Model Of Aerial Vehicle Research Articles

Neuro‐fuzzy Elman wavelet control for nonlinear uncertain systems with fuzzy input and unknown fuzzy disturbances: Application to robotics

SummaryKeeping into view the irregular existence of uncertainties and disturbances in nonlinear systems, a novel adaptive control scheme based on neuro‐fuzzy Elman wavelet neural network (NFEWNN) has been proposed in this work which is capable of accurately modeling system uncertainties. In addition to this, an improvement in an evolutionary algorithm named particle swarm optimization has also been introduced to optimize the initial parameters of the controller. Uncertain non‐linear discrete‐time systems in the non‐strict feedback form with unknown disturbances are taken into consideration. This work aims to design an efficient adaptive control scheme for the proposed systems in the case of fuzzy input and fuzzy external disturbance which makes the control of the system more complex and difficult. The proposed NFEWNN control scheme is capable of tracking the desired trajectory successfully along with accurately modeling system uncertainties with high computational power, low computational burden, and rapid convergence rate. The stability of the controller has been proved using Lyapunov theory and guaranteed convergence of the controller is proved. Finally, real‐world applications of the work have been found in robotics. The controller has been implemented on the robotic manipulator and the dynamic model of aerial robotic vehicles to prove its effectiveness and efficiency.

Performance Investigation of WDM based hybrid RF-FSO Link with Unmanned Aerial Vehicles based Optical Relays

The paper presents the design of wavelength division multiplexing (WDM) based hybrid radio frequency-free space optical communication (RF-FSOC) system for high data rate transmission in the scenarios where the direct line-of-sight (LOS) view between the end-to-end communication nodes is unavailable. As such, a simulation model of unmanned aerial vehicle (UAV) based parallel relaying mechanism incorporating amplify and reflection (AR) technique is presented for establishing a point-to-point FSOC link between UAV and ground base station. Furthermore, the power spectral characteristics of the WDM optical signals modulated by 8-PAM signalling scheme at the transmitter node of the proposed model is simulated and analysed in the Optisystem 16. The simulation results illustrate that the overall link length of the proposed UAV based hybrid system with 1 Gbps data rate and transmitted beam divergence angle of 10 mrad extends upto a maximum range of 200 m in light fog condition.

Development of a novel supervisory controller on a parallel-hybrid powertrain for small unmanned aerial systems

PurposeA hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable of achieving a high range and endurance due to the low energy density of its batteries. Alternatively, conventional UAVs (cUAVs) using fuel with an internal combustion engine (ICE) produces more noise and thermal signatures which is undesirable, especially if the air vehicle is required to patrol at low altitudes and remain undetected by ground patrols. This paper aims to investigate the impact of implementing hybrid propulsion technology to improve on the endurance of the UAV (based on a 13.6 kg UAV).Design/methodology/approachA HE-UAV model is developed to analyze the fuel consumption of the UAV for given mission profiles which were then compared to a cUAV. Although, this UAV size was used as reference case study, it can potentially be used to analyze the fuel consumption of any fixed wing UAV of similar take-off weight. The model was developed in a Matlab-Simulink environment using Simulink built-in functionalities, including all the subsystem of the hybrid powertrain. That is, the ICE, electric motor, battery, DC-DC converter, fuel system and propeller system as well as the aerodynamic system of the UAV. In addition, a ruled-based supervisory controlled strategy was implemented to characterize the split between the two propulsive components (ICE and electric motor) during the UAV mission. Finally, an electrification scheme was implemented to account for the hybridization of the UAV during certain stages of flight. The electrification scheme was then varied by changing the time duration of the UAV during certain stages of flight.FindingsBased on simulation, it was observed a HE-UAV could achieve a fuel saving of 33% compared to the cUAV. A validation study showed a predicted improved fuel consumption of 9.5% for the Aerosonde UAV.Originality/valueThe novelty of this work comes with the implementation of a rule-based supervisory controller to characterize the split between the two propulsive components during the UAV mission. Also, the model was created by considering steady flight during cruise, but not during the climb and descend segment of the mission.

Robust adaptive sliding mode control strategy of uncertain nonlinear systems

This paper presents a robust adaptive sliding mode controller scheme as applied to a class of uncertain nonlinear systems with parametric uncertainties and external disturbances. First, a sliding mode control technique is designed. Then, the proposed robust adaptive control schemes are applied to estimate the parametric uncertainties and the upper bound value of the external disturbances by using adaptive laws, ensure robustness in presence of parametric uncertainties and external disturbances, and reduce chattering problem by introducing an hyperbolic tangent function. Lyapunov stability theory is used to analyze the stability of the closed-loop system. As an exemplar, the schemes have been applied to a quadrotor unmanned aerial vehicle (QUAV) model. Simulation results for the control of the QUAV model are provided to illustrate the performance of the proposed robust adaptive sliding mode control scheme and demonstrate that the proposed method has good tracking performance. The simulation results clearly prove the effectiveness of our approach.

Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models

Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models

Should friction losses be included in an electromechanical model of a bioinspired flapping-wing micro aerial vehicle to estimate the flight energetic requirements?

The paper aims to examine the effects of mechanical losses on the performance of a bioinspired flapping-wing micro aerial vehicle (FWMAV) and ways to mitigate them by introducing a novel electromechanical model. The mathematical model captures the effect of a DC gear motor, slider-crank, flapping-wings aerodynamics, and frictional losses. The aerodynamic loads are obtained using a quasi-steady flow model. The parameters of the flight mechanism are estimated using published experimental data which are also used to validate the mathematical model. Incorporating the flapping mechanism friction losses into the mathematical model enables capturing the physics of the problem with higher accuracy, which is not possible with simpler models. It also makes it possible to estimate the aerodynamic energetic requirements. Moreover, the model enabled evaluations of the effects of adding bioinspired elastic elements on the efficiency of the system. Although it is established through experimental studies that the addition of a bioinspired elastic element can improve system efficiency and increase lift generation, the existing mathematical models fail to model and predict such effects. It has been demonstrated that the addition of an elastic element can reduce friction losses in the system by decreasing the internal forces. Optimised parameters for a FWMAV incorporating elastic elements are also obtained.

ПОРІВНЯЛЬНИЙ АНАЛІЗ ТА СТВОРЕННЯ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ ДЛЯ ФОРМУВАННЯ МАКЕТА РОЙОВОЇ ВЗАЄМОДІЇ

The subject of study is the process of creating an unmanned aerial vehicle of the helicopter type, which is able to perform autonomous flight and be used in the premises to test the algorithms of swarm interaction. The aim is to reduce the cost of forming and operating the UAV swarm intelligence model, ensuring compatibility with existing hardware positioning systems and simulation software platforms. Tasks: to analyze the existing prototypes of unmanned aerial vehicles of the helicopter type, used for modeling and testing of autonomous flight modes indoors; to review the systems of positioning and exchange of information between the participants of the swarm formation and to analyze the hardware systems necessary for the implementation of these systems; to develop the architecture of hardware subsystems for unmanned aerial vehicles capable of performing tasks at the level of the considered prototypes; design a case for a sound hardware platform, check its operational parameters, implement its collection and testing; install software that allows you to check the operability of the considered platform of the unmanned aerial vehicle. The methods used are: systems analysis used to compare models of unmanned aerial vehicles within the tasks, methods of analysis and synthesis of schemes for the implementation of the hardware platform, the method of graphic modeling for the design of the unmanned aerial vehicle, methods of system programming for flight program. The following results were obtained. The choice of the hardware platform of the unmanned aerial vehicle is substantiated; the hull for the helicopter was developed and implemented, two platforms of unmanned aerial vehicles were collected and tested during autonomous flight indoors. Conclusions. The study found that there are existing and widely used platforms for compatible indoor flight. These platforms are open and closed. The analysis of open hardware platforms and synthesis of architecture of own unmanned aerial vehicle is made. The designed and implemented unmanned aerial vehicle is capable of autonomous flight, has all the necessary components to perform a compatible flight program. As part of the layout of swarm interaction, it is necessary to further adjust the positioning system.

Safe Motion Planning and Learning for Unmanned Aerial Systems

To control unmanned aerial systems, we rarely have a perfect system model. Safe and aggressive planning is also challenging for nonlinear and under-actuated systems. Expert pilots, however, demonstrate maneuvers that are deemed at the edge of plane envelope. Inspired by biological systems, in this paper, we introduce a framework that leverages methods in the field of control theory and reinforcement learning to generate feasible, possibly aggressive, trajectories. For the control policies, Dynamic Movement Primitives (DMPs) imitate pilot-induced primitives, and DMPs are combined in parallel to generate trajectories to reach original or different goal points. The stability properties of DMPs and their overall systems are analyzed using contraction theory. For reinforcement learning, Policy Improvement with Path Integrals (PI2) was used for the maneuvers. The results in this paper show that PI2 updated policies are a feasible and parallel combination of different updated primitives transfer the learning in the contraction regions. Our proposed methodology can be used to imitate, reshape, and improve feasible, possibly aggressive, maneuvers. In addition, we can exploit trajectories generated by optimization methods, such as Model Predictive Control (MPC), and a library of maneuvers can be instantly generated. For application, 3-DOF (degrees of freedom) Helicopter and 2D-UAV (unmanned aerial vehicle) models are utilized to demonstrate the main results.

Study of Flow around a Trapezoidal Model of a Small-Sized UAV into Turbulent Wake

Investigations of the structure of the flow near the surface of a trapezoidal model of a small unmanned aerial vehicle were carried out when it enters a narrow turbulent wake. All experimental data were obtained in a wind tunnel at subsonic flow velocities. A feature of the work was that the study of the flow around the model was carried out at full-scale (flight) Reynolds numbers. Using the soot-oily visualization method, data on the features of the flow around the model were obtained, taking into account such factors as the angle of attack, the presence and absence of a source of external disturbances that generated a turbulent wake. The experiments were carried out in two flow regimes: at a zero angle of attack, when there are local separation bubbles on the wing, and at a large (supercritical) angle of attack of 18 degrees, when there is a global stall of the flow from the leading edge. It was shown that the turbulent wake has a significant effect on the nature of the flow near the model surface in both cases. Local separation bubbles gradually decrease in size with a decrease in the distance between the sources of disturbances and the wing. Large-scale vortices significantly decrease in geometrical dimensions and shift towards the side edges in the event of a global stall of the flow, thereby increasing the region of the attached flow on the model surface.

Development of Energy Efficient For UAV

The development of energy efficiency in unmanned aerial vehicle operations was proposed in this work. Tremendous and remarkable achievements have been recorded in the area of unmanned aerial vehicle operations with regards to energy efficiency. The principal aim of energy efficiency while maintaining accurate collision avoidance. Characterization of the energy consumption of a conventional unmanned aerial vehicle was first carried out, then, A successful characterization was followed by development of a Simulink model of the conventional unmanned aerial vehicle with the characterized parametric values as input for simulation. With a reliable simulation result, then a model on energy efficiency was developed. This model was simulated in order to validate and justify the work. Velocity and energy-time graphs were plotted to show the relationships of velocity and time of unmanned aerial vehicle flight as well as energy expended and time. Computations from the plotted graphs show an energy efficiency of 8.3% over a conventional operation of unmanned aerial vehicle without the application of the technique in this research. This is the percentage of improvement. It is a justification and validation of this research on the use of energy efficiency in unmanned aerial vehicle operations. It has been established that energy consumption in unmanned aerial vehicle operations is influenced by its mode of operation at a given time. There is an obvious reduced running cost with energy efficiency.

A Robust Sensor and Actuator Fault Tolerant Control Scheme for Nonlinear System

In this article, a new fault-tolerant control (FTC) method is presented for the Lipschitz nonlinear systems that is capable of handling the actuator faults, sensor faults, unknown external disturbances, and system uncertainties. An augmented system is first constructed by treating the sensor fault as an auxiliary state. An adaptive fault estimation scheme with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> performance criterion is then developed to simultaneously estimate the actuator and sensor faults. To achieve the tracking control, a nonlinear sliding mode-based state feedback control law is proposed depending on the estimated states and information about fault from the fault estimating unit. The efficacy of the suggested technique is evaluated using a nonlinear model of the multirotor unmanned aerial vehicle (UAV) system with six degrees-of-freedom (DoF) motion. The proposed method is implemented in the inner loop subsystem in order to obtain the attitude and altitude tracking while the outer-loop control is simply a PID controller. Several simulations on the nonlinear system are performed to prove the effectiveness of the proposed method compared with the existing methods.

Characteristic Mode Analysis Prediction and Guidance of Electromagnetic Coupling Measurements to a UAV Model

In this work, we study the current coupled to a simplified Unmanned Aerial Vehicle (UAV) model using a dual computational and experimental approach. The simplified surrogate structure reduced the computational burden and facilitated the experimental measurement of the coupled currents. For a practical system, a wide range of simulations and measurements must be performed to analyze the induced current variations with respect to properties of the incident excitation waveform, such as the frequency, angle of incidence, and polarization. To simplify this analysis, Characteristic Mode Analysis (CMA) was used to compute the eigen-currents of the UAV model and predict where and under which RF excitation conditions the coupled current is maximized. We verified these predictions using direct experimental measurement of the coupled currents. The presented simulations and measurements show the usefulness of CMA for studying electromagnetic coupling to practical systems.

Closed-Loop Linear Covariance Framework for Path Planning in Static Uncertain Obstacle Fields

Path planning in an uncertain environment is a key enabler of true vehicle autonomy. Over the past two decades, numerous approaches have been developed to account for errors in the vehicle path while navigating complex and often uncertain environments. An important capability of such planning is the prediction of vehicle dispersion covariances about a candidate path. This work develops a new closed-loop linear covariance (CL-LinCov) framework applicable to a wide range of autonomous system architectures. Important features of the developed framework include 1) separation of high-level guidance from low-level control; 2) support for output-feedback controllers with internal states, dynamics, and output; and 3) multi-use continuous sensors for navigation state propagation, guidance, and feedback control. The closed-loop nature of the framework preserves the important coupling between the system dynamics; exogenous disturbances; and the guidance, navigation, and control algorithms. The developed framework is applied to a simplified model of an unmanned aerial vehicle and validated by comparison via Monte Carlo analysis. The utility of the CL-LinCov information is illustrated by its application to path planning in a static, uncertain obstacle field via a modified version of the rapidly exploring random tree algorithm.

UAV Behavior-Intention Estimation Method Based on 4-D Flight-Trajectory Prediction

Aiming at the limitation of the traditional four-dimensional (4-D) trajectory-prediction model of unmanned aerial vehicles (UAV), a 4-D trajectory combined prediction model based on a genetic algorithm is proposed. Based on historical flight data and the UAV motion equation, the model is weighted dynamically by a genetic algorithm, which can predict UAV trajectory and the time of entering the protection zone instantly and accurately. Then, according to the number of areas where the tangent line of the current trajectory point intersects with the collision area, alarm area, alert area, and the time of entering the protection zone, the UAV’s behavior intention can be estimated. The simulation experiments verify the dangerous behaviors of UAV under different danger levels, which provides reference for the subsequent maneuvering strategies.

Multiple Drone Navigation and Formation Using Selective Target Tracking-Based Computer Vision

Autonomous unmanned aerial vehicles work seamlessly within the GPS signal range, but their performance deteriorates in GPS-denied regions. This paper presents a unique collaborative computer vision-based approach for target tracking as per the image’s specific location of interest. The proposed method tracks any object without considering its properties like shape, color, size, or pattern. It is required to keep the target visible and line of sight during the tracking. The method gives freedom of selection to a user to track any target from the image and form a formation around it. We calculate the parameters like distance and angle from the image center to the object for the individual drones. Among all the drones, the one with a significant GPS signal strength or nearer to the target is chosen as the master drone to calculate the relative angle and distance between an object and other drones considering approximate Geo-location. Compared to actual measurements, the results of tests done on a quadrotor UAV frame achieve 99% location accuracy in a robust environment inside the exact GPS longitude and latitude block as GPS-only navigation methods. The individual drones communicate to the ground station through a telemetry link. The master drone calculates the parameters using data collected at ground stations. Various formation flying methods help escort other drones to meet the desired objective with a single high-resolution first-person view (FPV) camera. The proposed method is tested for Airborne Object Target Tracking (AOT) aerial vehicle model and achieves higher tracking accuracy.

Use of unmanned aerial vehicles for automated forest fire patrols in the Republic of Sakha (Yakutia)

Within the framework of this article, the possibility of using unmanned aerial vehicles in forests is considered. The specific object of research is the territory of the Republic of Sakha in Yakutia of the Russian Federation. The choice is explained by the size of this region - it is the largest in the country. The relevance of this article is explained by the description of the experience and principles of using UAVs in the regions of Russia. The paper also provides statistics on fires over the past 4 years, demonstrates all the main fire centers, as well as the principles of their distribution. To solve this problem, it is proposed to use several models of unmanned aerial vehicles. Each of them has certain positive and negative properties. At the same time, the article contains a calculation of the total number of drones to ensure constant monitoring of the environment. The material contains an economic justification for the use of specific aircraft in comparison with aircraft models. The conclusion contains a description of a specific model of the drone, which makes it possible to ensure the greatest efficiency of the complex of reconnaissance measures to detect fires in the region under study.

MODELLING OF THE UNMANNED AERIAL VEHICLES FLIGHT CONTROL SYSTEM

The article is an independent work containing the author’s ingenious research methodology and the model of the control system of Unmanned Aerial Vehicles. Furthermore a unique and world first mathematical model of an Unmanned Aerial Vehicle was developed, as well as a simulation program which enabled to investigate the control system of any Unmanned Aerial Vehicles in the tilt duct pitch (altitude), bank (direction), deviation and velocity, depending upon the variable values of the steering coefficient, reinforcement coefficient and the derivative constant. The research program was written in the language of the C++ as the MFC class, on the MS Visual Studio 2010 platform. The main issue resolved in the article is the pioneering research of the process of control during manual and semi-automatic guidance of the Unmanned Aerial Vehicle, with a jet propulsion system to the coordinates of preset points of the flight route. Modelling of the flight control system takes into account: the logical network of operations of the simulation program, the pilot-operator model, the set motion and control deviations as well as the flight control laws. In addition, modeling of the control system takes into account the drive model, engine dynamics, engine thrust, the model of steering actuators and the model of external loads. In contrast, the external load model takes into account the external forces acting on the unmanned aircraft, including gravitational forces and moments, aerodynamic forces and moments, aerodynamic drag, aerodynamic lateral forces, aerodynamic lift forces, aerodynamic heeling moment, mechanism of local angle of attack from damping torque and forces and moments from the engine.

Multiphysics anti-icing simulation of a CFRP composite wing structure embedded with thin etched-foil electrothermal heating films in glaze ice conditions

Electrothermal ice protection systems (IPS) for CFRP composite aircraft face distinct challenges because of the composite structure’s relatively low thermal conductivity and vulnerability to overheating. In this work, the thermal response of a thin etched-foil heating film-based IPS integrated into CFRP laminates was characterized both experimentally and by thermal FEM simulation. A resulting IPS configuration was implemented in a CFRP wing skin laminate model of an unmanned aerial vehicle (UAV) for multiphysics icing simulation. Glaze ice accretion and melting were simulated with in-flight conditions and varying heater heat fluxes and angles of attack. Sharp surface temperature drops were observed in the heating film gap regions, which led to the implementation of a quasi-continuous film spacing. A uniform heater heat flux of 7.5 kW/m2 achieved anti-icing functionality with an associated surface temperature range of 0–13 °C. This range revealed the merit of heat flux zone modulation to uniformly distribute the surface temperature and improve the overall energy efficiency of the system.

Analysis on space transmission model of the Microwave Wireless Power Transfer system

Abstract This paper systematically analyzes the main link that imposes restrictions on the overall efficiency of the Microwave Wireless Power Transfer (MWPT) system–space transmission. Three typical transmission models of aperture transmission in the near-field area, radiation-focused transmission in the middle-field area, and Friis transmission in the far-field area of radiation were analyzed and calculated. Then, the applicable conditions and efficiency of three-models were compared. And the influence of antenna electrical parameters on the efficiency of the MWPT system was discussed. In the end, three typical space transmission models of aerial vehicles, satellites, and islands were studied. The influence of the medium on the transmission efficiency was emphatically analyzed. This paper aims to summarize the general laws of space transmission of microwave energy. Provide a theoretical reference for related scientific research and engineering practice.

Integrative 3D Geological Modeling Derived from SWIR Hyperspectral Imaging Techniques and UAV-Based 3D Model for Carbonate Rocks

This paper demonstrates an integrative 3D model of short-wave infrared (SWIR) hyperspectral mapping and unmanned aerial vehicle (UAV)-based digital elevation model (DEM) for a carbonate rock outcrop including limestone and dolostone in a field condition. The spectral characteristics in the target outcrop showed the limestone well coincided with the reference spectra, while the dolostone did not show clear absorption features compared to the reference spectra, indicating a mixture of clay minerals. The spectral indices based on SWIR hyperspectral images were derived for limestone and dolostone using aluminum hydroxide (AlOH), hydroxide (OH), iron hydroxide (FeOH), magnesium hydroxide (MgOH) and carbonate ion (CO32−) absorption features based on random forest and logistic regression models with an accuracy over 87%. Given that the indices were derived from field data with consideration of commonly occurring geological units, the indices have better applicability for real world cases. The integrative 3D geological model developed by co-registration between hyperspectral map and UAV-based DEM using best matching SIFT descriptor pairs showed the 3D rock formations between limestone and dolostone. Moreover, additional geological information of the outcrop was extracted including thickness, slope, rock classification, strike, and dip.