrotor dynamics using only the error position and velocity. The convergence with specific time is assured and the quadrotor stability is proved according to Lyapunov’s theory. Finally, to demonstrate the effectiveness of the proposed controller in this work, simulations are conducted.

Quadrotor stabilization by Fuzzy Kalman Filter

Quadrotor stabilization by Fuzzy Kalman Filter

Attitude Stabilization of Quadrotor with Input Time Delay

Abstract A predictor feedback control for attitude stabilization of quadrotors with input time delay has been proposed in this paper by representing the attitude using rotation matrices to avoid the singularities and ambiguities associated with Euler angles and quaternions. The closed loop system is shown to be asymptotically stable with respect to a norm defined in the text. The norm has been defined in terms of states and past control efforts and hence explicitly results in Lyapunov Krasovskii functional for the system. A cascade of PDE-ODE system and the concept of transport delay has been used in the proof.

System identification and H∞-based control of quadrotor attitude

The attitude control of a quadrotor is a fundamental problem, which has a pivotal role in a quadrotor stabilization and control. What makes this problem more challenging is the presence of uncertainty such as unmodelled dynamics and unknown parameters. In this paper, to cope with uncertainty, an $H_\infty$ control approach is adopted for a real quadrotor. To achieve $H_\infty$ controller, first a continuous-time system identification is performed on the experimental data to encapsulate a nominal model of the system as well as a multiplicative uncertainty. By this means, $H_\infty$ controllers for both roll and pitch angles are synthesized. To verify the effectiveness of the proposed controllers, some real experiments and simulations are carried out. Results verify that the designed controller does retain robust stability, and provide a better tracking performance in comparison with a well-tuned PID and a $\mu$ synthesis controller.

Sliding mode control for altitude and attitude stabilization of quadrotor UAV with external disturbance

This paper addresses the problem of robust altitude and attitude control of ‘×’ mode configuration quadrotor UAV using Lyapunov stability based sliding mode control with saturation function. The dynamic model of the quadrotor was derived by considering nonlinearity factor. MATLAB Simulink was used to simulate the model in two different conditions; without and with the presence of external disturbance. This was done to test the robustness of the control method. Simulation results showed that the sliding mode controller provides good performance and robustness against disturbance.

A constrained error-based MPC for path following of quadrotor with stability analysis

This paper proposes a linear constrained model predictive control (MPC) to solve the path following problem for quadrotor unmanned aerial vehicles. In the controller, an augmented model is employed to completely eliminate the tracking error due to external disturbances imposed on the quadrotor. The proposed controller is capable of improving the trade-off between feasibility and performance of the system. By approximating the control input sequence in MPC with Laguerre function, the computational burden significantly decreases and the closed-loop performance improves. In addition, a prescribed stability procedure is applied to guarantee the asymptotic stability of the quadrotor error dynamics. Besides, the proposed method improves the numerical ill-conditioning problem in solving MPC, by modifying the position of the closed-loop system poles to lie inside the unit circle. In the simulation results, two scenarios for the quadrotor tracking problem are considered. The results demonstrate the capability and the effectiveness of the proposed control strategy in disturbance rejection, fast trajectory tracking and the quadrotor stability, while a desired performance is achieved.

Stabilization and Path Tracking of a Mini Quadrotor Helicopter: Experimental Results

Quadrotor helicopters are gaining notoriety as research platform of unmanned aerial vehicle (UAV), due to its mechanical simplicity and high maneuverability, as well as the ability to hover and perform vertical take-off and landing (VTOL). However, the development of control systems for such vehicles is not trivial. Quadrotors have a nonlinear and open-loop unstable behavior and they are constantly affected by aerodynamic disturbances and unmodeled dynamics. In this article, a cascade PID control strategy designed for stabilization and path tracking of an unmanned quadrotor is presented. The dynamic motion equations are obtained by the Lagrange-Euler formalism. The proposed control structure consists of an outer loop for the translational movements, followed by an inner loop for the stabilization of the quadrotor's attitude motions. Simulations and experimental results check the performance achieved with the proposed control strategy. The aircraft used is the Crazyflie 2.0 and the state estimation is accomplished through an extended Kalman filter, where information from the inertial measurement unit is fused with positional information from an ultra-wideband system.

Integrated Visual Servoing Solution to Quadrotor Stabilization and Attitude Estimation Using a Pan and Tilt Camera

This paper presents an integrated visual servoing solution to the problem of quadrotor attitude estimation and stabilization based solely on image feedback from a pan and tilt camera and biased rate gyros. The solution comprises a control law for the quadrotor position and attitude, a control law for the pan and tilt camera platform, and an estimator for the vehicle attitude, whose interconnection stabilizes the quadrotor in hover above certain terrain landmarks. Lateral-longitudinal stabilization is achieved with a nested saturation control law by feedback of the image measurements, estimated attitude, and corrected angular velocity measurements and the vehicle is stabilized vertically by means of image feedback. Resorting to the input-to-state stability properties of the controllers, the quadrotor’s position and attitude are shown to converge to the desired equilibrium point and, in the end, the interconnected system’s closed loop is proven robust to observer estimation errors. Additionally, the pan and tilt camera is actively actuated to keep the relevant features visible in the image field of view for most operating conditions. The robustness and performance of the proposed control and estimation architecture is illustrated through both simulation and experimental results.

Quadrotor attitude and position fuzzy control using linearised inverted moment matrix

Controlling non-linear dynamic model of quadrotor is a challenging task since the quadrotor is considered as an under-actuated system with highly coupled dynamics due to both the six Degrees Of Freedom (DOF) motion and four control input variables. The objective of this research is to investigate the implementation of fuzzy logic concepts using linearised inverted moment matrix in order to design Multi-Inputs-Multi-Outputs (MIMO) fuzzy flight control system for the quadratic non-linear dynamic model. Non-linear mathematical model of the quadrotor is derived and MIMO attitude and position fuzzy controllers are designed. The invert of moment matrix is linearised and differential actions of PD-fuzzy controllers are considered as well. The quadrotor dynamic behaviour is simulated and evaluated using M-file programs, the results have shown that using PD-fuzzy controller type is capable to achieve the design requirements and significantly improves the performance of the quadrotor stability characteristics.

Attitude Estimation for Quadrotor Based on IMU with Kalman-Filter

Improved a quadrotor technology that is capable of fast maneuvering requires accurate attitude estimation or navigation to maintain a quadrotor stability. The GPS can provide position measurements with an accuracy of several meters, but cannot provide orientation information directly. This study aims to design a quadrotor attitude navigation system based on IMU sensors on AR Drone 2.0 with a Kalman filter using the equation of state space model. The system model was developed using the Matlab software. The Kalman filter is designed as an estimator to reduce noise on the sensor so that it can improve measurement accuracy. The test results showed that the system model can be used to estimated the orientation angle and shift of the quadrotor, while the Kalman filter that designed can reduce noise in the sensor data. At the time of tested, the system provided the measurement accuracy of above 90% when tested indoor.