Flight Mechanics Research Articles

USTButterfly: A Servo-Driven Biomimetic Robotic Butterfly

Different from birds, bats, flies, and other flying creatures that generate propulsions by flapping a pair of wings, butterflies with two pairs of wings have their peculiar flight aerodynamics. In this paper, a servo-driven biomimetic robotic butterfly, named USTButterfly, is designed to study the flight mechanism of biological butterflies. First, instead of using a single actuator to drive two pairs of wings, two servos are introduced to independently drive the left and right wings, thereby realizing tailless control of the robotic butterfly. Next, a bionic airfoil is designed inspired by the wing structure of the Glasswing butterfly. Wing geometry analysis indicates that USTButterfly well matches the morphological characteristics of biological butterflies. Finally, a multi-camera motion capture system is used to measure the flight characteristics of the robotic butterfly, and the results demonstrate that despite a larger Reynolds number, USTButterfly shares a similar coupled wing-bsody interaction with biological butterflies in the climbing flight. USTButterfly opens up a new way to study the flight specializations of biological butterflies, and offers a potential alternative paradigm for existing unmanned aerial vehicles.

Design and motion analysis of a space crank rocker biomimetic aircraft

Abstract In order to better understand the flight performance and kinematics performance of flapping wing aircraft designed and developed based on the principle of bionics, a space crank rocker mechanism was tried to carry out the virtual prototype design of the bionic aircraft in space motion, and on this basis, its movement characteristics were analyzed. Analyzing the flight mechanisms and scale laws of common flying organisms yields various physical estimation parameters that affect flight characteristics. Flight patterns and motion patterns are analyzed based on the design principles of seabirds, and structural designs and mathematical models are established. Secondly, carry out the design of its flapping and transmission structures, and based on this, carry out the overall structural design and establish a three-dimensional model. Here, the kinematics analysis of its flapping amplitude and angular velocity value is carried out by combining its mechanism motion diagram, and the kinematics simulation results are compared with the theoretical results, which proves the correctness of the theoretical analysis and the feasibility of the design structure.

An optimization method for wireless sensor networks coverage based on genetic algorithm and reinforced whale algorithm.

In response to the problem of coverage redundancy and coverage holes caused by the random deployment of nodes in wireless sensor networks (WSN), a WSN coverage optimization method called GARWOA is proposed, which combines the genetic algorithm (GA) and reinforced whale optimization algorithm (RWOA) to balance global search and local development performance. First, the population is initialized using sine map and piecewise linear chaotic map (SPM) to distribute it more evenly in the search space. Secondly, a non-linear improvement is made to the linear control factor 'a' in the whale optimization algorithm (WOA) to enhance the efficiency of algorithm exploration and development. Finally, a Levy flight mechanism is introduced to improve the algorithm's tendency to fall into local optima and premature convergence phenomena. Simulation experiments indicate that among the 10 standard test functions, GARWOA outperforms other algorithms with better optimization ability. In three coverage experiments, the coverage ratio of GARWOA is 95.73, 98.15, and 99.34%, which is 3.27, 2.32 and 0.87% higher than mutant grey wolf optimizer (MuGWO), respectively.

A combined ant colony optimization with Levy flight mechanism for the probabilistic traveling salesman problem with deadlines

In this paper, we are interested in the Probabilistic Traveling Salesman Problem with Deadlines (PTSPD) where clients must be contacted, in addition to their random availability before a set deadline. The main objective is to find an optimal route that covers a random subset of visitors in the same order as they appear on the tour, attempting to keep the path as short as possible. This problem is regarded as being ♯P-hard. Ant Colony Optimization (ACO) has been frequently employed to resolve this challenging optimization problem. However, we suggest an enhanced ACO employing the Levy flight algorithm in this study. This allows some ants to take longer jumps based on the Levy distribution, helping them escape from local optima situations. Our computational experiments using standard benchmark datasets demonstrate that the proposed algorithm is more efficient and accurate than traditional ACO.

Early and accumulated experience shape migration and flight in Egyptian vultures

Two types of experience affect animals' behavioral proficiencies and, accordingly, their fitness: early-life experience, an animal's environment during its early development, and acquired experience, the repeated practice of a specific task.1,2,3,4,5,6,7,8 Yet, how these two experience types and their interactions affect different proficiencies is still an open question. Here, we study the interactions between these two types of experience during migration, a critical and challenging period.9,10 We do so by comparing migratory proficiencies between birds with different early-life experiences and explain these differences by testing fine-scale flight mechanisms. We used data collected by GPS transmitters during 127 autumn migrations of 65 individuals to study the flight proficiencies of two groups of Egyptian vultures (Neophron percnopterus), a long-distance, soaring raptor.11,12 The two groups differed greatly in their early-life experience, one group being captive bred and the other wild hatched.13 Both groups improved their migratory performance with acquired experience, exhibiting shorter migration times, longer daily progress, and improved flight skills, specifically more efficient soaring-gliding behavior. The observed improvements were mostly apparent for captive-bred vultures, which were the least efficient during their first migration but were able to catch up in their migratory performance already in the second migration. Thus, we show how the strong negative effects of early-life experience were offset by acquired experience. Our findings uncover how the interaction between early-life and acquired experiences may shape animals' proficiencies and shed new light on the ontogeny of animal migration, suggesting possible effects of sensitive periods of learning on the acquisition of migratory skills.

Quantitative analysis of millet mixtures based on terahertz time-domain spectroscopy and improved coati optimization algorithm

The significant difference in economic and nutritional value between new and old cereals has led to a plethora of grain mix-ups on the market, and it is necessary to distinguish the old and new grains accurately and quickly. In this study, millet, which has high economic and nutritional value in cereals, was used as the research object. Terahertz time domain spectroscopy combined with chemometrics was used to detect its mixture. The experimental findings show that, compared to the partial least squares regression model, and the support vector regression models optimized by particle swarm and grid algorithms, the support vector regression model optimized by the coati optimization algorithm (COA) exhibits superior performance. In order to further improve the prediction accuracy of the support vector regression model, an improved COA was proposed. The quality and diversity of the initial population are improved by introducing chaotic mapping, tent mapping, and opposition based learning mechanisms, followed by the introduction of adaptive weights and Wright flight mechanisms, which enhance the flexibility and convergence speed of the algorithm, and finally, the introduction of the sine-cosine algorithm to improve the search range. The experiments demonstrate that a support vector regression model optimized by an enhanced coati’s algorithm provides superior quantitative analysis of millet mixtures as compared to other models tested. The optimized model achieves high prediction accuracy, with correlation coefficients reaching 0.9872 and 0.9742 for millet mixtures with gradient ratios of 10% and 2%, respectively. This research provides technical support and a reference for rapid, nondestructive quantitative detection of millet mixtures while opening up new possibilities for subsequent quantitative detection of other cereals.

High-Speed Virtual Flight Testing Platform for Performance Evaluation of Pitch Maneuvers

To research serious nonlinear coupling problems among aerodynamics, flight mechanics, and flight control during high maneuvers, a virtual flight testing platform has been developed for a large-scale, high-speed wind tunnel, based on the real physical environment, and it can significantly mitigate risks and reduce the costs of subsequent flight tests. The platform of virtual flight testing is composed of three-degrees-of-freedom model support, measuring devices for aerodynamic and motion parameters, a virtual flight control system, and a test model. It provides the ability to realistically simulate real maneuvers, investigate the coupling characteristics of unsteady aerodynamics and nonlinear flight dynamics, evaluate flight performance, and verify the flight control law. The typical test results of a pitch maneuver with open-loop and closed-loop control are presented, including a one-degree-of-freedom pitch motion and a two-degrees-of-freedom pitch and roll motion. The serious pitch and roll-coupled motion during a pitch maneuver at a high angle of attack is revealed, and the flight control law for decoupled control is successfully verified. The comparison of the test results and the flight data of a real pitch maneuver proves the reliability and capability of virtual flight testing.

Numerical Investigation of an Unmanned Aerial Vehicle Launch from Military Transport Aircrafts

Launching a fixed-wing unmanned aerial vehicle (UAV) out of the cargo hold of a flying transport aircraft (TA) is numerically investigated. A numerical tool chain is established to capture the dynamic motion of the UAV during launch, in which the DLR-TAU Code flow solver is coupled with a flight mechanics tool. A parameter study investigates how the UAV launch speed, position, and orientation relative to the loading platform of two different TAs affect its trajectory and aerodynamic behaviors. Furthermore, the influence of the angle of attack of the TA on the UAV trajectory and pitch angle is analyzed. This information will help design a launch mechanism that ensures a safe separation and aerodynamically stable flight after launch.

Structural damage detection based on modal strain energy assurance criterion using adaptive region shrinkage assisted IGOA

The efficiency in high-dimension optimization, premature convergence and noise robustness are common challenges that restrict the application of swarm-based algorithms in structural damage detection (SDD). In order to overcome these limitations, an improved grasshopper optimization algorithm (IGOA) based SDD approach assisted with adaptive region shrinkage strategies is proposed using modal strain energy assurance criterion. Firstly, the effectiveness of GOA in handling SDD is investigated, and an improved version is subsequently introduced with two adaptive region shrinkage strategies: adaptive Lévy flight mechanism and elite opposition-based learning, aiming to achieve more accurate and stable SDD results. Additionally, a novel objective function is defined, combining the frequency change ratio (FCR) and modal strain energy assurance criterion (MSEAC). To assess the performance of the proposed algorithm, a comparative analysis is conducted with four other selected swarm intelligent algorithms and GOAs with individual modification using four CEC benchmark functions. The results demonstrate that the proposed algorithm achieves improved convergence rate and accuracy. Furthermore, the effectiveness and efficiency of the proposed algorithm in SDD are validated through two numerical simulations and an experimental test. The SDD results obtained from both numerical simulations and experimental tests confirm the accuracy and robustness of the proposed method.

Design and flight test of the fixed-flapping hybrid morphing wing aerial vehicle

Bionic aircrafts have become a hot topic in the research on unmanned aerial vehicles (UAVs). By mimicking the flight mechanics and wing morphology of living organisms, bionic aircraft not only improve aerodynamic performance, stealth, and convenience but also enable single aircraft to complete multiple specific tasks. To further improve the practical performance of bionic aircraft, a fixed-flapping hybrid morphing wing aerial vehicle (F-FWAV) is designed, and the aerodynamic and flight mechanics are studied. First, kinematic simulations are conducted on the designed F-FWAV, and the kinematic characteristics of the flapping wing are analyzed. Then, flight tests are conducted on the aircraft model, and time-domain and frequency-domain analyses were performed on the data of the pitch angle and roll angle during level flight, high angle of attack (AOA) maneuvering and landing, indicating that the pitch and roll angles of the F-FWAV are coupled. CFD numerical simulations are used to obtain the cruise points of the F-FWAV under different AOAs, frequencies, and freestream velocities. The results of the mutual interference between the fixed wing and flapping wing sections show that the flapping wing section provides more than 50 % of the lift of the entire flight process, and the downward flapping movement of the flapping wing section increases the edge vortex of the fixed wing section, thereby increasing the lift of the fixed wing section.

A hull reconstruction-reprojection method for pose estimation of free-flying fruit flies.

Understanding the mechanisms of insect flight requires high-quality data of free-flight kinematics, e.g. for comparative studies or genetic screens. Although recent improvements in high-speed videography allow us to acquire large amounts of free-flight data, a significant bottleneck is automatically extracting accurate body and wing kinematics. Here, we present an experimental system and a hull reconstruction-reprojection algorithm for measuring the flight kinematics of fruit flies. The experimental system can automatically record hundreds of flight events per day. Our algorithm resolves a significant portion of the occlusions in this system by a reconstruction-reprojection scheme that integrates information from all cameras. Wing and body kinematics, including wing deformation, are then extracted from the hulls of the wing boundaries and body. This model-free method is fully automatic, accurate and open source, and can be readily adjusted for different camera configurations or insect species.

Impact of DGs on the Reactive Power-Supported Optimal EDN for Profit Maximisation

Significant issues such as high-Power Loss (PLoss) and drop in node voltages in Electric Distribution Networks (EDNs) can be well mitigated using renowned techniques such as Alteration of Electric Distribution Network Switches (AEDNS), Optimal Capacitor Support (OCS), and Integration of Dispersed Generation (IDG), which are identified as the most economical and efficient approaches. This study presents the optimisation of AEDNS with and without OCS considering four different scenarios to maximise the profit through reduction in PLoss, which is regarded as the first-step process. To further increase profit, IDG was integrated into the EDNs after the combined optimisation of OCS and AEDNS. In this work, Levy Flight Mechanism (LFM) was incorporated into the Seagull Optimisation Algorithm (SOA) and applied to solve the objective function based on economics. The effectiveness of the presented methodology was evaluated and confirmed using a real 59-bus in Cairo, Egypt, EDN, as well as a conventional 33-bus test system. For each scenario, the PLoss reductions and net profit of the proposed methodology were contrasted with those obtained from previously reported approaches. The collected findings show that by optimising AEDNS, OCS, and IDG, the established methodology effectively yields more economic gain for all scenarios.

Wandering albatrosses exert high take-off effort only when both wind and waves are gentle

The relationship between the environment and marine animal small-scale behavior is not fully understood. This is largely due to the difficulty in obtaining environmental datasets with a high spatiotemporal precision. The problem is particularly pertinent in assessing the influence of environmental factors in rapid, high energy-consuming behavior such as seabird take-off. To fill the gaps in the existing environmental datasets, we employed novel techniques using animal-borne sensors with motion records to estimate wind and ocean wave parameters and evaluated their influence on wandering albatross take-off patterns. Measurements revealed that wind speed and wave heights experienced by wandering albatrosses during take-off ranged from 0.7 to 15.4 m/s and 1.6 to 6.4 m, respectively. The four indices measured (flapping number, frequency, sea surface running speed, and duration) also varied with the environmental conditions (e.g., flapping number varied from 0 to over 20). Importantly, take-off was easier under higher wave conditions than under lower wave conditions at a constant wind speed, and take-off effort increased only when both wind and waves were gentle. Our data suggest that both ocean waves and winds play important roles for albatross take-off and advances our current understanding of albatross flight mechanisms.

Wandering albatrosses exert high take-off effort only when both wind and waves are gentle.

The relationship between the environment and marine animal small-scale behavior is not fully understood. This is largely due to the difficulty in obtaining environmental datasets with a high spatiotemporal precision. The problem is particularly pertinent in assessing the influence of environmental factors in rapid, high energy-consuming behavior such as seabird take-off. To fill the gaps in the existing environmental datasets, we employed novel techniques using animal-borne sensors with motion records to estimate wind and ocean wave parameters and evaluated their influence on wandering albatross take-off patterns. Measurements revealed that wind speed and wave heights experienced by wandering albatrosses during take-off ranged from 0.7 to 15.4 m/s and 1.6 to 6.4 m, respectively. The four indices measured (flapping number, frequency, sea surface running speed, and duration) also varied with the environmental conditions (e.g., flapping number varied from 0 to over 20). Importantly, take-off was easier under higher wave conditions than under lower wave conditions at a constant wind speed, and take-off effort increased only when both wind and waves were gentle. Our data suggest that both ocean waves and winds play important roles for albatross take-off and advances our current understanding of albatross flight mechanisms.

Modeling and Simulation Analysis of Bionic Flapping-Wing Flight Attitude Control Based on L1 Adaptive

Flapping-wing flight control is a multi-input and multi-output nonlinear system with uncertainties, which is affected by modeling errors, parameter variations, external disturbances, and unmodeled dynamics. Parameter uncertainty has a great impact on the stability control of flapping-wing flight, and gain adjustment is a common means to deal with parameter uncertainty, but it is complex and time-consuming. Based on the mechanism of flapping-wing flight, a nonlinear dynamic model for flapping-wing dynamic flight is established by analyzing the forces, moments, and attitude changes of the fuselage and wing in detail. Based on the constructed dynamic model, a fast robust adaptive flapping-wing flight control method is proposed. The state predictor is designed to estimate and monitor the uncertain parameters in the flapping-wing attitude control model, and the adaptive law adjusts the parameter estimation to ensure that the output error between the state predictor and the controlled object is stable in the Lyapunov sense, and finally the adaptive control law is obtained. At the same time, the Monte Carlo-support vector machine method is used to optimize the boundary of the control parameters in the flight control to obtain the control parameters that can meet the control expectations, and the obtained parameters are classified and judged according to the stable level flight conditions. Based on the adjusted parameters and the predetermined control signal, the control amount is adjusted according to the control law. When the adaptive gain is large enough, the simulation results show that the system has good transient response characteristics.

A mobile robot path planning using improved beetle swarm optimization algorithm in static environment

Optimization problems in the field of industrial engineering usually involve massive amounts of information and complex scheduling process with the characteristics of high-dimension and non-convexity, which bring many challenges to finding an optimal solution. We proposed an improved beetle swarm optimization (IBSO) algorithm demonstrating the potential to solve different problems of path planning in static environment with good performance. Firstly, the algorithm is an upgrade of the original beetle antennae search (BAS) algorithm and the search strategy is improved by replacing a single beetle by multiple beetles. Secondly, the global search ability gets enhanced, and the diversity of optimization is improved through introducing nonlinear sinusoidal disturbance with Levy flight mechanism in beetles’ position. Finally, the search performance of beetle swarm is improved by simulating the characteristics of employment bees to search for a better solution near the honey source field in the Artificial Bee Colony (ABC) algorithm. Our experiment results show that IBSO algorithm can achieve higher search efficiency and wider search ranges through well balancing the advantages of local search and fast optimization of the BAS algorithm with the global search of the improved mechanism. The IBSO algorithm has shown the potential to provide a new solution for several optimization problems in path planning in static environment.

Hummingbirds use wing inertial effects to improve manoeuvrability.

Hummingbirds outperform other birds in terms of aerial agility at low flight speeds. To reveal the key mechanisms that enable such unparalleled agility, we reconstructed body and wing motion of hummingbird escape manoeuvres from high-speed videos; then, we performed computational fluid dynamics modelling and flight mechanics analysis, in which the time-dependent forces within each wingbeat were resolved. We found that the birds may use the inertia of their wings to achieve peak body rotational acceleration around wing reversal when the aerodynamic forces were small. The aerodynamic forces instead counteracted the reversed inertial forces at a different wingbeat phase, thereby stabilizing the body from inertial oscillations, or they could become dominant and provide additional rotational acceleration. Our results suggest such an inertial steering mechanism was present for all four hummingbird species considered, and it was used by the birds for both pitch-up and roll accelerations. The combined inertial steering and aerodynamic mechanisms made it possible for the hummingbirds to generate instantaneous body acceleration at any phase of a wingbeat, and this feature is probably the key to understanding the unique dexterity distinguishing hummingbirds from other small-size flyers that solely rely on aerodynamics for manoeuvering.

Quaternion Methods and Regular Models of Celestial Mechanics and Space Flight Mechanics: Local Regularization of the Singularities of the Equations of the Perturbed Spatial Restricted Three-Body Problem Generated by Gravitational Forces

Quaternion Methods and Regular Models of Celestial Mechanics and Space Flight Mechanics: Local Regularization of the Singularities of the Equations of the Perturbed Spatial Restricted Three-Body Problem Generated by Gravitational Forces

Quadcopter Prototype Stability Assessment With Pid Controller And Euler-Lagrange Approach

Abstract The increasing use of drones in various fields has led to their popularity in developed countries due to their ease of use and manufacture. This Miniature Pilotless Aircraft has numerous beneficial usages such as express shipping, gathering information, crop monitoring, cargo transport, storm tracking, geographic mapping of inaccessible terrain, search and rescue operations, among others. This study aims to investigate the stability of a quadcopter through simulations based on the mathematical model that describes the quadcopter’s dynamic and flight mechanics, using the Euler-Lagrange approach. It conducts simulations in MATLAB and present the principles that govern quadcopter stability, focusing on setting the PID coefficients to achieve optimal stability. This study provides insights into the principles of drone mechanics and stability, enabling us to better understand the quadcopter’s behavior and performance.

Quaternion Methods and Regular Models of Celestial Mechanics and Space Flight Mechanics: Local Regularization of the Singularities of the Equations of the Perturbed Spatial Restricted Three-Body Problem Generated by Gravitational Forces

The problem of local regularization of differential equations of a perturbed spatial restricted three-body problem is studied: elimination of singularities (dividing by zero) generated by gravity forces of differential equations of perturbed spatial motion of a material point M, which has a negligibly small mass, in the vicinity of two gravitating points M0 and M1 by writing equations of motion in rotating coordinate systems, the use of new regular variables and the regularizing transformation of time. Various systems of regular quaternion differential equations (RQDE) for this problem are obtained. The following groups of variables act as variables in these equations: (1) four-dimensional Kustaanheimo–Stiefel variables, Keplerian energies and time t, (2) distances from the point M to the points M0 and M1, modules of the vectors of the moment of velocities of the point M with respect to the points M0 and M1, Keplerian energy, time t and Euler (Rodrigues–Hamilton) parameters characterizing the orientations of the orbital coordinate systems in the inertial coordinate system; (3) two-dimensional Levi-Civita variables describing the motion of the point M in ideal coordinate systems, Keplerian energies, time t and Euler parameters characterizing the orientations of ideal coordinate systems in the inertial coordinate system and being osculating elements (slowly changing variables) for the motion of the point M in the neighborhood gravitating point M0 or M1, respectively. To construct the RQDE, the equations of the perturbed spatial restricted three-body problem, written either in nonholonomic (azimuthally free), or in orbital, or in ideal coordinate systems, were used as initial ones; “fictitious” times τ0 and τ1 are used as new independent variables (i.e., regularizing differential transformations of the Sundmann time are used) or angular variables φ0 and φ1, which are traditionally used in the study of orbital motion as part of polar coordinates. To match the two independent variables used in the vicinity of the gravitating points M0 and M1, additional differential equations are used. The obtained various locally regular quaternion differential equations of the perturbed spatial restricted three-body problem make it possible to develop regular analytical and numerical methods for studying the motion of a body of negligibly small mass in the vicinity of two other bodies with finite masses, and also make it possible to construct regular algorithms for the numerical integration of these equations. The equations can be effectively used to study the orbital motion of celestial and cosmic bodies and spacecraft, to predict their motion, as well as to solve problems of controlling the orbital motion of spacecraft and solving problems of inertial navigation in space.