Flight Envelope Research Articles

Aircraft Closed-Loop Dynamic System Identification in the Entire Flight Envelope Range Based on Deep Learning

Aircraft Closed-Loop Dynamic System Identification in the Entire Flight Envelope Range Based on Deep Learning

Distributed feather-inspired flow control mitigates stall and expands flight envelope

Multiple rows of feathers, known as the covert feathers, contour the upper and lower surfaces of bird wings. These feathers have been observed to deploy passively during high angle of attack maneuvers and are suggested to play an aerodynamic role. However, there have been limited attempts to capture their underlying flow physics or assess the function of multiple covert rows. Here, we first identify two flow control mechanisms associated with a single covert-inspired flap and their location sensitivity: a pressure dam mechanism and a previously unidentified shear layer interaction mechanism. We then investigate the additivity of these mechanisms by deploying multiple rows of flaps. We find that aerodynamic benefits conferred by the shear layer interaction are additive, whereas benefits conferred by the pressure dam effect are not. Nevertheless, both mechanisms can be exploited simultaneously to maximize aerodynamic benefits and mitigate stall. In addition to wind tunnel experiments, we implement multiple rows of covert-inspired flaps on a bird-scale remote-controlled aircraft. Flight tests reveal passive deployment trends similar to those observed in bird flight and comparable aerodynamic benefits to wind tunnel experiments. These results indicate that we can enhance aircraft controllability using covert-inspired flaps and form insights into the aerodynamic role of covert feathers in avian flight.

Shock buffet onset prediction with flow feature-informed neural network

Transonic shock buffet is a significant self-excited shock oscillations and aerodynamic instability phenomenon induced by shock-boundary layer interaction, which limits the flight envelope and even causes flight accidents. The aviation industry has a significant interest in accurately predicting the shock buffet onset boundary, defined by a specific combination of Mach number and angle of attack. While the current methods of steady and unsteady numerical simulation suffer from a contradiction of efficiency and accuracy. In the current paper, a flow feature-informed neural network (FINN) model is constructed to predict the buffet onset boundary over airfoils. Typical features associated with buffet onset are extracted from the steady base flow and subsequently integrated into the hidden layer of the neural network to impose physical constraints. With the test cases of the NACA0012 airfoil at various Mach numbers, the FINN model can accurately predict the damping representing the unsteady instability margin. Compared to the direct mapping input-output neural network (NN) model, the proposed method with shock wave feature-informed has enhanced accuracy, with an average relative error decreased by 70% at extrapolated Mach numbers. This research demonstrates the effectiveness of the FINN model in predicting the buffet onset, which leverages physics features derived from the more economical steady solution far from the onset boundary at a given predicted Mach number.

Enhancing Ignition Reliability with Tail-Groove Strut Designs in Cavity-Based Combustors

As the flight envelopes of turbine-based combined cycle (TBCC) engines expand, ensuring reliable ignition and flame stability under varying conditions becomes increasingly critical. Previous work has shown a significantly changed ignition performance and flow pattern in cavity-based combustors when strut structure parameters were altered, indicating a strong correlation between the ignition process, flame structure, and the strut configuration. This suggests that further investigation is required to determine the optimal strut design. Therefore, this study examines the impact of various strut configurations through numerical simulations, validated by high-speed imaging. Findings show that the tail-groove strut designs improve the flame propagation performance compared to the normal struts, with a critical depth beyond which further increases do not enhance performance. Changes in strut length have a lesser impact than depth. Flow analysis indicates that tail-groove struts create additional recirculation zones that enhance fuel atomization and flame stability. These results suggest that optimizing strut configurations is vital for achieving reliable ignition and flame stability, advancing the development of efficient engines across a wide range of operational conditions.

Quadrotor Flight Envelope Protection with Trajectory and Yaw Tracking

This study proposes a reference governor control strategy to ensure that a quadrotor drone follows a planar trajectory while respecting the prescribed safety constraints. These constraints, including polynomial constraints accounting for aerodynamic and gyroscopic effects, were transformed into linear constraints using novel state-space augmentation. This allows for the design of a reference governor, which is designed to safeguard the drone’s flight envelope by adjusting the reference trajectory during trajectory tracking while also ensuring yaw tracking with lower priority than position tracking, especially when constraints are at risk of being violated. This study also presents simulations that illustrate the effectiveness of the proposed algorithms.

Novel Controller Methodology for the Cessna Citation X Under Turbulence During Cruise

The design of a new control approach for the longitudinal motion of the Cessna Citation X during cruise is performed using a combination of sliding mode control (SMC) system, type 1 fuzzy logic system, and adaptive control system. This methodology is presented for 1) controlling the aircraft pitch rate and 2) stabilizing the aircraft speed during turbulence. The nonlinear model of the aircraft was generated using a simulation platform, which was designed based on flight data obtained from the highest Federal Aviation Administration–certified Level-D Research Aircraft Flight Simulator. The type 1 adaptive fuzzy logic system was implemented to approximate unknown functions for constructing the equivalent part of the SMC system that handled the effects of uncertainties and turbulence. The adaptation laws, derived from the Lyapunov theorem, were used to update the approximated functions in the control law at each flight condition and simulation iteration. Using the control systems combination, the pitch rate could follow the given reference signal, while the aircraft speed remained at a reference value with and without turbulence across the whole flight envelope. Results have shown that the proposed controllers satisfied tracking performance while generating smooth elevator deflection, both of which are important for real-aircraft applications.

Aircraft Structural Assessments in Data-Limited Environments: A Validated FE Method

Aircraft operators often modify aircraft configurations, install new equipment, and alter airframes to accommodate this equipment, leading to operations in flight envelopes different from original design profile. These modifications necessitate airframe structural assessments, which typically require comprehensive aircraft design data, often unavailable to operators. This study aims to develop and validate a practical method for finite element analysis (FEA) of aircraft structures in the absence of this detailed design data. Focusing on a case study involving structural analysis of an aircraft wing, this study presents assumptions and idealizations used to develop 2.5D finite element (FE) model of the wing. Fidelity of this model is established by comparing FE analysis results with experimental data. Key validation metrics include reaction forces, load distribution at wing-fuselage attachments, and deformation at reference points on the wing under design load. Comparison between FE analysis and experimental results is carried out to substantiates accuracy of these geometric simplifications and idealizations of load-carrying behaviour of structural members. Therefore, practicality of these idealizations in absence of design data is demonstrated. This study offers a novel approach for structural assessments of aircraft without relying on proprietary design data. The validated method enhances capability of aircraft operators to perform effective structural analyses, thereby extending service life of aircraft with continued airworthiness.

Accelerated pump tube concept for hypersonic ground testing

This paper examines a new hypersonic wind tunnel concept which is referred to here as an ‘accelerated pump tube’ (APT). The facility can be considered a hybrid between a gun tunnel and an expansion tube. Like a gun tunnel, the test gas is isentropically compressed with a piston to raise its pressure and temperature; like an expansion tube, the compressed test gas is subject to an unsteady expansion to further increase its enthalpy and stagnation pressure. State-to-state analytical calculations incorporating high temperature equilibrium chemistry are presented which demonstrate that the APT is theoretically able to simulate a wide hypersonic terrestrial flight envelope from Mach 5–14, with significant capacity for pressure-length scaling. Potential practical benefits of this concept include relatively simple internal flow processes, removal of the need for a film secondary diaphragm and helium as a driver gas, and a reduction in experimental uncertainty through better defined internal boundary conditions and relatively low mechanical complexity. To assess the feasibility of the APT concept in a practical context, the paper considers how an APT based around a 25 m long, 600 mm diameter pump tube should be configured for a Mach 10 test flow. One-dimensional Lagrangian CFD analysis is used to compute piston dynamics for three different pump tube compression ratios and the associated test flows are characterised. The CFD results suggest that the concept should be viable in practice, and also validate the Mach 10 state-to-state calculations.

Control allocation optimization for an over-actuated tandem tiltwing eVTOL aircraft considering aerodynamic interactions

This paper describes control allocation strategies for a tandem tiltwing electric vertical take-off and landing (eVTOL) aircraft with distributed propulsion. The control mappings are constructed as local surrogate models that relate the control effectors to the aircraft's aeropropulsive forces and moments across the full flight envelope, including interactional aerodynamics effects. Control allocation optimization problems are formulated based on force and moment commands for specific flight conditions. Specifically, a nonlinear programming formulation based on nonlinear control mapping is proposed for control allocation optimization, and the problem is solved using a sparse nonlinear optimizer. The solutions obtained from different formulations such as the minimization of force and moment residuals and the minimization of control effort are investigated. Furthermore, these solutions are compared with the solutions obtained using linear control mapping-based formulations. Results presented for the cases of forward flight, low speed flight & hover, and flight in the transition corridor suggest that considering aerodynamic interactions while formulating and solving the control allocation problem is necessary for higher levels of accuracy compared to linear approaches. One-propeller-out scenarios and moment and force generation cases are also investigated. Finally, control allocation for steady and accelerated operation in the transition corridor is discussed. The contribution of the methods and results in the paper is a nonlinear control allocation methodology for the entire flight envelope of an over-actuated tandem tiltwing eVTOL aircraft.

Robust acceleration schedule design for gas turbine engine using multilayer perceptron network with adaptive sample class weighting

The acceleration schedule is crucial for generating acceleration control references for the gas turbine engine (GTE) and ensuring optimal acceleration performance. However, under harsh operating conditions, GTEs may encounter difficult-to-diagnose pressure sensor faults, which lead to inaccurate control references and decreased acceleration performance. This paper proposes a data-driven robust acceleration schedule (RAS) design method to tackle this issue, including fault data augmentation and adaptive sample class weighting (ASCW). Fault data augmentation generates multiple pressure fault sample classes from a normal acceleration schedule dataset. Due to the redundant pressure sensor configuration, the RAS can reconstruct these classes and generate accurate control references when a single pressure sensor fails. The ASCW employs a multilayer perceptron network to reconstruct the normal and fault sample classes accurately. Proportional integral regulation adjusts their weights during training to ensure balanced reconstruction precision. Simulation cases were conducted to verify the effectiveness of the RAS under actual GTE conditions, including engine-model mismatches, performance deterioration, flight envelope, and measurement uncertainty. The results demonstrate that the RAS ensures superior acceleration performance of GTEs across the full flight envelope in both normal and single pressure sensor fault scenarios. Additionally, the ASCW achieves reconstruction precision of 0.068 %, 0.080 %, 0.080 %, 0.082 %, and 0.077 % for normal and fault sample classes, respectively, prioritizing the precision of the normal sample class and balancing the precision of fault sample classes.

Fixed-time anti-disturbance control for nonlinear turbofan engine with impulsive prescribed performance

To analyze the robust control problem of turbofan engine within a large flight envelope, a fixed-time prescribed performance control scheme is proposed for the nonlinear turbofan engine in presence of unknown disturbances and possibly discontinuous reference signals. Firstly, the equilibrium manifold expansion (EME) modeling method is adopted for the turbofan engine to construct an affine nonlinear model. Then, considering the possibly discontinuous reference signals, a novel fixed-time prescribed performance function (FxTPPF) with impulsive characteristic is presented to successfully deal with the singularity problem caused by its discontinuity situation. In what follows, a fixed-time nonlinear disturbance observer (FxTNDO) is developed to realize fast estimation of disturbances within fixed time. According to the transformed error system and disturbance estimations, a fixed-time anti-disturbance composite controller is further developed. By borrowing Lyapunov stability theory, the boundedness of all error signals in the impulsive closed-loop system is proved. Finally, simulation results indicate that this control scheme can ensure rotor speeds effectively to track the desired commands within a predefined time after the appearance of a discontinuity and the tracking errors are limited to the performance bound all along.

Addressing Launch and Deployment Uncertainties in UAVs with ESO-Based Attitude Control

This paper describes the design and implementation of a novel three-axis attitude control autopilot scheme for tube-launched, air-deployed UAVs. In early flight tests, various factors, such as model uncertainties during launch, aerodynamic uncertainties, geometric parameter changes during deployment, and significant uncertainties in booster rocket installation, exceeded the control capabilities of the attitude autopilot, causing flight instability. In order to address these issues, a numerical simulation model of the full launch process considering deviations was established based on early flight tests. A cascade attitude controller was then designed using an extended state observer (ESO), and the boundedness of control errors under unknown bounded disturbances was theoretically proven, providing requirements for the parameter tuning of the cascade controller. Comparative experiments and a second flight test both demonstrate that the ESO-based cascade attitude controller exhibits strong feedforward disturbance compensation under high-uncertainty conditions, effectively achieving stable control within the flight envelope.

Dual-Loop μ-Synthesis Direct Thrust Control for Turbofan Engines

As the power unit of an aircraft, the engine’s primary task is to provide the demanded thrust, making research on direct thrust control crucial. However, being a complicated multivariable system, effective multivariable direct thrust control methods are currently lacking. The main content of this paper is threefold. First, it presents a dual-loop multivariable μ-synthesis direct thrust control scheme for mixed-exhaust low-bypass turbofan engines, which is a typical rotationally symmetric machine. The scheme adjusts fuel flow for thrust control and nozzle area to control the turbine pressure ratio, ensuring thrust tracking while maintaining the engine’s key parameters within safe limits. Second, a fast, accurate thrust estimation algorithm based on aerodynamic thermodynamics and component characteristics is introduced. At last, considering the model uncertainties between off-design and design points, a weight function frequency shaping μ-synthesis control design method is proposed to address internal loop coupling and external disturbance suppression. Nonlinear simulations within the flight envelope show that μ-synthesis direct thrust control achieves robust servo tracking and disturbance rejection, with a maximum steady-state thrust error of no more than 0.1%, and the key parameters are not over their safety boundaries.

Thrust online fusion estimation of high-flow dual variable cycle engine

For the aeroengines, thrust is a crucial performance parameter which is closely related to the mission accessibility. Accurate thrust control is conducive to excavate the potential of the variable cycle engine (VCE) in different operation modes, which meets the requirements of future engine control system. However, the thrust is unmeasured in flight. Besides, the traditional thrust estimation method is difficult to meet the wide-area thrust control requirements due to the strong nonlinearity and large flight envelope for a neoconfiguration VCE of the high-flow triple-bypass, named high-flow dual variable cycle engine (HDVCE). This paper proposes a novel online fusion thrust estimation method mainly under single operation mode for the HDVCE. The problem of individual engine differences is also focused, and the combination of model and data-driven is to generate the thrust estimation with fusion strategy. At first, a multi-combustion chamber coupled dynamic model is established for the HDVCE, and an adaptive network is used for model optimization to improve the model accuracy. On this basis, an EKF-based thrust estimator is built. Secondly, a data-driven thrust estimator is pre-trained by a stacked autoencoder (SAE) and then tuned by back propagation (BP) neural network. Subsequently, the thrust integration is incorporated based on estimation results from the EKF-based and data-driven one using Euclidean distance fusion strategy. Simulation results show that the fusion estimation method proposed in this paper, on the one hand, reduces the effect of model instability on EKF. On the other hand, it ensures the estimation accuracy of SAE-BP far from the training point. The comparisons also reveal that the fusion one produces more than 97% in thrust estimation accuracy and is better than the remaining ones, which is promising for thrust control applications.

A novel simplified simulation method for the precooler based on the virtual source term: modeling, validation and application

Precooling technology is one of the promising approaches for expanding the flight envelope of conventional turbine engines and enhancing flight performance at high Mach numbers. Within this domain, a crucial challenge is to rapidly and accurately obtain the flow and heat transfer characteristics of the precooler. Currently, full-size simulation of the precooler is impractical, while simplified and fast simulation methods employed in previous research have exhibited certain deficiencies, including excessive simplification and unconvincing validation. In this study, a novel simplified simulation method for the annular precooler based on the virtual source term model was proposed. This method comprehensively considered the axial and radial non-uniformity of airflow caused by the coupling effect between the precooler and the inlet channel in the actual flow field. Subsequently, systematic validations of the reliability and superiority of this method were conducted, along with its application in the overall performance calculation of the precooled engine. The results demonstrate that the simplified method proposed in this paper showcases higher accuracy than the methods employed in previous research. Compared with the real model, the relative errors of the overall parameters are within ± 1 %, and the relative errors of the distortion indices for total temperature and total pressure are 5.1 % and −1.5 %, respectively. Meanwhile, the number of computational mesh cells is reduced by more than 95 %. Moreover, the first application of the simplified method in the overall performance calculation of the precooled engine reveals that the traditional low-dimensional model underestimates both the total pressure loss of the precooler and the fuel consumption for precooling, resulting in larger calculation deviations in the thrust and equivalence ratio, respectively. The values of thrust calculated with the high-dimensional virtual model show an average decrease of 2.01 % compared to those derived from the low-dimensional model. In addition, a higher Mach number results in lower effectiveness, higher air inlet temperature, and reduced resistance of the precooler to heat exchange imbalance caused by flow non-uniformity. These factors lead to an escalating relative deviation of the equivalence ratio between the two models, reaching 26.45 % at Mach 5.

Studies on in-flight aircraft rerouting

With the publication of this article, the authors continue the research on the development and testing of a methodology for in-flight aircraft rerouting which have begun in previously published articles in the Civil Aviation High Technologies of the Moscow State Technical University of Civil Aviation. This article presents the results of the study in terms of developing the potentials of the methodology from reconfiguring a route of a hypothetical aircraft and obstacles in the horizontal plane, which were previously demonstrated, prior to rerouting in both the horizontal and vertical planes for two different types of obstacles: 1) ground natural or artificial (mountain, power line support, etc.); 2) air (squall line, prohibited flight area, etc.) and their combinations using an example of a Mi-8 helicopter flight on route using a real digital map of the terrain. As mentioned above, a large amount of aviation accidents is associated with the loss of control in-flight, as well as the collision with terrain in a controlled flight (categories LOC-I, CFIT, LALT). As a result of the investigation of the aviation accidents, it was found that these accidents are often caused by the requirement to reroute quickly due to obstacles, for example, a squall line. When determining alternatives to avoid an obstacle, as well as while implementing the selected route for avoiding action, the crew makes errors due to the increased psychophysiological load and lack of time. The methodology and the algorithms, proposed by the authors, make it possible to assess the safety of an original route, estimate options for alternatives to avoid around obstacles detected in-flight, check them for feasibility, taking into account aircraft performance, flight envelope, and also select the optimal route from the view of some criterion, for example, based on minimizing the route length increase, reducing additional fuel consumption, the time required to implement a new route of flight, etc.

Compound Attitude Control Strategy for Reusable Launch Vehicle Based on Improved Particle Swarm Optimization Algorithm

This study introduces an advanced dual-mode compound attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers and dynamically adjusting the inertia weights and learning factors of the PSO algorithm to achieve the balance between global and local optimization performance, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers’ weighting coefficients, culminating in an optimized dual-mode compound attitude control system. A series of comparative simulation analyses are thoroughly executed to appraise the system’s responsiveness, stability, precision, and resilience to interference. The simulation outcomes demonstrate an average reduction of 42.21% in step response overshoot, an 18.52% decrease in settling time, a 53.18% decline in steady-state error, a 56.80% drop in the maximum deviation value, a 55.82% improvement in recovery speed, and a 75.61% enhancement in tracking precision for the proposed controller. The findings clearly verify the superior performance of the proposed control system, affirming its contribution to the advancement of RLV attitude control. The proposed controller holds promising potential for real application in attitude control systems and is poised to augment the reliability and mission success rate of RLVs under intricate flight scenarios.

Enhanced Fuzzy-Based Super-Twisting Sliding-Mode Control System for the Cessna Citation X Lateral Motion

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC.

Investigation of Hybrid Laminar Flow Control Capabilities from the Flight Envelope Perspective

The present work conducts a multifidelity aerodynamic design of a medium-range commercial aircraft wing featuring hybrid laminar flow control (HLFC) technology. The design was performed to investigate the capabilities of the HLFC, considering the entire design flight envelope, low-speed performance requirements, and various potential mission scenarios. A combination of medium-fidelity aerodynamic design tools for laminar flow control using MSES-COCO-LILO, CFD RANS for high-lift cases, the quasi-three-dimensional for database generations, and SUAVE for mission analysis were used to design and assess aircraft’s performance with the HLFC wing. Studies of the design objective demonstrated a conflict between friction and compressibility drag that strongly affects the design objective function and the wing performance at various off-design conditions. A strong dependence of HLFC on flight conditions was observed to indicate technology performance limitations and a tradeoff between airplane emissions, range, and costs. Finally, a comparison of medium- and low-fidelity performance results showed deviations in the design fuel burn of 4%, a minimum possible harmonic range difference of 3%, and direct operating costs of 2%. The outcome suggests the need for better compressibility and parasite drag models for early design stages to accurately model the HLFC technology without introducing complicated methods at the first sizing steps.

Data-Driven Approach for Fixed-Frame Rotorcraft Mast-Moment Estimation

In contrast to the fixed frame, measuring rotor states in the rotating frame of a helicopter rotor is complex and costly and therefore usually unaffordable for small production rotorcraft. In this paper, a data-driven approach to linear observer tuning is proposed and illustrated for predicting the rotor mast bending moments using fixed-frame rigid-body measurements only. The method is demonstrated on a research helicopter, where flight test data is used to identify three possible design models, optimize their respective observer performances, and select the most promising model structures for final application. The resulting observers are assessed in the time and frequency domains using sweep and turbulence data. The results show that data-driven observer tuning allows the effective adaptation of the observer to the reference data. To extend the observer to a larger flight envelope, improved models and a larger database would be required.