Unmanned Aerial Vehicle Configuration Research Articles

Weather-aware energy management for unmannedaerial vehicles: a machine learning application with global data integration

This study introduces a machine learning (ML) framework to predict unmanned aerial vehicle (UAV) energy requirements under diverse environmental conditions. The framework correlates UAV flight patterns with publicly accessible weather data, to yield an energy management tool applicable to a wide range of UAV configurations. The model employs the Cross-industry standard process for data mining and advanced feature engineering, offering an in-depth analysis of meteorological factors and UAV energy demands. The study assesses several multi-regression linear and ML models, whereby ensemble models gradient boosting (GB) and eXtreme gradient boosting demonstrate superior performance and accuracy. Specifically, the GB model achieved a test mean absolute error (MAE) of 0.0395 V (V) for voltage, 0.808 A (A) for current, and 9.758 mA-hours (mAh) for discharge, with prediction accuracy of over 99.9% for voltage and discharge, and 97% for current, derived from the coefficient of determination (R2). A novel integration of real-world UAV logs and weather data underpins the development of a weather-aware ML prediction model for UAV energy consumption. Our framework is capable of concurrently predicting three components of energy and power with almost uniform accuracy, a feature not found in contemporary models. Empirical test flights show a discrepancy of only 0.005 W-hour (Wh) between total predicted and actual energy consumption. This work enhances both efficiency and safety in UAV operations. The resulting energy-predictive flight planning tool sets a new benchmark for artificial intelligence (AI) applications in intelligent automation for UAVs.

CFD study of the effect of leading-edge tubercles on the aerodynamic characteristics of a small UAV based on eppler 186 airfoils

A numerical analysis is carried out to evaluate the aerodynamic characteristics of a small Unmanned Aerial Vehicle (UAV) whose wings are modified to incorporate sinusoidal leading edges (tubercles). This UAV has a rectangular wing composed of Eppler 186 airfoils. The aerodynamic characteristics of four UAV configurations varying the wavelength and amplitude along the wingspan are evaluated using Computational Fluid Dynamics (CFD). Results are compared with the baseline case, that is, without leading-edge tubercles. The wing configurations with tubercles exhibited increased lift at high angles of attack and delayed stall. The configuration with maximum amplitude (a=0.05c) and minium wavelength (λ=0.25c) achieved an increase up to 17 % in the maximum lift coefficient and delayed the stall up to the angle of attack of 20° compared to the baseline case.

Topology optimization of UAV network for target surveillance task with support jamming

In this paper, a topology optimization method is proposed for cooperative surveillance in unmanned aerial vehicles (UAVs) under an interference environment. We introduce the regional coverage rate to evaluate the cooperative surveillance performance under interference. At its core, we derive the expression of detection probability under interference in detail, which is inherently tied to the signal to interference plus noise ratio (SINR) influenced by UAV configuration, in which the location of each UAV affects the cooperative surveillance performance. To maximize the network surveillance performance, we use the coverage rate metric as the objective function to formulate a topology optimization problem under the interference environment, while satisfying distance constraints between UAVs. As the problem is non-convex and highly nonlinear, the internal self-constrained particle swarm optimization (ISC-PSO) algorithm is used to solve this problem, which can well address the issue of range constraints while maintaining adequate convergence. The numerical studies demonstrate that the proposed algorithm can obtain good surveillance performance in terms of different jamming strategies and shapes of monitoring areas.

Enhancing Coastal Risk Recognition: Assessing UAVs for Monitoring Accuracy and Implementation in a Digital Twin Framework

This paper addresses the intricate challenges of coastal management, particularly in rapidly forming tidal flats, emphasizing the need for innovative monitoring strategies. The dynamic coastal topography, exemplified by a newly formed tidal flat in Shanghai, underscores the urgency of advancements in coastal risk recognition. By utilizing a digital twin framework integrated with state-of-the-art unmanned aerial vehicles (UAVs), we systematically evaluate three configurations and identify the optimal setup incorporating real-time kinematics (RTK) and light detection and ranging (LiDAR). This UAV configuration excels in efficiently mapping the 3D coastal terrain. It has an error of less than 0.1 m when mapping mudflats at an altitude of 100 m. The integration of UAV data with a precise numerical ocean model forms the foundation of our dynamic risk assessment framework. The results showcase the transformative potential of the digital twin framework, providing unparalleled accuracy and efficiency in coastal risk recognition. Visualization through Unity Engine or Unreal Engine enhances accessibility, fostering community engagement and awareness. By predicting and simulating potential risks in real-time, this study offers a forward-thinking strategy for mitigating coastal dangers. This research not only contributes a comprehensive strategy for coastal risk management but also sets a precedent for the integration of cutting-edge technologies in safeguarding coastal ecosystems. The findings are significant in paving the way for a more resilient and sustainable approach to coastal management, addressing the evolving environmental pressures on our coastlines.

Affine Formation Maneuver Control for Multi-Agent Based on Optimal Flight System

The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously.

Optimization of propellers under consideration of aeroacoustic and aerodynamic goals and installation effects

Advanced Air Mobility (AAM) vehicles like air taxis and cargo unmanned aerial vehicles (UAVs) operate close to urban areas. Therefore, it is necessary to keep the noise footprint of such aerial vehicles at a minimum to gain societal acceptance for AAM vehicle operations. Cargo UAVs are typically highly integrated in terms of functions leading to a high extent of aerodynamic interactions between propellers and the airframe. As a result of these installation effects, unsteady loading noise can become the dominant part of the aerial vehicle noise emissions which leads to a situation, where classical propeller noise reduction measures like blade tip Mach number reduction do not necessarily lead to a reduction in the overall noise emissions. Overcoming these uncertainties in propeller design necessitates propeller noise optimization on an aircraft configuration level. In this work, an existing propeller optimization framework for isolated propellers was extended accordingly: Consideration of propeller inflow velocity perturbations due to installation in the blade element momentum theory-based propeller performance prediction and utilization of a blade element method code (BEM) to consider the scattering of propeller noise on the airframe accounts for configuration noise aspects. Optimization results of a pusher propeller UAV configuration conclude this work.

Dynamic fuzz testing of UAV configuration parameters based on dual guidance of fitness and coverage

ArduCopter's configuration parameter verification defects may cause the Unmanned Aerial Vehicle (UAV) in abnormal status. However, traditional UAV configuration parameter defect detection methods based on fuzz testing lack guidance design and inadequately detect configuration parameter defects. This paper proposes an improved configuration security defect analysis method based on fuzz testing. Using the fitness feedback mechanism based on the CAG neural network to guide the generation of fuzz testing cases, and using multiple coverage feedback mechanisms to guide the exploration direction of fuzz testing. Experimental results show that this method almost covers ArduCopter's position and attitude controller, guiding the UAV into abnormal states such as spin and crash, and detecting specific instances of configuration parameter defects.

Finite-time terminal sliding mode attitude control for tailless full-wing configuration UAVs based on extended state observers and auxiliary compensators

Considering the sensitivity of the tailless full-wing configuration unmanned aerial vehicle to disturbance and the strong nonlinearity and coupling caused by the manipulation combining the propeller and rudder, a finite-time terminal sliding mode controller with compound compensation is proposed in this paper to ensure stable attitude control. Based on singular perturbation theory, the inner loop sliding mode controller is designed so that the supremum of the convergence time of the rotational angular velocity tracking error in the sliding phase can be directly determined by the control parameters without requiring the initial state, and the outer loop sliding mode controller is designed so that the sliding surface function of the attitude angle tracking error has a fast convergence speed when it is far from and close to the origin. The compound compensation design further addresses the manipulation nonlinearity and disturbance sensitivity of the research object. Based on the minimum Euclidean norm optimization, the designed control allocator achieves command decoupling and reduces the desired control command. Through comprehensive verification, the proposed controller shows superior control performance and low energy consumption and exhibits strong robustness in the cruising flight envelope.

Validation of the Flight Dynamics Engine of the X-Plane Simulator in Comparison with the Real Flight Data of the Quadrotor UAV Using CIFER

The vertical take-off and landing (VTOL) of unmanned aerial vehicles (UAVs) is extensively employed in various sectors. To ensure adherence to design specifications and mission requirements, it is vital to verify flight control and system performance using an accurate dynamic model specific to UAV configuration. Traditionally, engineers follow a sequential approach in UAV design, which involves multiple design iterations comprising CAD drawings, material collection, fabrication, flight tests, system identification, modifications, dynamic model extraction, checking if the results meet requirements, and then repeating the process. However, as UAVs become larger, heavier, and more enduring to meet complex system demands, the costs and time associated with each design iteration of creating a new UAV escalate exponentially. The bare-airframe dynamics of the UAV are crucial for engineers to design a controller and validate handling quality and performance. This paper proposes a novel method to accurately predict the dynamic model of the bare airframe for quadrotor UAVs without physically constructing them in the real world. The core concept revolves around converting the quadrotor UAV design from CAD software into a UAV model within an X-Plane simulator. Leveraging the CIFER software’s two key features—frequency domain system identification and parametric model fitting—the unstable bare-airframe dynamics are extracted for both the UAV model in X-Plane and a real-world DJI 450 UAV with the same physical configuration. This paper provides essential parameters and guidance for constructing a 92% high-fidelity dynamic model of the given UAV configuration in X-Plane. The flight test results demonstrate excellent alignment with the simulation outcomes, instilling confidence in the effectiveness of the proposed method for designing and validating new UAVs. Moreover, this approach significantly reduces the time and cost associated with the traditional design process, which requires an actual build of the UAV and many flight tests to verify the performance.

Solar UAVs—More Aerodynamic Efficiency or More Electrical Power?

Solar UAVs (unmanned aerial vehicles) have experienced important development in recent years. The use of solar free energy is not neglected in the present energy crisis, with the intention to move toward green energies. However, an important problem arises concerning the limited amount of solar energy available on board UAVs. Until now, high-aerodynamic-efficiency configurations have been used. These configurations use high-aspect-ratio wings. However, high-aspect-ratio wings have some disadvantages regarding their excessive elasticity and weak bending resistance in the housing section. Additionally, the aircraft maneuverability is reduced. In this work, a study is proposed on a solar UAV configuration that sacrifices high aerodynamic efficiency for a higher surface area available for solar cells. In this manner, the amount of energy available on board the UAV is increased, and the UAV structure becomes more rigid and robust. The presented UAV fits better with more complex evolutions, is more maneuverable and the wingspan is much reduced. This UAV is more compact, can maneuver better in the take-off and landing phases, and the necessary storage space is considerably reduced. This paper highlights the performances that can be achieved using this kind of UAV and explores whether these performances are enough for some applications. Using an on-board energy balance, the possible performances of this new configuration is studied. As this is a preliminary study, the precision level is not very high, but it offers an image concerning the possibilities of this new configuration.

A Computational Investigation of the Hover Mechanism of an Innovated Disc-Shaped VTOL UAV

Inventive approaches are constantly being revealed in the field of vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) configuration concepts and designs. To date, a body-associated configuration of UAVs for augmented lift remains unclear among other approached designs. The current paper investigates the mechanism of a high-lift ducted fan mounted in the central body for VTOL UAV designs. We report an unresolved design of a disc-shaped UAV with a single rotor that aims to enhance the cost-effectiveness of fuel consumption with a substantial contribution of body lift to hover thrust. The convex upper surface curvature was applied to generate a significant lift contribution from the body during hover. The computational fluid dynamics (CFD) approach based on unstructured discretization followed by three-dimensional steady Reynolds-averaged Navier–Stokes (RANS) flow was applied in ANSYS CFX to mechanistically investigate the underlying design considerations. The disc-shaped UAV uses the lip curvature on the duct inlet to generate a vertical force that demonstrates a significant contribution of 95% of the rotor thrust during hovering. The UAV’s upper surface generates prolonged flow entrainment free from momentum losses in swirling flows. This phenomenon is followed by reduced power consumption in hovering and vertical flight, making the UAV aerodynamically stable and environmentally safe.

Application of electrolaminates for the development of biomimetic morphing unmanned aerial vehicles

Morphing aircraft offer the promise of performance that can be optimized for a range of flight profiles. But such capability places challenging demands on the morphing system that cannot easily be met with conventional actuators or smart materials. Electrolaminates use electrostatic forces controlled by the application of a voltage (typically high-voltage but extremely low-current) to controllably bond or unbond layers of a laminated composite structure together. Such on-demand bonding can be used to effectively change the stiffness of the structure or control elongation or twist of the structure. This technology has multiple benefits compared to other smart material or conventional actuator-driven approaches; it is thin and light, has very low energy requirements, and offers rapid response capabilities controlled by simple electronics. These capabilities can enable bio-inspired morphing with large numbers of degrees of freedom and high spatial resolution. We designed, fabricated, and tested a fully functional morphing-wing unmanned aerial vehicle (UAV) with telescoping wings and a splaying, bird-like tail enabled by electrolaminates. Key features of the current UAV configuration include: a variable wingspan of 1.2–2.4 m with a corresponding change in the wing area of nearly a factor of four; no vertical tail; and a horizontal tail area variable by a factor of three. The ability to asymmetrically control the tail area allows for independent pitch and body circulation control. The tail area is changed by a separate electrolaminate clamping mechanism. The variable-area tail uses ‘feathers’ that can be overlapped or splayed as needed. The practical shape-changing is enabled by electrolaminate materials that can rapidly lock the orientation of the feathers. The electrolaminate clutches support more than 5 nm of torque and are sufficient to resist expected flight loads. We also designed, fabricated, and tested other morphing-wing designs enabled by electrolaminate technology to create a wing with smoothly sliding skin that is capable of changing chord and camber with a single linear actuator. Our results suggest that electrolaminates can practically enable bio-inspired, small (Group 1 and 2) morphing UAVs.

A modeling study on water and thermal management and cold startup of unmanned aerial vehicle fuel cell system

The water and thermal management of hydrogen/air proton exchange membrane fuel cell (PEMFC) system in a variable environment and its fast and efficient cold start at low temperature are the key issues in the practical design and integration of unmanned aerial vehicle (UAV) fuel cell power system. Herein, a complete mathematical model of fuel cell stack and balance of plant (BOP) is established, then the nonlinear relationship between cooling water flow rate, coolant bypass valve opening, and stack temperature at different flight altitudes is studied for a typical UAV configuration, and the safe working range of stack is pointed out. In addition, a cold-start model supporting operation at the high current density is proposed. After analyzing the cold start-up process of the fuel cell, it is found that a reduction of active reaction area caused by icing is the main reason for voltage loss. The optimal self-start current densities of the fuel cell at different low temperatures are detected by the galvanostatic method, as a result, a successful self-startup of the fuel cell is achieved at a temperature of 263.15 K.

Design Configuration and Technical Application of Rotary-Wing Unmanned Aerial Vehicles

Due to their advantages in hovering, takeoff and landing adaptability, maneuverability, and other factors, rotary-wing unmanned aerial vehicles (UAVs) are widely applied across many different fields. The UAVs' design and configuration can be quite flexible to fit diverse operation conditions. The major goal of innovations in rotary-wing UAVs is to lower operating risk and expense by optimizing payload and structure layout. This study examines three aspects of rotary-wing UAV design and evolution: the number and arrangement of rotors, hybrid-wing-based UAVs, and configuration and loading structures. The most current advancements of UAV applications in crucial industries, including agriculture, fire rescue, inspection and monitoring, and aerial logistics, are then thoroughly examined. Finally, the authors discussed the prospective uses for rotary-wing UAV design in the future.

Multirotor Unmanned Aerial Vehicle Configuration Optimization Approach for Development of Actuator Fault-Tolerant Structure

Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing the achievable forces and moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns about their service. On the other hand, their design flexibility allows further design optimization for various performance requirements, including actuator failure tolerance. Thus, this study proposed an optimization framework that can be employed to design a novel actuator fault-tolerant multirotor UAV configuration. The approach used an attainable moment set (AMS) to evaluate the achievable moment from a multirotor configuration; similarly, standard deviation geometries (SDG) were employed to define performance requirements. Therefore, given a UAV configuration, actuator fault situation, and SDG derived from the designed mission requirement, the suggested optimization framework maximizes the scaling factor of SDG and fits it into the AMS by adjusting the design parameters up to a sufficient margin. The framework is implemented to optimize selected parameters of the Hexacopter-type of parcel delivery multirotor UAV developed by the PNU drone, and a simulation was conducted. The result showed that the optimized configuration of the UAV achieved actuator fault tolerance and operation-performing capability in the presence of a failed actuator.

Modified Mayfly Algorithm for UAV Path Planning

The unmanned aerial vehicle (UAV) path planning problem is primarily concerned with avoiding collision with obstacles while determining the best flight path to the target position. This paper first establishes a cost function to transform the UAV route planning issue into an optimization issue that meets the UAV’s feasible path requirements and path safety constraints. Then, this paper introduces a modified Mayfly Algorithm (modMA), which employs an exponent decreasing inertia weight (EDIW) strategy, adaptive Cauchy mutation, and an enhanced crossover operator to effectively search the UAV configuration space and discover the path with the lowest overall cost. Finally, the proposed modMA is evaluated on 26 benchmark functions as well as the UAV route planning problem, and the results demonstrate that it outperforms the other compared algorithms.

A Fast and Efficient Attitude Control Algorithm of a Tilt-Rotor Aerial Platform Using Inputs Redundancies

Overactuated multirotor unmanned aerial vehicles (UAVs) usually consist of multiple tiltable thrust actuators. The controllers are mostly designed by regarding the thrust forces and actuator tilting angles as inputs of outer-loop position and attitude controllers, while formulating an inner-loop controller for each actuator to track the thrust and angle as required by the outer-loop. This hierarchical control strategy separates the complicated combined dynamics into two relatively simple systems, and thus simplifies the control design. However, the interaction between the two systems is neglected and therefore the control performance will be degraded when the inner-loop dynamics are not sufficiently fast. This letter investigates the capability of a new overactuated multirotor UAV configuration, where regular quadcopters are passively hinged onto the frame as tiltable thrust actuators. Apart from the thrust force and tilting angle, each actuator has additional auxiliary torque inputs, which exhibit fast responses as they are not subject to the inner-loop actuator tilting angle dynamics. In this letter, an add-on attitude compensation control is designed exploiting the auxiliary inputs to reduce the tracking and disturbance-rejection errors from the nominal control loop. The effectiveness is demonstrated in simulation and verified by experiment.

Quasi-3D Aerodynamic Analysis Method for Blended-Wing-Body UAV Configurations

The current study presents a low-fidelity, quasi-3D aerodynamic analysis method for Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV) configurations. A tactical BWB UAV experimental prototype is used as a reference platform. The method utilizes 2D panel method analyses and theoretical aerodynamic calculations to rapidly compute lift and pitching moment coefficients. The philosophy and the underlying theoretical and semi-empirical equations of the proposed method are extensively described. Corrections related to control surfaces deflection and ground effect are also suggested, so that the BWB pitching stability and trimming calculations can be supported. The method is validated against low-fidelity 3D aerodynamic analysis methods and high-fidelity, Computational Fluid Dynamics (CFD) results for various BWB configurations. The validation procedures show that the proposed method is considerably more accurate than existing low-fidelity ones, can provide predictions for both lift and pitching moment coefficients and requires far less computational resources and time when compared to CFD modeling. Hence, it can serve as a valuable aerodynamics and stability analysis tool for BWB UAV configurations.

Design and Implementation of a Hardware-in-the-Loop Simulation System for a Tilt Trirotor UAV

The tilt trirotor unmanned aerial vehicle (UAV) is a novel aircraft that has broad application prospects in transportation. However, the development progress of the aircraft is slow due to the complicated control system and the high cost of the flight experiment. This work attempts to overcome the problem by developing a hardware-in-the-loop (HIL) simulation system based on a heavily developed and commercially available flight simulator X-Plane. First, the tilt trirotor UAV configuration and dynamic model are presented, and the parameters are obtained by conducting identification experiments. Second, taking the configuration of the aircraft into account, a control scheme composed of the mode transition strategy, hierarchical controller, and control allocation is proposed. Third, a full-scale flight model of the prototype is designed in X-Plane, and an interface program is completed for connecting the autopilot and X-Plane. Then, the HIL simulation system that consists of the autopilot, ground control station, and X-Plane is developed. Finally, the results of the HIL simulation and flight experiments are presented and compared. The results show that the HIL simulation system can be an efficient tool for verifying the performance of the proposed control scheme for the tilt trirotor UAV. The work contributes to narrowing the gap between theory and practice and provides an alternative verification method for the tilt trirotor UAV.

Rechargeable Multi-UAV Aided Seamless Coverage for QoS-Guaranteed IoT Networks

Due to their high flexibility, high maneuverability, and line-of-sight (LOS) predominant channel, unmanned aerial vehicles (UAVs) serving as flying base stations have received a lot of interest in emerging Internet of Things (IoT) networks. This article studies the energy-efficient cooperative strategy of rechargeable multi-UAVs for providing seamless coverage and long-term information services for IoT nodes. Considering the limited cruising duration of the UAV, multiple rechargeable UAVs are capable of constructing a closed chain for the sake of alternately supporting IoT nodes. Moreover, a joint IoT node assignment and UAV configuration optimization problem is proposed in order to maximize the energy efficiency of the system. Since the proposed problem is a mixed-integer nonconvex problem, we divide it into three subproblems, namely, node assignment scheduling, UAV trajectory planning, and transmit power control. By exploiting sequential convex optimization techniques, we reformulate the nonconvex subproblems into three convex optimization problems which can be solved within the polynomial time. A block coordinate descent-based iterative algorithm is proposed for solving these energy-efficiency oriented subproblems. Finally, the simulation results corroborate the effectiveness of our proposed method.