Quad-rotor Aerial Vehicle Research Articles

Robust Attitude Controller Design for an Uncommon Quadrotor With Big and Small Tilt Rotors

AbstractIn this article, a robust attitude controller design for an uncommon quadrotor aerial vehicle is discussed. This aerial vehicle is designed to have two big rotors on the longitudinal axis to increase the lift capacity and flight endurance, and two small tilt rotors on the lateral axis to stabilize the attitude. Similar to other multirotors, linearization of the full nonlinear model and using an appropriate rotor mixing matrix give the approximate diagonal attitude model of this quadrotor around hover. However, this ideal model lacks sensor delays, uncertain parameters, flexible modes of a structure, and inexact decoupling dynamics. Therefore, using this model in the control design limits the achievable attitude control performance. Unlike most studies, a system identification method is applied to estimate a more accurate model and increase the resulting attitude control performance. The aim of this paper is to obtain a suitable nominal model with accompanying uncertainty using robust control criterion in the system identification. In this way, an uncertain model that gives high performance in the subsequent robust control design is obtained. The experimental results show that this combined identification and robust control procedure improves attitude control performance compared to existing classical controller design methods.

Oil Facilities Surveillance Using an Autonomous Quadrotor

This work addresses using the autonomous quadrotor or unmanned aerial vehicle (UAV) for surveillance of oil fields, Facilities and pipelines since that can be very costly and dangerous specially in dangerous zones. This topic is very important because of the money consuming to repair and protect these oil facilities. Quadrotors are very small Vertical take-off landing (VTOL) helicopter, cheap, easy to use and has many other fields of applications. Quadrotor’s dynamic model involves nonlinearity, uncertainties, and coupling which makes the Quadrotor has a very complex system. PID controllers are proposed for controlling the quadrotor altitude through different environments during different missions. To drive the quadrotor to follow the desired trajectory pure pursuit algorithm (PPA) will be use. The simulation results will be pretested using the visual simulator named Gazebo with the aid of ROS to connected with the MATLAB to show the movement of the quadrotor insides different environments.

Energy efficiency path planning for a quadrotor aerial vehicle

Unmanned aerial vehicles are used today in many real-world applications. In all these applications, the vehicle endurance (flight time) is an important constraint that affects mission success. This study investigates the limitations of embedded energy for a quadrotor aerial vehicle. We consider a quadrotor simple tasked to travel from an initial hover configuration to a final hover configuration. In order to have a precise approximation of the consumed energy, we propose a power consumption model with battery dynamic, motor dynamic, and rotor efficiency function. We then introduce an optimization algorithm to minimize the energy consumption during quadrotor aerial vehicle mission. The proposed algorithm is based on an optimal control problem formulated for the quadrotor model and solved using nonlinear programming. In the optimal control problem, we seek to find control inputs (rotor velocity) and vehicle trajectory between initial and final configurations that minimize the consumed energy during a point-to-point mission. We extensively test in simulation experiments the proposed algorithm under normal and windy weather conditions. We compare the proposed optimization method with a nonlinear adaptive control approach to highlight the saved amount of energy.

A Mixed-Initiative Formation Control Strategy for Multiple Quadrotors

In this paper, we present a mixed-initiative motion control strategy for multiple quadrotor aerial vehicles. The proposed approach incorporates formation specifications and motion-planning commands as well as inputs by a human operator. More specifically, we consider a leader–follower aerial robotic system, which autonomously attains a specific geometrical formation, by regulating the distances among neighboring agents while avoiding inter-robot collisions. The desired formation is realized by a decentralized prescribed performance control strategy, resulting in a low computational complexity implementation with guaranteed robustness and accurate formation establishment. The multi-robot system is safely guided towards goal configurations, by employing a properly defined navigation function that provides appropriate motion commands to the leading vehicle, which is the only one that has knowledge of the workspace and the goal configurations. Additionally, the overall framework incorporates human commands that dictate the motion of the leader via a teleoperation interface. The resulting mixed-initiative control system has analytically guaranteed stability and convergence properties. A realistic simulation study, considering a team of five quadrotors operating in a cluttered environment, was carried out to demonstrate the performance of the proposed strategy.

A Predictive Control Strategy for Aerial Payload Transportation with an Unmanned Aerial Vehicle

This paper presents the results of a model-based predictive control (MPC) design for a quadrotor aerial vehicle with a suspended load. Unlike previous works, the controller takes into account the hanging payload dynamics, the dynamics in three-dimensional space, and the vehicle rotation, achieving a good balance between fast stabilization times and small swing angles. The mathematical model is based on the Euler–Lagrange formulation and considers the dynamics of the vehicle, the cable, and the load. Then, the mathematical model is represented as an input-affine system to obtain the linear model for the control design. A constrained MPC strategy was designed and compared with an unconstrained MPC and an algorithm from the literature for the case of study. The constraints to be considered include the limits on the swing angles and the quadrotor position. The constrained control algorithm was constructed to stabilize the aerial vehicle. It aims to track a trajectory reference while attenuating the load swing, considering a maximum swing range of ±10∘. Numerical simulations were carried out to validate the control strategy.

Hemispherical InfraRed (IR) Marker for Reliable Detection for Autonomous Landing on a Moving Ground Vehicle From Various Altitude Angles

Autonomous landing of a quadrotor aerial vehicle on a mobile ground vehicle is a key function required for heterogeneous cooperation between air and ground vehicles to extend mission range. Wide angle detection and localization of mobile landing spot can improve reliability and convenience in autonomous landing processes. In this study, we present a hemispherical InfraRed (IR) marker designed and built for reliable detection and autonomous landing from various altitude angles. IR light has higher transmittance and the hemispherical design provides wide angle radiation. We present the fabrication process of the hemispherical marker from a planar flexible film, followed by full system integration on the ground vehicle. The relatively compact (radius: 2.25 cm, height: 2.3 cm) marker is detectable from wide altitude angles (0–180°) and detectable even when covered by thin foreign objects such as fallen leaves or plastic bags. Outdoor experiments with full system integrating autonomous air and ground vehicles demonstrated the feasibility of this approach to autonomous landing for heterogeneous cooperation.

Image Guided Visual Tracking Control System for Unmanned Multirotor Aerial Vehicle with Uncertainty

This paper presents a wavelet-based image guided tracking control system for unmanned multirotor aerial vehicle system with the presence of uncertainty. The visual signals for the visual tracking process are developed by using wavelet coefficients. The design uses a multiresolution interaction matrix with half and details images to relate the time-variation of wavelet coefficients with the velocity of the aerial vehicle and controller. The proposed design is evaluated on a virtual quadrotor aerial vehicle system to demonstrate the effectiveness of the wavelet-based visual tracking system without using an image processing unit in the presence of uncertainty. In contrast to the classical visual tracking technique, the wavelet-based method does not require an image processing task.

Effects of unmodelled dynamic factors on an under-actuated quadrotor: A review of hybrid observer design methods

Unmodelled dynamic factors are either the left-over or the estimated factors such as lower or upper bound values while modelling any mechatronic system. Hence, with the inclusion of under-actuation in a system such as fewer number of actuators as compared to degrees of freedom, this will lead the system to high instability. These factors are changing instantly during multiple flights of quadrotor that is, the values of these factors in path following may vary from the values in hovering mode. Hence, it is one of the strenuous tasks to tackle these unmodelled dynamic factors for the multiple flight modes of an underactuated quadrotor craft. One of the better ways for tracking control of a quadrotor aerial vehicle with unmodelled dynamics is to observe and estimate the instant change in parameters. Thus, this paper exhibits an extensive review of several hybrid observer design methods being fused with some novel control strategies. In addition to this, the survey paper also summarises the limitations of the current state of the art approaches. This paper demonstrates an unexplored field of study where researchers must need to evaluate the performance of hybrid observer design methods.

Neural Network-Based Self-Learning of an Adaptive Strictly Negative Imaginary Tracking Controller for a Quadrotor Transporting a Cable-Suspended Payload With Minimum Swing

In this article, we introduce an adaptive strictly negative-imaginary (SNI) autopilot for a low-cost quadrotor aerial vehicle, specifically designed to achieve high precision hovering and perform accurate trajectory tracking under time-varying dynamic load (i.e., displacement, velocity, and acceleration). Leveraging the learning ability of an artificial neural network, our adaptive SNI controller is robustly designed to overcome uncertainties in flight environments such as variations in the centre-of-gravity, modeling errors, and unpredictable wind gusts. The efficacy of the proposed adaptive control system is investigated under extensive flight tests in addition to numerous computer simulations and rigorous comparison with other control techniques, namely, fixed-gain SNI, fuzzy-SNI, and conventional PID controllers. We also conduct a stability analysis of the proposed control system using the SNI theorem.

Controlling of an Under-Actuated Quadrotor UAV Equipped With a Manipulator

Unmanned aerial vehicles (UAV) equipped with a manipulator offer an additional flexibility and smart way to grasp the desired objects from inaccessible locations where the access of ground vehicles (GV) are not possible. In this research, we design an adaptive control based regulation, pole-placement and tracking (RST) control scheme for controlling the nonlinear behavior of an under-actuated quad rotor aerial vehicle. The overall performance of the system dealt by MIT rules. The aerial vehicle is equipped with a camera and a gripper that helps us to locate the wanted object from inaccessible location. The model of quad rotor UAV has six degrees of freedom (6-DOF) and the equipped gripper is about (2-DOF). For a successful flight operation UAV requires a reliable controller to stabilize the aerodynamic effects, disturbances that produced by the gripper. Due to aforementioned issue, design an adaptive RST controller, to control the dynamic behavior of the highly nonlinear complex system. Moreover, the effectiveness of the designed controller proven by applying computer-based simulation and it will verify experimentally. Lastly, it observes that the designed controller shows better robustness and good steady state performance to accomplish the given task.

Modeling and controlling of quadrotor aerial vehicle equipped with a gripper

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.

Trajectory Tracking Control of a Quadrotor Aerial Vehicle in the Presence of Input Constraints

In this paper, we address the control problem of a Quadrotor Aerial Vehicle (QAV) in the presence of the input constraints. For this purpose, a separation principle is applied in the control design. The QAV model is decoupled and constructed as a cascaded structure to handle its underactuated property. By imposing the constraints on the orientation angles, we show that the QAV will be never overturned. Then, a combination of the backstepping method, barrier Lyapunov and saturation functions is used in the control design for each subsystem to deal with both input and output constraints. Our design renders the cascaded system of the QAV into the form in which an Input-to-State Stable (ISS) subsystem is driven by an asymptotic subsystem, and hence the stability of the overall cascaded system of the QAV is ensured. In addition, the tracking errors are guaranteed to converge to the origin. Simulation results are provided to illustrate the effectiveness of the proposed control.

An adaptive hierarchical control for aerial manipulators

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.

Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle

This paper addresses the stability and tracking control problem of miniature unmanned multirotor aerial vehicle (MUMAV) in the presence of bounded uncertainty. The uncertainty may appear from unmodeled dynamics, underactuated property, input disturbance and flying environment. Nonlinear robust adaptive sliding mode control algorithm is designed by using Lyapunov function. Robust adaptation laws are designed to learn and compensate the bounded parametric uncertainty. Lyapunov analysis shows that the proposed algorithms can guarantee asymptotic stability and tracking control property of the linear and angular dynamics of MUMAV system. Compared with other existing control methods, the proposed design is very simple and easy to implement as it does not require multiple design steps, augmented auxiliary signals and exact bound of the uncertainty. Experimental results on a miniature unmanned quadrotor aerial vehicle are presented to illustrate of effectiveness of the proposed design for real-time applications.

Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters

ABSTRACTIn this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.

THE DEVELOPMENT OF TILT-ROTOR UNMANNED AERIAL VEHICLE

In this research, we had developed quad-rotor unmanned aerial vehicles with the tilt-rotor mechanism. People are eager to fly therefore the development of aerial vehicles, such as fixed-wing aerial vehicles and multi-rotor aerial vehicles, has grown rapidly in recent years. The multi-rotor vertical take-off and landing (VTOL) unmanned aerial vehicle which can fly stably and hover in a fix position developed the fastest. Comparing the general fixed-wing aircrafts and rotorcrafts, fixed-wing aircrafts can fly with a higher speed than rotorcrafts, but they do not have the VTOL and hovering abilities. The proposed quad-rotor aerial vehicle with tilt-rotor mechanism has two flight modes: rotorcraft and fixed-wing aircraft flight mode. It can take-off and land vertically in rotorcraft mode and can also fly faster in fixed-wing aircraft flight mode. The dynamic equations of the proposed quad-rotor aerial vehicle with tiltrotor mechanism are also studied in this paper.

Embedded solutions for a class of highly unstable, underactuated and self-balancing robotic systems

This paper presents a didactic framework in embedded electronics systems that is used to elicit awareness into students and engineers on the design issues arising in the realization of a class of underactuated robots and aerial vehicles that needs be robustly controlled due to their intrinsic unstability. The applications prototyped on the embedded platform presented here are conceived, by design, to be compliant with tiny collaborative robotics applications in order to adhere to the needs of the complex cyber-physical systems problem. The proposed platform is self-contained with on-board sensing and computation. Its engineering uses only off-the-shelf and mass production components. The system is based on a general purpose embedded board equipped with a 32-bit microcontroller which is able to manage all the basic tasks of this robotic platform: sensing, actuation, control and communication. The framework is described, and initial experimental results are introduced. Three applications are presented in this work as a validation of the methodology: a ballbot robot, a legged robot and a quadrotor aerial vehicle. The chosen case studies are robotics applications that are specialized in performing maneuvers when operating in tight spaces as in the human living environments.

Integrated Navigation System for a Low-Cost Quadrotor Aerial Vehicle in the Presence of Rotor Influences

AbstractThe performance of navigation sensors may be seriously affected by the operating rotors of a drone. To address this kind of disturbance, a low-cost multisensor integrated navigation system was developed for a quadrotor aerial vehicle (QAV). The navigation board integrates a global positioning system (GPS) module, triaxial gyroscope, accelerometer, magnetometer, and a digital barometer. The sensors’ outputs were mathematically modeled and subsequently used in the integration Kalman filter. The data processing consisted of several steps: prefiltering, centralized filtering, and feedback. On the basis of onboard tests, the stochastic models of sensors were established in the presence of vibration, revolution, and ventilation caused by the QAV rotor’s operation, and in particular, its electromagnetic and aerodynamic characteristics. Flight experiments indicate that the proposed integrated navigation system can significantly improve flight accuracy and reliability.

Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure

It is challenging to stabilise an unmanned quad-rotor aerial vehicle when a dynamic change in its model parameters or failure of its actuator occurs. In this paper, a quad-rotor unmanned aerial vehicle UAV is controlled based on model reference adaptive control MRAC and a linear quadratic regulator LQR. The kinematics and dynamics of the quad-rotor are calculated, and Lyapunov's direct stability method is used to design the MRAC. In order to evaluate the performance of the adaptive control algorithms in the presence of thrust loss that may occur due to component failure or physical damage, a real quad-rotor is built from scratch using commercial components. Both controllers are designed, implemented and tested using AVR microcontrollers. Comparison is made between the controllers under normal and faulty situations and the effectiveness of the proposed control strategy is verified. Simulation and experimental results show that both controllers have satisfactory performance under normal conditions and even in the presence of the partial loss of thrust that may occur due to the loss of control effectiveness in one of the rotors or the damage of one propeller, superior system performance is observed using the proposed MRAC controller.

Implementation and Testing of Autonomous Quad-Rotor Aerial Vehicle by Using Ardu-Pilot

Implementation and Testing of Autonomous Quad-Rotor Aerial Vehicle by Using Ardu-Pilot