Flight Simulator Research Articles

Recurrent neural networks for aerodynamic parameter estimation with Lyapunov stability analysis

ABSTRACT Aircraft parameter estimation is crucial for designing accurate and reliable flight dynamic models, essential for integration into flight simulators and developing effective control laws. These parameters, encompassing aerodynamic characteristics, play a pivotal role in enhancing aircraft performance, safety and overall operational efficiency. This paper explores aircraft parameter estimation using two Recurrent Neural Network (RNN) approaches: (i) the weight-bias method (RNN-WB) and (ii) the gradient-based method (RNN-Gradient). RNN-WB is based on the Hopfield neural network and relies on pre-computation of weight and bias information, applying non-linearity to the states of the network. RNN-Gradient computes direct gradients and applies non-linearity to the error. Simulated flight data is employed in MATLAB implementations to assess estimation results, considering both performance metrics and computation time. The estimated parameters were also compared with estimates obtained from Unscented Kalman Filter (UKF). A novel methodology is introduced to establish the asymptotic stability of RNN-WB and RNN-Gradient methods, utilizing the normalized Lyapunov energy functional. The asymptotic stability ensures the reliability and robustness of these techniques for parameter estimation. The RNN-Gradient shows a 20% performance improvement over RNN-WB. Satisfactory simulation results from both algorithms provide a promising foundation for their potential applications to real flight test data.

Integral barrier Lyapunov function-based fixed-time integrated guidance and control with asymmetric field-of-view angle constraints

The missile integrated guidance and control (IGC) problem with seeker’s asymmetric field-of-view (FOV) angle constraints is addressed. In the introduced model, the fin deflections controller is used to drive the body line-of-sight angle rate, which avoids the solving and tracking of aerodynamic angles in traditional IGC method. A novel fixed-time convergence virtual input based on the integral barrier Lyapunov function is designed to ensure the asymmetric FOV angle constraints are never violated. The virtual input is tracked by a new proposed pre-defined fixed time controller with adjustable initial convergence speed. The lumped uncertainty including aerodynamic coefficient and target maneuvering is coped by the fixed-time disturbance observer. It is proved that the closed-loop system states are converged to the bounded region in a fixed-time and the asymmetric FOV angle constraints are satisfied. The 6-degree of freedom flight simulations and comparisons verified the advantages of the proposed algorithm.

Effect of wing morphing on stability and energy harvesting in albatross dynamic soaring

Dynamic soaring, which harvests energy from the wind, can enhance Unmanned Aerial Vehicles’ (UAVs’) range and endurance. However, energy harvesting efficiency issues hinder UAV applications, which can be addressed by wing morphing. Therefore, this study investigates the influence of albatross wing morphing during dynamic soaring. By constructing a parametric model, the shape of the albatross wing can be modeled and achieve morphing based on joints. From the video data, this paper summarizes the typical wing morphing patterns of the albatross and notices that changes primarily occur during the leeward descent phase. This paper first analyzes the aerodynamic performance of different wing morphing patterns and finds that the drag coefficient can be reduced by 7.75% with a suitable morphing pattern. This paper also explores the drag coefficient reduction mechanism and finds that downwash airflow decreases by 30.32% after wingtip anhedral. Interestingly, the lift-to-drag ratio shows minimal variation under different morphing patterns, within 2%. From the stability perspective, this study finds that the neutral point position changes after morphing. The maximum longitudinal static margin change is 4.9%, enhancing longitudinal stability by increasing the restorative moment arm. The lateral neutral point is 4.87% closer to the center of gravity, decreasing the roll and yaw moments. It can be observed that wingtip anhedral significantly increases the stability of the albatross. Moreover, a flight simulation is carried out to study the morphing influence on trajectory and energy harvesting. The results show that maximum energy gained is improved by 47.99%, and endurance is increased by 13.05%. The results also indicate that the effects of wing morphing are global rather than limited to the phase of morphing occurrence. Finally, based on the results, this paper proposes wing morphing regularity about the wingtip for UAVs. Wingtip bends downward can significantly increase the UAVs’ stability and reduce drag, but the overall trajectory needs to be reconsidered after introducing wing morphing.

Pitot tube measure-aided air velocity and attitude estimation in GNSS denied environment

This paper addresses the problem of estimating air velocity and gravity direction for small autonomous fixed-wing drones in GNSS11Global Navigation Satellite Systems.-denied environments. The proposed solution uses a minimal sensor suite, relying on Pitot tube measurements and Inertial Measurement Unit (IMU) signals, including only gyrometers and accelerometers. The approach combines the Riccati observer and Equivariant Filter designs, using an over-parametrization technique to design an observer on SO(3)×R3 and subsequently re-project to S2×R3 to estimate the gravity direction. The system’s observability is analyzed, and local exponential stability of the origin of the observer error is demonstrated as long as the aircraft attitude is persistently exciting. The observer was evaluated using simulated and real flight data to showcase the estimator’s performance.

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.

An Engine Deterioration Model for Predicting Fuel Consumption Impact in a Regional Aircraft

A deterioration cycle model is presented, designed to consider the turbomachinery efficiency losses that are expected during real engine in-service operations. The cycle model was developed using information from practical experience found in the literature to account for both short- and long-term deterioration effects; the former occurring during the first flight cycles, the latter due to regular in-service operation. This paper highlights the importance of analyzing the inter-turbine temperature margin (ITTM) to track engine deterioration to determine the extent of an in-service engine life. The proposed model was used to assess the ITTM and fuel consumption impact in the CRJ-700 regional aircraft (powered by two CF34-8C5B1 engines) for three representative missions: short (0.4 h), average (1.4 h), and long (2.5 h), considering different levels of engine deterioration, from the new engine level up to fully deteriorated. The fuel consumption at the new engine level (zero deterioration) was validated against a real-time engine model embedded in a Level-D flight simulator, the so-called Virtual Research Flight Simulator located at the Laboratory of Applied Research in Active Control, Avionics, and AeroServoElasticity. The errors found in this validation for the trip mission fuel consumption in the short, average, and long missions were −3.6, +0.9, and +0.6%, respectively. The cycle model predictions suggest the ITTM for a new engine is 55.2 °C, whereas for a fully deteriorated engine, it is 26.4 °C. Finally, in terms of fuel consumption, the results presented here show that an average CF34-8C5B1 engine shows an increase in the cumulative fuel consumption of 2.25% during its life in service, which translates to a 4.5% impact in aircraft fuel consumption.

Cybersickness with passenger VR in the aircraft: Influence of turbulence and VR content

Using VR in the airplane cabin is appealing, primarily because of the enhanced entertainment value, increased privacy, and improved recreational opportunities provided by higher levels of immersion. However, VR applications in aircrafts contain the risk of passengers developing cybersickness. The particular environment of a moving aircraft in interaction with visual representation of movements in VR could lead to severe cybersickness, especially during turbulence. We had 129 participants experience VR in a full flight simulator with different content (static or dynamic VR clips) and during varying phases of flight including turbulence. The employed simulator is equipped with a cabin module, creating an economically valid environment. VR induced significant but mild symptoms of cybersickness. Nausea and dizziness symptoms were most severe during turbulence and especially with dynamic VR content being presented. More anxious participants tended to report more symptoms. In addition, there was an association with video game use and attitudes toward new technologies. While mild content and short exposure times only led to fairly low expressions of cybersickness, a long-term use of VR under turbulence could possibly become a concern. Airlines should especially address passengers’ negative attitudes toward new technologies, and VR in particular, to reduce fears and the risk of low tolerability.

Trajectory tracking control of parallel manipulator actuated with shape memory wire

This study describes the design of a parallel spatial manipulator with four degrees of freedom actuated with shape memory alloy (SMA) wire to validate the use of SMA in complicated mechatronics systems. The manipulator has a closed kinematic structure, which includes a fixed base and a moving square platform (end effector). The four arms of the manipulator are SMA wires fastened between the fixed base and the end effector. SMA wire-based actuators replace bulky conventional revolute actuators. This work spotlights the development of an actuator model, dimensional analysis, and design of cascade control strategies of various PID and sliding mode controller in their integral and fractional order configurations. Experimental evaluation of the actuator is performed through trajectory tracking to quantify the different controller configurations. The experimental results indicate that the parallel manipulator associated with SMA wire actuators is the best alternative to conventional motion stages for highly precise micro-positioning and tracking applications in the fields of 3D printing, intricate surgical operations, the medical and pharmaceutical industries, and flight and gaming simulators.

Aerodynamic Modeling of a Missile Combining Transfer Learning and Dendritic Net

During the initial stages of missile design, finding an efficient method for analyzing aerodynamic characteristics is crucial. This paper proposes a novel aerodynamic modeling method based on a limited computational fluid dynamics (CFD) dataset, combining transfer learning (TL) with Dendritic Net (DD). Initially, we employ CFD-calculated aerodynamic data to establish a pretrained model using DD. Subsequently, the model is adapted to the target domain by TL, predicting aerodynamic parameters under specific conditions. The overall aerodynamic parameters are utilized to generate a relational spectrum through DD’s white-box features, from which primary features are extracted to establish an aerodynamic polynomial model. Finally, the model’s practicality is validated by ballistic flight simulations. The innovation lies in leveraging DD to generate a relational spectrum of aerodynamic parameters, leading to a high-precision polynomial model. Research shows DD outperforms traditional cell-based networks in predicting aerodynamic parameters, and TL reduces the CFD computation workload in the target domain by 3/4 while maintaining prediction accuracy. The polynomial model exhibits superior accuracy compared to the empirical fitting formulas. The method reduces the computational workload for aerodynamic data collection, and through system identification, a high-precision polynomial model is obtained, which provides a reliable basis for missile controller design.

Basic Computational Algorithms for Representing an Aircraft Flight (Calculation of 3D Displacement and Displaying)

This manuscript describes the computational process to calculate an airplane path and display it in a 2D and 3D coordinate system on a computer screen. The airplane movement is calculated as a function of its dynamic’s conditions according to physical and logical theory. Here, the flight is divided into maneuvers and the aircraft conditions are defined as boundary conditions. Then the aircraft position is calculated using nested loops, which execute the calculation procedure at every step time (Δt). The calculation of the aircraft displacement is obtained as a function of the aircraft speed and heading angles. The simulator was created using the C++ programming language, and each part of the algorithm was compiled independently to reduce the source code, allow easy modification, and improve the programming efficiency. Aerial navigation involves very complex phenomena to be considered for an appropriate representation; moreover, in this manuscript, the influence of the mathematical approach to properly represent the aircraft flight is described in detail. The flight simulator was successfully tested by simulating some basic theoretical flights with different maneuvers, which include stationary position, running along the way, take off, and some movements in the airspace. The maximum aircraft speed tested was 120 km/h, the maximum maneuver time was 12 min, and the space for simulation was assumed to be without obstacles. Here, the geometrical description of path and speed is analyzed according to the symmetric and asymmetric results. Finally, an analysis was conducted to evaluate the approach of the numerical methods used; after that, it was possible to confirm that precision increased as the step time was reduced. According to this analysis, no more than 500 steps are required for a good approach in the calculation of the aircraft displacement.

IMMERSIVE ANALYTICS

Immersive Analytics focuses on the benefits and challenges of using immersive environments for data analysis, and developing designs to improve efficiency. Although immersive technologies are widely available, practical solutions have not gained widespread acceptance in real- world applications. Research in this field focuses on abstract 3D visualization, immersive environments, paper sampling and use case evaluation. 03 Related Works • Brooks early review of VR applications found it effective in specific domains like flight simulators, automotive engineering, and astronaut training. • Van Dam et al. highlighted VR applications for SciVis, benefiting archaeology and medical fields. • Laha and Bowman reviewed VR techniques for visualizing volume data, highlighting the need for controlled experiments to explore individual components of immersion. • Reda et al. summarized research for hybrid reality environments like the CAVE2, emphasizing the possibility of collaborative data analysis. • Brath collected evidence that 3D visualizations offer advantages beyond 2D, focusing on immersive displays. 05 Result • Overall, immersive analytics can lead to better data comprehension, better decision-making, more engagement and teamwork, effective big data exploration, creative data visualization methods, non-technical users' empowerment, and applications in a variety of fields. • These results add to the increasing importance of immersive analytics as an efficient tool for decision support and data analysis. Introduction • To facilitate data-driven analytical reasoning, immersive analytics leverages interactive technology like as virtual reality glasses, big flat screen displays, and even the internet of things. • Immersion refers to an experience that creates a genuine sense of presence in a virtual environment. • A person experiences a shift in awareness from their immediate real environment to another reality. • Immersion analytics is still a relatively new field that has mostly been studied in use cases and workshops. • The notion remains extremely difficult, even within the small community of immersive analytics practitioners. Methodology 4.1 Immersive environments • The study focuses on immersive environments leading to a mixed reality experience. • Abstract 3D visualizations must be presented in a mixed or VR environment where hardware and user interact closely. 4.2 Abstract 3D visualizations • Data that lacks a physical representation or intrinsic spatial organization is referred to as abstract data. • In visualization, abstraction is obtained by using colors and shapes that are not directly associated with the object. 4.3 Paper sampling • Paper sampling in immersive analytics refers to the process of selecting and gathering relevant research papers and publications related to immersive analytics. Conclusion and future scope • In conclusion, immersive analytics has the potential to completely transform how we work with data by facilitating deeper understanding, better decision-making, and improved teamwork. • Immersion analytics will develop further and contribute significantly to data analysis and decision support in the future by tackling issues and seizing opportunities in technological innovation, domain-specific applications, ethical issues, and user experience design.

Validating Synthetic Data for Perception in Autonomous Airport Navigation Tasks

Autonomous navigation within airport environments presents significant challenges, mostly due to the scarcity of accessible and labeled data for training autonomous systems. This study introduces an innovative approach to assess the performance of vision-based models trained on synthetic datasets, with the goal of determining whether simulated data can train and validate navigation operations in complex airport environments. The methodology includes a comparative analysis employing image processing techniques and object detection algorithms. A comparative analysis of two different datasets was conducted: a synthetic dataset that mirrors real airport scenarios, generated using the Microsoft Flight Simulator 2020®video game, and a real-world dataset. The results indicate that models trained on a combination of both real and synthetic images perform much better in terms of adaptability and accuracy compared to those trained only on one type of dataset. This analysis makes a significant contribution to the field of autonomous airport navigation and offers a cost-effective and practical solution to overcome the challenges of dataset acquisition and algorithm validation. It is thus believed that this study lays the groundwork for future advancements in the field.

Quantifying the Environmental Impact of Private and Commercial Pilot License Training in Canada

As the global aviation sector expands to accommodate increasing air travel demand, the subsequent rise in flights exacerbates carbon dioxide (CO2) emissions, challenging the sector’s environmental sustainability. Targeting net-zero emissions by 2050, international aviation agencies are stressing the imperative of reducing emissions directly at their source. While the literature provides abundant estimates of aviation emissions from airline flights, there has been a lack of work aimed at quantifying CO2 emissions specific to the general aviation sector. This study investigates CO2 emissions attributed to the pilot training sub-sector within Canada’s general aviation sector. It specifically examines the initial phase of pilot training, known as ab initio training, extending through to the attainment of a commercial pilot license. Utilizing a mathematical framework alongside assumptions, combined with data on license issuances over a 23-year period, it estimated that each hour of flight training emits about 70.4 kg of CO2, varying between 44.9 kg and 94.9 kg per hour. Annual CO2 emissions from Canada’s ab initio pilot training are estimated at approximately 30,000 tons, with a possible range of 19,000 to 40,000 tons. The study also explores mitigation opportunities, such as flight simulation training devices and electric aircraft. Though focusing on Canada’s ab initio pilot training, the findings have international relevance.

Numerical investigation of nitrogen spontaneous condensation over airfoils in cryogenic wind tunnel

Cryogenic wind tunnels (CWT) provide the aerodynamic tests that occur at high Reynolds numbers by operating under cryogenic environment to meet the requirements of hypersonic flight simulation. However, condensation in cryogenic environment near the limited condition destroys the reliability of the test measurement results. Accordingly, research on condensation in CWT is imperative for devising effective control strategies. This study introduces a transonic non-equilibrium condensation model, tailored to evaluate the complex phenomena of nitrogen condensation over airfoils. The model was applied to assess condensation effects on the NACA 0012–64 airfoil and the RAE 2822 airfoil under various operating conditions. Furthermore, the study examined the effect of the angle of attack and airfoil shape on the condensation process. The result show that nitrogen condensation near the airfoil is observable only under operating conditions within the pre-condensation zone. Operating conditions of CWT can be tailored to prevent condensation with specific airfoil profiles. The effect of condensation on the pressure coefficient includes advancing the position of the pressure jump and increasing the pressure coefficient of the airfoil intermediate region, particularly within the 20 %–70 % chord length span on the airfoil's upper surface. This primarily affects the measurement of lift coefficients in CWT. In the operating conditions of this study, the lift coefficient exhibits a maximum deviation of 31.4 %, and the drag coefficient shows a maximum deviation of 2.4 %. The transonic spontaneous condensation model offers an approach to evaluate condensation's impact on airfoil tests within CWT. The findings introduce a methodological framework for effectively controlling condensation phenomena.

Density gradient-RRT: An improved rapidly exploring random tree algorithm for UAV path planning

In-depth studies of algorithms for solving motion planning problems have been conducted due to the rapid popularization and development of unmanned aerial vehicles in previous decades. Among them, the classic rapidly exploring random tree (RRT) algorithm has derivative algorithms (e.g., RRT*, Q-RRT*, and F-RRT*) that focus on the optimal path cost of the initial solution. Other improved algorithms, such as RRT-connect and BG-RRT, focus on the optimal time of the initial solution. This article proposes an improved density gradient-RRT (DG-RRT) algorithm based on RRT that improves the efficiency of the guide point and reduces the time lost in the process of obtaining the initial solution through the dynamic gradient sampling strategy. Simultaneously, it reduces the path cost by reconstructing the output path. The proposed algorithm is an expansion algorithm of a random tree, and the performance of the algorithm can be further improved by combining it with other RRT optimization algorithms. DG-RRT and other algorithms are compared in different environments through simulation experiments to verify the advantages of DG-RRT. In addition, it used a set of simulation flight tests to verify the feasibility of the DG-RRT algorithm for UAV path planning.

Wind Shear Operation-Based Competency Assessment Model for Civil Aviation Pilots

Wind Shear Operation-Based Competency Assessment Model for Civil Aviation Pilots

Graph‐based control framework for motion propagation and pattern preservation in swarm flight simulations

AbstractSimulation of swarm motion is a crucial research area in computer graphics and animation, and is widely used in a variety of applications such as biological behavior research, robotic swarm control, and the entertainment industry. In this paper, we address the challenges of preserving structural relations between the individuals in swarm flight simulations by proposing an innovative motion control framework that utilizes a graph‐based hierarchy to illustrate patterns within a swarm and allows the swarm to perform flight motions along externally specified paths. In addition, this study designs motion propagation strategies with different focuses for varied application scenarios, analyzes the effects of information transfer latencies on pattern preservation under these strategies, and optimizes the control algorithms at the mathematical level. This study not only establishes a complete set of control methods for group flight simulations, but also has excellent scalability, which can be combined with other techniques in this field to provide new solutions for group behavior simulations.

AERODROME MAPPING DATA DESIGN DEVELOPMENT APPROACH HIGHLIGHTS

In accordance with the trend in further intellectualization of mapping data design systems, this article deals with the problem of development methods for obtaining aerodrome mapping data more efficient than the existing methods that use manual vectorization on a raster base. Data usage areas were listed, including automated control systems, flight deck automation, simulators and simulation systems. Much attention was given to main aerodrome mapping data design approaches analysis, which shows that existing aerodrome cartographic data obtaining methods lack functionality. A description and basic requirements for an aerodrome mapping data design system, as well as requirements for the data itself, are presented. Additionally, data validation aspects are noted, including those of a taxi route network. Results of the research suggest that computer-aided design methods make it possible to significantly reduce labor intensity and time required to obtain mapping data. A new approach, which consists in using computer-aided design methods for such data, is proposed. Areas in which this approach can provide a significant effect were identified. Methods, algorithms and programs that implement the approach are being developed in context of the new data design system. It will provide a wide range of functions for aerodrome mapping design. General scheme of the system describing its main components was given. An example of aircraft parking elements design as a part of routing network design is provided.

The effect of Ashtanga-Vinyasa Yoga method on air force pilots' operational performance.

In today's military landscape, optimizing performance and bolstering physical health and mental resilience are critical objectives. Introducing a 12-week Ashtanga Vinyasa Yoga Supta Method (AVYSM) to the training protocol of military trained Airforce pilots, we aim to assesses the feasibility and impact of the method. Borg Scale assesses the intensity level of physical activity during the intervention. Flight simulator data gauges operational performance responses. Postural control responses are measured using a force platform, stress responses are monitored via heart monitor, and handgrip dynamometry will measure strength. Respiratory capacity is assessed using a spirometer, body composition is evaluated using impedance balance, and aviation-related questionnaires are administered before and after the intervention period. In a randomized controlled trial, the totality of pilots from the "Masters in Military Aeronautics: aviator pilot specialist" course at the Portuguese Air Force Academy (PAA) were randomly assigned to the yoga intervention or the waiting list control groups, with participants providing written informed consent. The control group followed protocolized course classes for 12 weeks, while the intervention group integrated two weekly one-hour yoga sessions into their course. The PAA has approved the implementation of this intervention protocol at Airbase 11 in Beja, highlighting its significance for the organization's policy makers. We hypothesize that this method will enhance operational performance and, subsequently, elevate flight safety. This research's potential extends beyond the PAA, as it can be adapted for use in Airforce departments of other nations and various military contexts. Évora University research ethics committee-approval number 21050. Study registered on ClinicalTrials.gov under identifier NCT05821270, registered on April 19, 2023.

Design and verification of controller for a small coaxial dual-rotor aircraft

In recent years, coaxial dual-rotor aircraft has attracted much attention due to its unique aerodynamic layout. However, it is difficult to miniaturize the coaxial dual-rotor aircraft that relies on the principle of periodic pitch variation due to complex structure and control difficulties. This study proposes a small cylindrical coaxial dual-rotor aircraft based on a vector motor seat. For the control problems of such coaxial dual-rotor aircraft, a position and attitude controller based on neural networks and adaptive cascaded PID control is designed. A control system model was established and tested using MATLAB/Simulink. The proposed control scheme’s soundness and efficiency were confirmed by creating a prototype and performing flight trials. The results show that compared with the classic PID controller, the control effect of the controller has improved by 36.3% to 54.6%. In the centripetal rotation flight simulation experiment, the displacement error does not exceed 0.2 m, the speed error does not exceed 0.05 m/s, and the attitude angle error does not exceed 0.01 rad. This validates the effectiveness of the designed controller, indicating that the controller can enhance the stability of the system and achieve stable hovering and flight.