Flight Maneuvers Research Articles

A twist of the tail in turning maneuvers of bird-inspired drones.

A banked turn is a common flight maneuver observed in birds and aircraft. To initiate the turn, whereas traditional aircraft rely on the wing ailerons, most birds use a variety of asymmetric wing-morphing control techniques to roll their bodies and thus redirect the lift vector to the direction of the turn. Nevertheless, when searching for prey, soaring raptors execute steady banked turns without exhibiting observable wing movements apart from the tail twisting around the body axis. Although tail twisting can compensate for adverse yaw, functioning similarly to the vertical tail in aircraft, how raptors use only tail twisting to perform banked turns is still not well understood. Here, we developed and used a raptor-inspired feathered drone to find that the proximity of the tail to the wings causes asymmetric wing-induced flows over the twisted tail and thus lift asymmetry, resulting in both roll and yaw moments sufficient to coordinate banked turns. Moreover, twisting the tail induces a nose-up pitch moment that increases the angle of attack of the wings, thereby generating more lift to compensate for losses caused by the banking motion. Flight experiments confirm the effectiveness of tail twist to control not only low-speed steady banked turns but also high-speed sharp turns by means of coordinated tail twist and pitch with asymmetric wing shape morphing. These findings contribute to the understanding of avian flight behaviors that are difficult to study in controlled laboratory settings and provide effective control strategies for agile drones with morphing aerial surfaces.

Optimal Periodic Control of Unmanned Aerial Vehicles Based on Fourier Integral Pseudospectral and Edge-Detection Methods

The endurance of unmanned aerial vehicles (UAVs) is a critical factor in expanding the scope of their applications. Extended flight times enable UAVs to undertake longer missions, cover larger areas and perform tasks such as persistent surveillance, data collection and search and rescue operations. Optimal trajectory planning is a cost-effective method to significantly enhance UAV endurance and performance by minimizing fuel consumption. This study introduces a novel numerical optimization framework to maximize UAV endurance. Specifically, we address the problem of determining optimal thrust and cruise angle of attack for a UAV in 2D space under specific initial, periodic and boundary conditions. By normalizing the free final time optimal control problem and employing Fourier collocation and quadrature, we transform it into a nonlinear programming problem. A key contribution of this work is accurately detecting and reconstructing the thrust history, including jump discontinuities, directly from Fourier pseudospectral data without smoothing techniques. The proposed method outperforms existing approaches in solving the periodic energy-optimal path planning problem for UAVs, as it effectively reconstructs the bang-bang thrust profile, facilitating rapid and efficient thrust adjustments essential for various flight maneuvers. Furthermore, the algorithm aligns with the UAV model, ensuring seamless integration into real-world control systems. The method’s independence from prediction horizon length, due to the use of Fourier collocation on the normalized interval [Formula: see text], is a notable advantage. This characteristic offers potential for future applications in various fields involving nonsmooth optimal control problems. This research generally provides a valuable tool for researchers and engineers working on UAV design and operation, paving the way for more efficient and effective UAV systems.

Use of Simulation for Pre-Training of Drone Pilots

This study investigates the effectiveness of simulator-based training systems in enhancing human drone piloting skills and performance. The study utilized a true-experimental research design to assess the impact of simulation training on accuracy, efficiency, and workload perception among human drone pilots. Leveraging historical simulation practices in conventional crewed aviation and incorporating instructivist educational principles, this research evaluates the potential for structured simulator training to improve real-world drone operation proficiency. Performance evaluation was focused upon the precision with which the participants were able to return the aircraft to a defined point in space after conducting a standard flight maneuver. Results indicate a significant improvement in flight performance among participants undergoing simulator training, reflected in a 32% reduction in mean final displacement. This highlights the value of integrating advanced simulation technologies and instructivist methodologies into drone pilot training programs to meet the evolving needs of both industry and academia.

Effect of geometric variations on the wing rock of blended wing–body aircraft

Blended wing–body configurations are anticipated to dominate future transport and military aerospace designs. The departure of the conventional tube-wing configuration has opened several areas of investigation. These designs are susceptible to lateral instability during landing, takeoff, and maneuvering flight despite having improved aerodynamics because of their tailless nature. One of these instabilities, Wing-Rock, poses significant performance and operational difficulties and can potentially cause crashes. Though experimental and numerical studies of the aerodynamics and stability of blended wing–body configurations have been conducted, wing-rock characteristics still need to be identified in the literature. This research aims to investigate these characteristics at low subsonic speeds with varying outboard sweep and geometric twist angles. The study includes a numerical approach based on the rigid body free-vibration method in single roll degree of motion, which uses three-dimensional unsteady Reynolds’ Average Navier Stokes equations, and an analytical approach based on the multiple time scale method, which captures the crucial aspect of the wing rock system. The findings show that the geometrical parameters significantly impact the wing rock characteristics, which are unique to such novel tailless designs.

Avian-inspired embodied perception in biohybrid flapping-wing robotics

Avian feather intricate adaptable architecture to wing deformations has catalyzed interest in feathered flapping-wing aircraft with high maneuverability, agility, and stealth. Yet, to mimic avian integrated somatic sensation within stringent weight constraints, remains challenging. Here, we propose an avian-inspired embodied perception approach for biohybrid flapping-wing robots. Our feather-piezoelectric mechanoreceptor leverages feather-based vibration structures and flexible piezoelectric materials to refine and augment mechanoreception via coupled oscillator interactions and robust microstructure adhesion. Utilizing convolutional neural networks with the grey wolf optimizer, we develop tactile perception of airflow velocity and wing flapping frequency proprioception. This method also senses pitch angle via airflow direction and detects wing morphology through feather collisions. Our low-weight, accurate perception of flapping-wing robot flight states is validated by motion capture. This investigation constructs a biomechanically integrated embodied perception system in flapping-wing robots, which holds significant promise in reflex-based control of complex flight maneuvers and natural bird flight surveillance.

Monitoring pilot trainees’ cognitive control under a simulator-based training process with EEG microstate analysis

The objective of pilot training is to equip trainees with the knowledge, judgment, and skills to maintain control of an aircraft and respond to critical flight tasks. The present research aims to investigate changes in trainees’ cognitive control levels during a pilot training process while they underwent basic flight maneuvers. EEG microstate analysis was applied together with spectral power features to quantitatively monitor trainees’ cognitive control under varied flight tasks during different training sessions on a flight simulator. Not only could EEG data provide an objective measure of cognitive control to complement the current subjective assessments, but the application of EEG microstate analysis is particularly well-suited for capturing rapid dynamic changes in cognitive states that may happen under complex human activities in conducting flight maneuvers. Comparisons were conducted between two types of tasks and across different training stages to monitor how pilot trainees’ cognitive control responds to varied flight task types and training stages. The present research provides insights into the changes in trainees’ cognitive control during a pilot training process and highlights the potential of EEG microstate analysis for monitoring cognitive control.

Load spectra of a light unmanned aircraft – data recording frequencies and resulting measurement variations

The article focuses on the load spectrum of a lightweight unmanned aircraft. It examines the impact of load signal sampling frequency on the load spectrum derived from the load signal. The flight sessions followed two scenarios: a maneuvering flight causing a wide range of load factor variations and a calm photogrammetric flight. The recorded load signals from two types of sensors were initially rescaled into load factor time series, with an optional signal smoothing process. These series were then downsampled by selecting every nth term, resulting in load factor sequences recorded at a lower frequency. Next, all sequences were transformed into sequences of local extremes of the Load Levels, resulting from quantifying the operational load variability into 32 intervals. Two options were considered: without filtering or with filtering of sequential pairs of terms generating small Load Level increments. Subsequently, the Rainflow Counting algorithm was applied, producing 32x32 load half-cycle arrays. Based on these arrays, incremental load spectra were calculated. The study provides a detailed comparison of load spectra for different load signal sources and recording frequencies. Additionally, calculations of the fatigue life of a structural element subjected to various load spectra were performed, leading to the formulated conclusions.

Crack Growth Analytical Model Considering the Crack Growth Resistance Parameter Due to the Unloading Process

Crack growth analysis is essential for probabilistic damage tolerance assessment of aeroengine life-limited parts. Traditional crack growth models directly establish the stress ratio–crack growth rate or crack opening stress relationship and focus less on changes in the crack tip stress field and its influence, so the resolution and accuracy of maneuvering flight load spectral analysis are limited. To improve the accuracy and convenience of analysis, a parameter considering the effect of unloading amount on crack propagation resistance is proposed, and the corresponding analytical model is established. The corresponding process for acquiring the model parameters through the constant amplitude test data of a Ti-6AL-4V compact tension specimen is presented. Six kinds of flight load spectra with inserted load pairs with different stress ratios and repetition times are tested to verify the accuracy of the proposed model. All the deviations between the proposed model and test life results are less than 10%, which demonstrates the superiority of the proposed model over the crack closure and Walker-based models in addressing relevant loading spectra. The proposed analytical model provides new insights for the safety of aeroengine life-limited parts.

Advancements in UAV Path Planning: A Deep Reinforcement Learning Approach with Soft Actor-Critic for Enhanced Navigation

This paper tackles the intricate challenge of autonomous navigation for Unmanned Aerial Vehicles (UAVs) through dynamically changing environments. We focus on a sophisticated Deep Reinforcement Learning (DRL) approach using the Soft Actor-Critic (SAC) algorithm, optimized for UAV path planning within a continuous action space. This methodology leverages environmental image data to enhance the precision of flight maneuvers and effective obstacle avoidance. Our approach, validated through extensive simulations in Gazebo and field tests, demonstrates the algorithm’s efficacy in enabling UAVs to adeptly navigate obstacles using depth maps. The study further explores the robustness of the SAC algorithm by comparing it with traditional DRL methods, emphasizing its superior performance in real-world applications. This research contributes significantly to advancing UAV technology, particularly in autonomous motion planning, by integrating cutting-edge machine learning techniques. The video link is: https://www.youtube.com/watch?v=Nd_aMzejNXY .

Investigating Propellers for Drone Applications: Analyzing Varied Designs and Characteristics

The importance of drones has evidently increased in various aspects of daily life, such as defense, agriculture, disaster management, and more. Drone propellers are crucial for generating the lift and propulsion necessary for steady flight. Efficient propeller design is critical for maximizing flight time and maneuverability in drones. We are currently investigating the impact of different propeller designs on drone performance. Our research focuses on optimizing propeller characteristics to ensure optimal propulsion and overall functionality. By testing three airfoil designs and systematically varying the angle of attack and pitch, we aim to understand how these changes influence the propeller's efficiency and effectiveness. The CFD-based analysis primarily evaluates parameters such as the lift-to-drag ratio and RPM to determine the most suitable design for drone operations. Through extensive analysis and data collection, the study seeks to identify settings that balance performance metrics, ultimately enhancing the drone's functionality. Based on insights from the analysis, various iterations and refinements have been carried out to draw informed conclusions about the most effective propeller design for drone applications.

An UAV system for visual inspection and wall thickness measurements in ship surveys

This article presents the development of a UAV system designed to perform visual inspections and thickness measurements in ships’ cargo tanks. That includes the conception and evolution of the different components and subsystems of this UAV system and several tests, including some carried out in actual operating conditions. It also presents a near-wall positioning and propulsion system designed and developed to improve stability and avoid collisions. The paper also describes an articulated arm designed around an EMAT probe for wall thickness measurement. The measurement chain developed for this purpose includes all the electronics and computing necessary to send data in real-time to a ground station. Flying near walls poses challenges that compromises accuracy when approaching each measurement target points. Therefore, the wall approach and departure flight maneuvers are fully automatic. That facilitates and speeds up the inspection task that may require measurements on thousands of locations specified by the surveyor. The proposed UAV system aims to automate and improve the long and expensive surveys and inspections in the marine industry by reducing their time and costs.

Deep Embedding Koopman Neural Operator-Based Nonlinear Flight Training Trajectory Prediction Approach

Accurate flight training trajectory prediction is a key task in automatic flight maneuver evaluation and flight operations quality assurance (FOQA), which is crucial for pilot training and aviation safety management. The task is extremely challenging due to the nonlinear chaos of trajectories, the unconstrained airspace maps, and the randomization of driving patterns. In this work, a deep learning model based on data-driven modern koopman operator theory and dynamical system identification is proposed. The model does not require the manual selection of dictionaries and can automatically generate augmentation functions to achieve nonlinear trajectory space mapping. The model combines stacked neural networks to create a scalable depth approximator for approximating the finite-dimensional Koopman operator. In addition, the model uses finite-dimensional operator evolution to achieve end-to-end adaptive prediction. In particular, the model can gain some physical interpretability through operator visualization and generative dictionary functions, which can be used for downstream pattern recognition and anomaly detection tasks. Experiments show that the model performs well, particularly on flight training trajectory datasets.

Enhancing Longitudinal Flight Performance of Drones through the Coupling of Wings Morphing and Deflection of Aerodynamic Surfaces

In nature, gliding birds frequently execute intricate flight maneuvers such as aerial somersaults, perched landings, and swift descents, enabling them to navigate obstacles or hunt prey. It is evident that birds rely on different wing–tail configurations to accomplish a wide range of aerial maneuvers. For traditional fixed‐wing unmanned aerial vehicles (UAVs), pitch control primarily comes from the tail's elevators, while adjusting flight lift and drag involves deploying wing flaps. Although these designs ensure reliable flight, they compromise the drones’ maneuverability to maintain longitudinal stability. Therefore, the study introduces a biomimetic morphing wing UAV, and presents a pitch control strategy that simultaneously engages morphing wings, ailerons, and tail elevators. The pull‐up maneuver tests indicate that the proposed control method results in a pitch rate that is approximately 2.5 times greater than when using only the elevator control. A closed‐loop control system for the drone is also established. The closed‐loop flight experiment, which tracks a 45° pitch angle, demonstrates the effectiveness of the proposed coupled control method in adjusting the flight attitude. In addition, during cruising, the UAV employs three configurations, straight wing, forward‐swept wing, and back‐swept wing, to cater to different mission objectives and augment its flight capabilities.

Vibration characteristics of dual-rotor system with staggered-type double elastic ring squeeze film dampers under maneuvering flight

The vibration of the rotor system is significantly intensified during maneuvering flight, rendering traditional elastic ring squeeze film dampers (ERSFDs) insufficient or unstable. To improve the applicability of dampers, a novel structure of staggered-type double elastic ring squeeze film dampers (SDERSFD) is proposed in this paper. Through the synergistic effect of double elastic rings, the damping effect is significantly enhanced, and the circumferential stiffness anisotropy of the damper is improved, which is more suitable for vibration reduction requirements under complex working conditions. Utilizing the Reynolds equation, the internal and external pressure field control equations of the double elastic rings are established. The finite difference method is then employed to solve the dynamic characteristics of the damper. Additionally, a finite element model of the dual-rotor system with SDERSFDs considering complex dynamic factors such as unbalanced force, oil film force, gravity, and additional inertial force caused by maneuvering flight is established for the study of nonlinear rotor dynamic characteristics and the analysis of SDERSFDs vibration reduction effect. Based on the model, the influence of various factors such as maneuvering speed, maneuvering radius, rotor speed and unbalance on the transient response of dive-pull up condition is analyzed. The results reveal that during dive-pull up, the vibration of the rotor system intensifies significantly. When compared with the ERSFDs, the SDERSFDs effectively reduce the vibration amplitudes of the rotor system under maneuvering flight condition, achieving the maximum vibration reduction ratio of 48.9%. Furthermore, the SDERSFD exhibits robustness against large maneuvering loads, enhancing the stability of the rotor system under extreme conditions.

The future and technique challenges of high-speed ground effect vehicle enrolled in maritime transportation

This paper presents a high-speed ground effect vehicle (HS-GEV) used specifically for maritime transportation. Given the limitations of current vessels, including various types of watercraft and high-speed boats, in fulfilling of needs in different maritime transportation scenarios, the HS-GEV emerges as a promising solution to address unmet requirements. To efficiently accomplish maritime transportation missions with quickness and safety, several critical features are emphasized, including short take-off on water, flight maneuverability and flight stability. The key techniques required to achieve these features, as well as recent progress highlights, are introduced. Following and promoting these crucial techniques is also suggested as a future step to improve HS-GEV performance. With its predominant features, the HS-GEV holds immense application value in enhancing a high-speed maritime transportation system that aligns with the evolving needs of the real world.

Pilot fatigue evaluation with the method of weight TOPSIS

Abstract Fatigue is significant to many aviation accidents, so assessing pilot fatigue is critical to aviation safety. Traditional fatigue risk assessment studies often ignore the impact of difficult flight maneuvers on pilot fatigue. The study sought to develop a fatigue risk indicator system that could be integrated with airline data systems to achieve a more accurate assessment of pilot fatigue. The questionnaire content was determined by literature collection and methods, and 128 civil aviation pilots were surveyed by questionnaire. The influence of pilot scheduling, workload, working environment and other specific indicators on pilot fatigue was evaluated by Weight TOPSIS analysis method. Then the model is used to evaluate pilot fatigue for practical scheduling problems. The study found that lack of rest time, long working hours and red-eye flights were the most common causes of pilot fatigue. In practice, the fatigue evaluation system can be combined with the database information of the airline to help the airline rationally arrange the flight, minimize the fatigue index and ensure the safety.

Robust Geometric Control for a Quadrotor UAV with Extended Kalman Filter Estimation

This study proposes a robust geometric controller tailored for quadrotor unmanned aerial vehicles (UAVs). The original geometric controller exhibits excellent performance in quadrotor UAV maneuvers. However, as a model-based nonlinear control method, it is sensitive to system model parameters. By integrating a novel extended Kalman filter (EKF)-based estimator for real-time, online estimation of the quadrotor’s inertia parameters, the controller adeptly handles internal uncertainties and external perturbations during flight maneuvers. This approach significantly improves the robustness of the control system against model inaccuracies. Empirical evidence is provided through both simulation and extensive real-world flight tests, demonstrating the controller’s effectiveness and its practical applicability in dynamic environments. The results confirm that this integration substantially enhances system reliability and performance under varied operational conditions.

Current Status and Development Trends of Morphing Wing of Aircraft

Abstract:: Aircraft morphing wings, also known as adaptive wings or shape-variable wings, represent a revolutionary development in the field of aerospace engineering. Inspired by the adaptability observed in birds and insects during flight, researchers have been exploring potential applications of morphing wing technology to enhance the performance and efficiency of aircraft. This innovative technology holds the promise of improving aerodynamic efficiency, reducing fuel consumption, and enhancing overall flight maneuverability. This manuscript aims to explore and analyze the potential applications and effects of morphing wing technology for aircraft. Furthermore, this paper aims to gain an in-depth understanding of the principles and implications of morphing wing technology for aircraft and to assess its potential advantages in terms of flight performance, handling characteristics, and energy efficiency. Based on different driving mechanisms, patents related to aircraft morphing wings were systematically categorized and summarized, highlighting the most typical intra-wing and extra-wing deformations. Through an examination of patents related to aircraft morphing wings, various morphing wing technologies' unique characteristics were summarized. A comparative analysis of different deformation methods revealed their respective strengths and limitations. The paper concludes with a summary of current technical challenges facing morphing wing technology and a forward-looking exploration of its future trends and directions. Categorizing aircraft morphing wings into intra-wing and extra-wing deformations based on the method of deformation, this paper elaborates on the operational principles, advantages, and limitations of these two categories. Compared to traditional fixed wings, morphing wings exhibit superior flight performance, and it is anticipated that more patents will be developed in the future.

Flows past airfoils for the low-Reynolds number conditions of flying in Martian atmosphere

Fixed-wing aircraft with potential for long-duration flight and efficient manoeuvrability is expected to be the next frontier of Mars surface exploration. However, the feasibility of such an aircraft demands for wing airfoil suitable for low Reynolds flight conditions. In this framework, the paper deals with the computational study of two wing sections specifically designed for Mars exploration aircraft. Two-dimensional steady Reynolds-averaged Navier–Stokes simulations, using the computational fluid dynamics tool SU2 with the γ−Reθ transition model and the XFoil panel flow solver, are performed to address airfoils’ aerodynamics. Computational tools are validated by simulating flow past the Eppler 387 airfoil at Re∞=60×103, and comparing the results with experimental data collected in wind tunnel experiments. Aerodynamic performances of optimal wing sections are investigated at Re∞=3.4×104 by considering pressure coefficients and skin friction coefficients. The application of a literature-based correlation, specifically tailored to identify transition and reattachment locations, is extended to separation point detection. Computational Fluid Dynamics analysis conducted on the studied airfoils revealed that separation occurs within the laminar regime. Additionally, examination of turbulent shear stresses highlighted the role of airfoil curvature in counterbalancing the suction defect produced by the laminar separation bubble. This curvature-induced effect was found to play a crucial role in optimizing airfoil efficiency.

Aggressive flight control of quadrotors using incremental nonlinear dynamic inversion with a high-fidelity thrust unit model

The application of quadrotors has been expanded into aggressive tasks such as military confrontation and aerobatics shows, making it crucial to enhance flight maneuverability to adapt to rapid and large-scale command changes. Unlike hovering or low-speed modes, aggressive flight exacerbates quadrotor model uncertainty, making it challenging for controllers to balance response speed and robustness. This paper proposes an INDI control method that integrates a high-fidelity thrust model unit to address this practical need. First, based on the pole distribution theory and the application of INDI on quadrotors, it is concluded that the dynamic response of quadrotor flight is impacted by the accuracy of the thrust model. Second, consider the airflow velocity and angles, the high-fidelity modeling approach, and the aerodynamic forces and torque expression validated through wind tunnel experiments are provided. Then the flight controller for the quadrotor is designed with the established high-fidelity thrust unit model. Finally, aggressive trajectory-tracking flight tests are set to evaluate the improvement of our work. The results demonstrate that our proposed method indeed enhances the response speed and tracking accuracy, as well as the flight stability of the quadrotor.