Framework for Real-Time Closed-Loop Simulation of Advanced Rotorcraft Configurations Using Comprehensive Flight Dynamics Models

Aircraft flight dynamics trim is the basis for the large civil aircraft flight dynamics characteristics analysis. In this paper, the full nonlinear flight dynamics model of civil aircraft is systematically deduced, an iterative trim method for the six-degree-of-freedom flight dynamics model based on the Downhill Simplex optimization algorithm is designed, and the trim accuracy and computational efficiency of the Downhill Simplex optimization algorithm are analyzed and the variation of trim variables under different initial weights is studied. Results show that the Downhill Simplex optimization algorithm can effectively solve the six-degree-of-freedom full nonlinear aerodynamics trim problem of large civil aircraft under the condition of straight forward and level flight, and the trim deviation can be controlled within the range of ±0.05N/Nm within 500 steps. The flight dynamics iterative trim method based on the Downhill Simplex optimization algorithm designed in this paper can provide reference and technical support for civil aircraft flight simulation, flight dynamics characteristics and flight quality research.

The lightweight structures and unconventional configurations being considered for the next generation of aircraft mean that any effort to predict or control the flight dynamics is impacted by the structural dynamics. One of the most severe forms of coupling between aeroelasticity and flight dynamics is an instability called body freedom flutter. The existing tools often assume a relatively weak effect of structural dynamics on the flight dynamics, and are therefore incapable of modeling strong interactions like body freedom flutter. A method of combining different sources of data traditionally used for aeroelasticity and flight dynamics is described by reconciling many of the differences between these models. By building upon past modeling efforts, a level of familiarity in the approach is achieved. Generally the differences from the traditional approaches are subtle but significant. The traditional frequency domain flutter model in a modal coordinate system is converted to a form consistent with a time domain flight dynamics model. The time domain rational function approximation about a non-inertial coordinate system and the unique constraints for the conversion between the inertial and non-inertial coordinate systems are discussed. A consistent transformation of the states of aeroelastic models to flight dynamics models is derived, which enables the integration of data from higher fidelity computational fluid dynamics models or wind-tunnel testing. The present method of integrating multidisciplinary data was used to create models that compare well with X-56A flight-test data, including conditions past the flutter speed.

<div>An accurate Unmanned Aerial System (UAS) Flight Dynamics Model (FDM) allows us to design its efficient controller in early development phases and to increase safety while reducing costs. Flight tests are normally conducted for a pre-established number of flight conditions, and then mathematical methods are used to obtain the FDM for the entire flight envelope. For our UAS-S4 Ehecatl, 216 local FDMs corresponding to different flight conditions were utilized to create its Local Linear Scheduled Flight Dynamics Model (LLS-FDM). The initial flight envelope data containing 216 local FDMs was further augmented using interpolation and extrapolation methodologies, thus increasing the number of trimmed local FDMs of up to 3,642. Relying on this augmented dataset, the Support Vector Machine (SVM) methodology was used as a benchmarking regression algorithm due to its excellent performance when training samples could not be separated linearly. The trained Support Vector Regression (SVR) predicted the FDM for the entire flight envelope. Although the SVR-FDM showed excellent performance, it remained vulnerable to adversarial attacks. Hence, we modified it using an adversarial retraining defense algorithm by transforming it into a Robust SVR-FDM. For validation studies, the quality of predicted UAS-S4 FDM was evaluated based on the Root Locus diagram. The closeness of predicted eigenvalues to the original eigenvalues confirmed the high accuracy of the UAS-S4 SVR-FDM. The SVR prediction accuracy was evaluated at 216 flight conditions, for different numbers of neighbors, and a variety of kernel functions were also considered. In addition, the regression performance was analyzed based on the step response of state variables in the closed-loop control architecture. The SVR-FDM provided the shortest rise time and settling time, but it failed when adversarial attacks were imposed on the SVR. The Robust-SVR-FDM step response properties showed that it could provide more accurate results than the LLS-FDM approach while protecting the controller from adversarial attacks.</div>

Tailless Unmanned Aerial Vehicles (UAVs) offer several advantages over their conventional counterparts, including enhanced maneuverability, higher durability, and better stealth. However, they are challenging in their stability and control due to the absence of stabilizing and control surfaces that typically exist in conventional empennage. A crucial process for analyzing the tailless UAVs’ stability/performance characteristics and determining/validating their flight control parameters is done via the modeling and simulation of flight dynamics. This paper presents a comprehensive and systematic procedure for investigating the flight dynamics of a tailless UAV, including modeling, simulation, analytical verification, and flight testing, while also explaining the interconnections among these elements. It also addresses the common challenge of limited accessibility of UAV essential data through using diverse analytical, empirical, and experimental methods. First, a rapid and effective first-principles modeling approach is introduced to simulate the nonlinear six-degree-of-freedom flight dynamics of a small tailless UAV case study. The modeling process follows a modular framework where well-defined experiments and commercial of-the-shelf software, tools, and sensors are employed to build the necessary sub-models, including geometric, mass–inertia, aerodynamic, propulsion, and actuator models. Then, all sub-models are integrated into a simulation environment to allow the prediction of the UAV dynamic response obtained from the given control inputs. The developed flight dynamic model is subjected to a thorough verification process to ensure its integrity and proper functionality by comparing the simulated trim and natural flight modes with the calculated analytical results. Finally, a set of specific flight tests are performed to validate the developed simulation model and verify relevant performance characteristics for the case-study UAV. The results show that the proposed approach provides a systematic and straightforward method for examining the flight dynamics of small tailless UAVs with reasonable accuracy.

A linear parameter varying (LPV) flight dynamics model (FDM) is proposed to cater for atmospheric disturbance analysis in special flight conditions. A novel FDM which is capable of addressing the influence of turbulent wind is derived under the wind frame. An affine parameter dependent LPV model with wind effects is built based on function substitution method. The optimal solution for the decomposing function of the LPV FDM is obtained by genetic algorithm (GA). The analysis of dynamic response indicates that the genetic-optimized LPV FDM approximates the nonlinear FDM evidently, since it identifies the instantaneous dynamics and flight states varying in a wide range. The simulations of approach and landing against wind shear show that the genetic-optimized LPV FDM captures the instantaneous dynamic response when flying through turbulent wind, indicating that the LPV model can be further applied to turbulent wind special flight analysis and control law design.

An integrated modelling approach, suitable for flight loads analysis and flight dynamics investigations is presented. These scenarios need fast loop capable simulation models. Typically, they are evaluated many times in the entire flight envelope, for varying mass cases and for changing parameters during the aircraft design process. Further, the simulations models have very different requirements depending on their application. Flight dynamics models must account for large nonlinear rigid Body motions and aerodynamic nonlinearities, manoeuvre loads analysis, additionally need to take flexible deformations into account, and hence require distributed aerodynamics, and for gust loads Analysis unsteady aerodynamic effects are essential. The proposed integrated model is based on nonlinear equations of motion using mean axes constraints. Potential flow based aerodynamics with low computational cost are the method of choice for most aeroelastic applications. Presented in this paper are some important aspects regarding the aerodynamic modelling, which are handled differently compared to other implementations. Instead of the Doublet Lattice Method (DLM), the 3D panel method NEWPAN is used, which is able to capture previously neglected flight mechanical effects such as roll-yaw coupling and induced drag. Since, the Aerodynamic Influence Coefficient (AIC) matrices obtained from NEWPAN are nonlinearly dependent on the flight state, a Reduced Order Model (ROM) based on Proper Orthogonal Decomposition (POD) is setup and subsequently interpolated. The proposed ROM interpolates directly AIC matrices (AIC-ROM) instead of pressures. The advantages of a ROM based on AIC matrices over similar approaches based on pressure coefficients are explained. Similarly to the Doublet Lattice Method, the 3D panel code is able to compute frequency based unsteady Aerodynamic Influence Coefficient (AIC) matrices, which are approximated by a Rational Functions (RFA) to make them amenable for time domain simulations. Unlike other approaches, the physical RFA allows a clear separation of quasi-steady, added mass and unsteady lag terms. Several application examples are presented and their particular needs are addressed. The proposed modelling approach supports flight dynamics by including previously neglected aerodynamic roll yaw coupling and nonlinear angle of attack dependencies, manoeuvre loads, including aeroelastic deformations, and gust loads analyses, including unsteady aerodynamics in one integrated model and is suitable for for investigations regarding active gust and manoeuvre load alleviation, primary flight control design, or performance improvement through lift redistribution.

In this paper, the flight dynamic model of Vertical Take-Off and Landing (VTOL) aircraft which equips a propeller-wing-flap system that produces slipstream is established. The complete aircraft is modeled by combining experimental results, theoretical calculation, and empirical data. Firstly, the propeller deflected slipstream effects and the parameters of ducted fan are obtained by bench test. The DATCOM are used for generating the aerodynamic coefficients. Then, the 6-DoF nonlinear flight dynamic model in both hover and forward flight conditions are deducted by employing the assumption of linear superposition. The gyro effect and gravity are considered. Finally, specific trim conditions in hovering, transitional and level flight states are determined, and dynamic characteristics at trim are studied by both full model simulation and linear system analysis obtained through small-perturbation theory. It is found that the aircraft is critically stable in hovering condition. The damping ratio of short-period mode is relatively small, and the phugoid mode divergence in the transition state. The aircraft is less well damped in the level flight condition. The built model accurately reflects the dynamic characteristics of the VTOL aircraft and provides help for the design of the flight control system afterward.KeywordsSlipstreamVertical Take-off and Landing (VTOL) aircraftBench testDynamic modeling

INPE (National Institute for Space Research)’s Satellite Tracking and Control Center (CRC) has been performing TT&C control of satellites since 1993. Currently at CRC, flight dynamics activities and satellite operations planning are performed in an integrated manner. Most payload operations are either performed in real-time, over the visibility range of data receiving ground stations, or else triggered by user requests which conditions are typically predicted by flight dynamics models. Health maintenance required by satellites under CRC control comprises mostly attitude, orbit, power and data handling subsystems telemetry monitoring. Most housekeeping telecommands are planned on a case-by-case basis, upon telemetry trend analysis. The remaining few are mainly onboard ephemeris data updating. Because of these synergies, at CRC the flight dynamics team is also responsible for generating ground and flight operations plans. Software tools currently at use by the CRC flight dynamics team have been proven reliable over decades of continuous running, but are not easy to use or maintain. As technology rapidly changes, new machines must be acquired and, most often, they are not fully compatible with older platforms. Porting program codes from one system to another is costly. Moreover, software operation tasks such as filtering out erroneous measurement data and precisely adjusting input parameters have become a fine art that only the most expert flight dynamics operators can handle. Training a new operator for this purpose alone would be extremely time-consuming. By taking advantage of INPE’s alternative role as an academic institute, CRC has directed some scholarly researches towards satellite control automation. Most resulting works concerned about intelligent planning of flight operations, by managing time and resources among satellite passes over ground stations. Their byproducts would not afford actual spacecraft control operations without major modifications. Due to their academic focusing, they would not reflect the complexity of real systems. In order to fill this gap, a validation tool for such intelligent operations planners is proposed. This project aims at building a software tool that would verify the outputs of academic operations planners by feeding them into a satellite simulator. The tasks contained in the operations plan would be executed on the satellite simulator, which effects would be reflected on its internal statuses. These internal statuses would be compared to design limits set by the satellite developers, in order to either accept or reject the operations plan. It is expected that the resulting validated plan would be workable with actual missions. The final decision on its usability would be decided by the flight dynamics team, upon comparison of results with those from the legacy system currently in use.

With the development of the space industry, LEO simulation platforms are increasingly important. Prior work mainly focused on the dynamics of constellation topology, routing algorithms against the topological motion, and the behavior of LEO constellation networks, but neglected real-time and completeness properties. In our work, we design a real-time and complete network simulation framework, named LEOCN, that is more meaningful and detailed for researchers than previous work on LEO satellite constellation simulations. LEOCN is supported by Linux System, which makes the framework more realistic and relieves the computational burden. Meanwhile, LEOCN deeply considers topology and routing algorithms, visualization, satellite mobility, communication protocols, and network traffic problems. On LEOCN, we can deploy routing algorithm experiments via SDN. We evaluate the performance of LEOCN in large-scale constellation scenarios, and the results demonstrate the superiority of the real-time and complete network simulation framework.

Flight dynamics modeling and analysis for a Mars helicopter

The free-wing tilt-body technology refers to an unconventional aircraft design concept that enables short-takeoff and landing, reduced sensitivity to gust and to center of gravity change. Due to its unique nature arising from an articulated wing, fuselage, and tail configuration along with a strong propulsive system influence, the resulting vehicle aerodynamics and flight dynamics are quite different from those of a conventional fixedwing aircraft. In previous studies extensive aerodynamic analysis, both experimental and computational, were reported, and also a flight dynamic model based on the wind tunnel test data was developed. In this study, a scaled flying model of a generic free-wing tilt-body aircraft is built. Flight tests are carried out to further investigate the free-wing tilt-body technology, and also to validate the previously developed flight dynamic model. An accurate flight dynamic model is essential for model-based flight control design studies.

This study presents systematic procedures for the development of a cost-effective flight simulator by integrating multiple software tools into a unified simulation environment. The simulator framework combines both Microsoft Flight Simulator and Blender for 3D realistic CAD model generation, JSBSim as the aerodynamics and flight dynamics model, and Unreal Engine as the primary simulation platform. The Cessna T-37 aircraft is used as a case study to develop the simulator. The development process includes the preparation of the 3D CAD model, the integration of the aerodynamic data, and real-time control surface animations, ensuring an immersive and accurate representation of the aircraft behavior. The JSBSim is implemented to handle the flight dynamics while Unreal Engine is used for visualization and interactivity. Additionally, the simulation includes an analysis of the aircraft’s natural modes, such as phugoid, short-period, rolling, spiral and dutch-roll modes, to assess its dynamic stability. The response characteristics of these modes are examined to ensure consistency with theoretical expectations and to identify nonlinear effects present in the simulation. The results demonstrate the feasibility of integrating open-source tools for flight simulation and highlight the efficiency of the proposed cost-effective framework in replicating realistic flight performance.

A method to identify the flight dynamics model of a helicopter in hovering is put forward in this paper. First, a mechanism model of the helicopter is given and a great lot of helicopter flight tests are performed based on this model. Then, flight data obtained from the tests are used in the proposed stepwise regression identification approach to ascertain the parameters of flight dynamics model and a state-space model of the helicopter in hovering is built. Finally, flight experiments are carried out and the results validate the correctness and accuracy of the model.

This paper discusses the development of a quantitatively-accurate non-linear hybrid flight dynamics model of a hover-capable Air-Launched Tailsitter Unmanned Aerial System (ALUAS) in order to 1) understand its dynamics during complicated maneuvers, and 2) provide a high-fidelity framework to develop novel control laws. Wind tunnel tests were conducted on a 1:1 scale model of the full aircraft to measure the airloads, which were used in the simulation as a lookup table. Flight tests of the ALUAS were performed in hover, transition, and cruise to collect a large amount of unique state measurements by providing large excitations to induce highly transient motion. The flight dynamics predictions using Rotorcraft Comprehensive Analysis System (RCAS) software were then compared with experimental flight test data. To correct any discrepancies in the RCAS physics-based predictions, a correction was learned from the experimental measurements, making use of the large amount of collected flight test data. Using a neural network to learn this correction, the end result was a quantitatively accurate neural network assisted flight dynamics model. The accuracy of current simulations in complex flight states successfully demonstrates the applicability of the proposed methodology for correcting the dynamics model of novel out-of-the-box aircraft configurations.

This paper proposes a two-level, data-driven, digital twin concept for the autonomous landing of aircraft, under some assumptions. It features a digital twin instance (DTI) for model predictive control (MPC); and an innovative, real-time, digital twin prototype for fluid-structure interaction and flight dynamics to inform it. The latter digital twin is based on the linearization about a pre-designed glideslope trajectory of a high-fidelity, viscous, nonlinear computational model for flight dynamics; and its projection onto a low-dimensional approximation subspace to achieve real-time performance, while maintaining accuracy. Its main purpose is to predict in realtime, during flight, the state of an aircraft and the aerodynamic forces and moments acting on it. Unlike static lookup tables or regression-based surrogate models based on steady-state wind tunnel data, the aforementioned real-time digital twin prototype allows the DTI for MPC to be informed by a truly dynamic flight model, rather than a less accurate set of steady-state aerodynamic force and moment data points. The paper describes in detail the construction of the proposed two-level digital twin concept and its verification by numerical simulation. It also reports on its preliminary flight validation in autonomous mode for an off-the-shelf unmanned aerial vehicle instrumented at Stanford University. This article is part of the theme issue 'Data-driven prediction in dynamical systems'.