This paper presents a new approach to force fighting equalisation in a redundant active-active-active rudder actuation system that is used for the primary flight control system of a turboprop regional aircraft. The related coupled problem of force fighting scenario, and the hydraulic architecture of electronic-hydrostatic actuator (EHA) are analysed, the mathematical model of the EHA system is built. The virtual test bench is designed to evaluate the performance of the force fighting equalisation strategy. The proposed methodology is tested on an iron bird test rig. The physical experiment shows that the fighting force is minimised under all flight conditions, meets the low cost requirement and can be a very reliable system. The proposed methodology can be applied to other types of aircraft’ flight actuation systems.

A spacetime formulation is presented to solve unsteady aerodynamic problems involving large deformation or topological change such as store separation, slat and flap deployment or spoiler deflection. This technique avoids complex CFD meshing methods, such as Chimera, by the use of a finite-volume approach both in space and time, and permits a locally varying real timestep. The use of a central-difference scheme in the time direction can yield non-physical transient solutions as a consequence of information travelling backwards in time. Therefore, an upwind formulation is provided and validated against one-dimensional and two-dimensional test cases. A hybrid formulation (central in space, upwind in time) is also given and unsteady cases are computed for a spoiler and spoiler/flap deployment, with all three formulations compared, demonstrating that the use of an upwind time stencil yields more representative physical solutions and improves the rate of convergence.

Modern low-altitude unmanned aircraft (UA) detection and surveillance systems mostly adopt the multi-sensor fusion technology scheme of radar, visible light, infrared, acoustic and radio detection. Firstly, this paper summarises the latest research progress of UA and bird target detection and recognition technology based on radar, and provides an effective way of detection and recognition from the aspects of echo modeling and micro motion characteristic cognition, manoeuver feature enhancement and extraction, motion trajectory difference, deep learning intelligent classification, etc. Furthermore, this paper also analyses the target feature extraction and recognition algorithms represented by deep learning for other kinds of sensor data. Finally, after a comparison of the detection ability of various detection technologies, a technical scheme for low-altitude UA surveillance system based on four types of sensors is proposed, with a detailed description of its main performance indicators.

The aerodynamic modelling is one of the challenging tasks that is generally established using the results of the computational fluid dynamic software and wind tunnel analysis performed either on the scaled model or the prototype. In order to improve the confidence of the estimates, the conventional parameter estimation methods such as equation error method (EEM) and output error method (OEM) are more often applied to extract the aircraft’s stability and control derivatives from its respective flight test data. The quality of the estimates gets influenced due to the presence of the measurement and process noises in the flight test data. With the advancement in the machine learning algorithms, the data driven methods have got more attention in the modelling of a system based on the input-output measurements and also, in the identification of the system/model parameters. The research article investigates the longitudinal stability and control derivatives of the aerodynamic models by using an integrated optimisation algorithm based on a recurrent neural network. The flight test data of Hansa-3 and HFB 320 aircraft were used as case studies to see the efficacy of the parameter estimation algorithm and further, the confidence of the estimates were demonstrated in terms of the standard deviations. Finally, the simulated variables obtained using the estimates demonstrate a qualitative estimation in the presence of the noise.

The reduction of computational costs in the context of the Multidisciplinary Design Optimisation of a typical medium-range aircraft was investigated through an assessment of active constraints and the use of multi-fidelity models-based estimation of drag and structural stress. The results show that for this problem, from the set of considered constraints that includes flutter boundary, the active constraint is a 2.5g pull up Maximum Take Off Weight. Results show that the multi-fidelity approach reduced the required high-fidelity aerodynamic number of evaluations, for both drag assessment and stress assessment with sufficient level of accuracy for the former and conservatively for the latter. Further computational cost reduction can be achieved using a surrogate model based Multidisciplinary Design Optimisation. The best configuration attained shows an Aspect Ratio increase of 16%, a reduction of 4.5% in fuel consumption and wing structural weight increase of 2.7% relative to a predefined baseline configuration.

A control system verification framework is presented for unmanned aerial vehicles using theorem proving. The framework’s aim is to set out a procedure for proving that the mathematically designed control system of the aircraft satisfies robustness requirements to ensure safe performance under varying environmental conditions. Extensive mathematical derivations, which have formerly been carried out manually, are checked for their correctness on a computer. To illustrate the procedures, a higher-order logic interactive theorem-prover and an automated theorem-prover are utilised to formally verify a nonlinear attitude control system of a generic multi-rotor UAV over a stability domain within the dynamical state space of the drone. Further benefits of the procedures are that some of the resulting methods can be implemented onboard the aircraft to detect when its controller breaches its flight envelope limits due to severe weather conditions or actuator/sensor malfunction. Such a detection procedure can be used to advise the remote pilot, or an onboard intelligent agent, to decide on some alterations of the planned flight path or to perform emergency landing.

Although the problem of locked-in deep stall is well documented over many years, there currently exists no consistent procedure that can guarantee recovery. Past studies have suggested that it might be possible to rock the aircraft in pitch to destabilise the statically stable deep stall trim point, thereby gaining enough momentum to push the nose down. However, the methods used in these studies are either of preliminary or empirical nature and cannot guarantee recovery. In this paper, we use bifurcation analysis to derive a recovery manoeuvre, specifically by assessing the aircraft’s nonlinear frequency response under an elevator forcing. The ensuing nonlinear Bode plot detects unstable (divergent) solutions near resonance that contribute to a successful deep stall recovery. Moreover, the nonlinear resonant frequency is slightly lower than the result obtained using linear analysis, and time simulation shows that relying on the linear result does not lead to a successful recovery. It is also found that at the high angles of attack associated with deep stall, the frequency separation between the short period and phugoid mode is significantly reduced, leading to only one visible peak in the frequency response. This feature is also reflected in the time-domain step response.

Reinforcement learning has previously been applied to the problem of controlling a perched landing manoeuvre for a custom sweep-wing aircraft. Previous work showed that the use of domain randomisation to train with atmospheric disturbances improved the real-world performance of the controllers, leading to increased reward. This paper builds on the previous project, investigating enhancements and modifications to the learning process to further improve performance, and reduce final state error. These changes include modifying the observation by adding information about the airspeed to the standard aircraft state vector, employing further domain randomisation of the simulator, optimising the underlying RL algorithm and network structure, and changing to a continuous action space. Simulated investigations identified hyperparameter optimisation as achieving the most significant increase in reward performance. Several test cases were explored to identify the best combination of enhancements. Flight testing was performed, comparing a baseline model against some of the best performing test cases from simulation. Generally, test cases that performed better than the baseline in simulation also performed better in the real world. However, flight tests also identified limitations with the current numerical model. For some models, the chosen policy performs well in simulation yet stalls prematurely in reality, a problem known as the reality gap.

In the era of Unmanned Aerial Systems (UAS), an onboard autopilot occupies a prominent place and is inevitable for many of their modern applications. The efficacy of autopilot heavily relies upon the accuracy of the sensors employed and the capability of the onboard flight controller. In general, aerodynamic behaviour and flight dynamic capabilities of Unmanned Aerial Vehicles (UAVs) govern the selection and the design of flight controllers. Precise modeling of linear aerodynamic characteristics from flight data can be achieved using many of the existing classical parameter estimation techniques such as Output Error Method (OEM), Equation Error Method (EEM), and Filter Error Method (FEM). However, all the classical methods may not be readily applicable for aerodynamic modeling in nonlinear flight envelopes. The current manuscript is an attempt to exploit the capabilities of the Artificial Intelligence (AI) technique, named Particle Swarm Optimisation (PSO), in combination with Least Squares (LS) cost function to perform linear as well as nonlinear aerodynamic parameter estimation. The aforementioned task is accomplished by considering flight data from manoeuvers pertaining to linear angles of attack, moderate and near stall flight envelopes of two different UAVs with cropped delta planform geometry. Parameters estimated using the proposed LS-PSO method are consistent with minimum standard deviation and are on a par with OEM estimates. The proposed LS-PSO method enhances the capabilities of LS-based EEM while estimating stall characteristic parameters, which was not possible with LS alone. The longitudinal and lateral-directional static parameters estimated from the full-scale wind tunnel testing of the two UAVs were also used to corroborate the results obtained from the flight data using the LS-PSO method.

Flutter suppression is an important measure to improve fatigue life and enhance the performance of aircraft in modern aircraft design. In order to design more effective controllers for flutter suppression with high efficiency, an efficient reduced-order framework for active/passive hybrid flutter suppression is proposed. The traditional CFD-based ROMs have been successfully applied to active flutter suppression with high accuracy and efficiency. But, when a structure modification is made such as in aeroelastic tailoring and aeroelastic structural optimisation, the structural model should be updated, and the expensive, time-consuming CFD-based ROMs have to be reconstructed; such a process is impractical for passive flutter suppression. To overcome the realistic challenge, an efficient reduced-order framework for active/passive hybrid flutter suppression is proposed by extending an efficient aeroelastic CFD-based POD/ROM which we have developed. The proposed framework is demonstrated and evaluated using an improved AGARD 445.6 wing model. The results show that the proposed framework can accurately predict the aeroelastic response for active/passive hybrid flutter suppression with high efficiency. It provides a powerful tool for active/passive hybrid flutter suppression, and therefore, is ideally suited to design more effective controllers, and may have the potential to reduce the overall cost of aircraft design.

A fast numerical method for unsteady aerodynamic calculation of 3D wing is established, which is suitable for the preliminary design. Based on the lifting-line method, the aerodynamic data of the 2D aerofoil obtained by the unsteady CFD simulation is used as the model input to solve the aerodynamic force of the 3D wing. Compared with the traditional steady lifting-line method, the augmented method adopts the unsteady Kutta-Jouowski (K-J) theorem to calculate the circulation and improve the accuracy of the method through the circulation correction. The pitching motion of 3D wing at different aspect ratio and reduction frequencies are studied. The results show that the aerodynamic forces obtained by the augmented lifting-line method have good agreement with the 3D unsteady CFD calculations. Compared with 3D CFD calculation, the calculation efficiency of the improved method is increased by more than 12 times. The improved method has extensive applicability and can be used to estimate the unsteady aerodynamic forces of 3D single or multiple wing configurations.

The locus of aerodynamic centres of a finite wing is the collection of all spanwise section aerodynamic centres, and depends on aspect ratio, wing sweep and planform shape. This locus is of great importance in the positioning of vortex elements in lifting-line theory. Traditionally, these vortex elements are placed along the quarter-chord of a wing, leading to inaccurate predictions of aerodynamic coefficients for swept wings due to the discontinuity in the line of vorticity at the wing root. An analytical solution was presented by Küchemann in 1956 to determine the locus of aerodynamic centres as a function of sweep. While experimental studies have been performed to visualise this locus, no large amount of data is available to fully evaluate the accuracy of Küchemann’s analytical solution. In the present study, a numerical approach is taken using a high-order panel method for inviscid, incompressible flow to calculate the locus of aerodynamic centres for elliptic wings over a wide range of sweep angles, aspect ratios and profile thicknesses. An inviscid panel method is chosen over full CFD solutions because of their ability to isolate the inviscid phenomena. Küchemann’s prediction is compared to this numerical data. The root mean square error is calculated for each wing in a broad design space to determine the accuracy of Küchemann’s theory. It is shown to be remarkably accurate over the range of cases studied, with the root mean square error staying below 4% for all wings with aft sweep and aspect ratios higher than $R_A=5$. The actual difference between Küchemann’s prediction and numerical data is lower than that for the majority of the span for many of the wing designs considered, with the RMS error being skewed by the results at the tip. Results demonstrate that Küchemann’s analytical equations can be used as an accurate approximation for the locus of aerodynamic centres and could be used in modern numerical lifting-line algorithms*.

In real gas turbines, multiple nozzles are used instead of a single-nozzle; therefore, interactions between flames are inevitable. In this study, the effects of flame-flame interaction on the emission characteristics and lean blowout limit were analysed in a CH4-fueled single- and dual-nozzle combustor. OH* chemiluminescence imaging showed that a flame-interacting region, where the two flames from the nozzles were merged, was present in the dual-nozzle combustor, unlike the single-nozzle combustor. Flow-field measurements using particle image velocimetry confirmed that a faster velocity region was formed at the flame merging region, thereby hindering flame stabilisation. In addition, we compared the emission indices of NOx and CO between the two combustors. The emission indices of CO were not significantly different; however, a distinct effect of flame-flame interaction was indicated in NOx. To understand the effect of flame-flame interaction on NOx emissions, we measured temperature distribution using a multi-point thermocouple. Results showed that a wider high-temperature region was formed in the dual-nozzle combustor compared to the single-nozzle combustor; this was attributable to the high OH* chemiluminescence intensity in the flame-interacting region. Furthermore, it was confirmed that the size of this interacting region caused the deformation of the temperature distribution in the combustor, which can induce a difference in the increase ratio of NOx emission between high and low equivalence ratio ranges. In conclusion, we confirmed that flame-flame interaction significantly affected temperature distribution in the downstream of the flame, and the change in temperature distribution contributed primarily to the varying concentration of the emission gas.

For a common micro-satellite, orbiting in a circular sun-synchronous orbit (SSO) at an altitude between 500 and 600km, the satellite attitude during off-nadir imaging and staring-imaging operations can be up to ±45 degree on roll and pitch angles. During these off-nadir pointing for both multi-trip operation and staring imaging operations, the spacecraft body is commonly subject to high-rate motion. This posts challenges for a spacecraft attitude determination subsystem called Gyro Stellar Inertial Attitude Estimate (GS IAE), which employs gyros and star sensors to maintain the required attitude knowledge, since star trackers will severely degrade attitude estimation accuracies when the spacecraft is subject to high-rate motion. This paper analyses the star motion-induced errors for a typical star tracker, models the star motion-induced errors to assess the performance impact on the attitude estimation accuracy, and investigates the adaptive extended Kalman filter design in the GS IAE while evaluating its effectiveness.

This article presents the research status and development trends of Vertical Take-off and Landing hybrid Unmanned Aerial Vehicles. In this research, a special emphasis is laid on the design philosophies, analysis techniques, dynamic modeling, and control laws of hybrid VTOL UAVs. It studies and compares various design configurations of hybrid VTOL UAVs, based on key design features such as aerodynamic performance, flight stability, structural strength, propulsive power, avionics systems, flight controls, autonomy, ease of fabrication and flight transition mechanisms. The benefits and shortcomings of each design configuration are expressed in detail. A selection problem is formulated in a fuzzy environment and the Multi-Attribute Decision-Making technique is employed. Ongoing research projects in the field are discussed and a novel design of tail sitter hybrid VTOL UAV is presented by the authors. This work serves as a useful guide for the prospective explorers of this challenging field of research.

For a multi-vectored propeller aerostat with actuator faults, this study presents a fault-tolerant tracking control strategy, which includes fault modeling, observer, force estimation and tracking controller. Fault modeling considers the four types of faults of vectored propellers, namely, thrust offset, thrust efficiency loss, vectored angle offset and vectored angle stuck. Actuator faults can be determined from the fault observer, which identifies the thrust offset from the acceleration difference of the faulty aerostat with the ideal model. For tracking positions, a traditional PID controller is constructed with virtual control, compensated with the estimated fault force. The control allocation scheme is proposed to redistribute the available actuators in case faults occur. Simulation results of position tracking prove the effectiveness of the proposed strategy.

The impact of alternative aviation jet fuels and their properties on lean blowout (LBO) limits has recently raised several questions in the jet fuel area. There is a need for a detailed investigation of the impact of fuel properties on the LBO limit involving actual engine hardware. This study investigates the impact of a range of alternative aviation jet fuels with notable differences in physical and chemical properties and derived cetane number (DCN) on the LBO limit and their effects on key performance indicators. LBO performance results for ten different alternative fuels using a Rolls-Royce single-can Tay combustor are presented in this study. The study also assesses impact of different equivalence ratios and flow rates on LBO, with the aim of determining the impact of a certain range of operating conditions. The results are further analysed to determine the influence of fuel chemical and physical properties on the LBO limit. Finally, based on results in the above experiments, individual fuel properties are adjusted for subsequent experimental analysis of blended fuels. With this approach, 25 additional fuel blends are evaluated and presented, with an emphasis on varying the DCN. This study provides effective data and results to facilitate future fuel optimisation and reduce the risk of a negative performance of new fuels in gas turbines.

The objective of the present work is to estimate the performance of a turbojet engine during Fluidic Thrust Vectoring (FTV) employed by injecting the secondary-jet at the throat of a convergent nozzle. The nozzle performance maps and effective nozzle throat area obtained from experiments are coupled with the performance of a conventional engine (without FTV) using an iterative algorithm developed as a part of this work. The performance is estimated for different flow rates of secondary-jet sourced either from a separate compressor or the engine’s compressor. During FTV, the operating point shifted towards the surge line with increased turbine entry temperature. The desired and obtained vector angles and thrust magnitudes are different. At high secondary-jet flow rates, the turbine operation moved out of its performance map. These aspects should be incorporated while integrating the FTV at the system level, thus, asserting the importance of FTV studies coupled with engine performance.

Airports have been frequently affected by different internal and external disruptive events, which generally deteriorated their planned/regular performances. Their resilience is defined as the ability to withstand and maintain a certain level of functionality of performances compared to their reference regular/planned level during the impact of disruptive events and to recover reasonably rapidly afterwards. Robustness is defined as the level of saved functionality of performances compared to their planned/regular level, enabling continuous operations during the impact of disruptive events. The level of deteriorated functionality compared to that of the planned/regular functionality of performances represents their vulnerability. This paper develops a methodology for assessing resilience, robustness and vulnerability of airports affected by a given disruptive event(s). The methodology consists of analytical models of indicators of operational, economic, social and environmental performances of airports and other main actors/stakeholders involved. These indicators are used as figures-of-merit in analytical models for assessing their cumulative and time-dependent resilience, robustness, and vulnerability. The methodology is applied to assess resilience, robustness and vulnerability of two large airports – LHR (London Heathrow, UK) and NYC JFK (John F. Kennedy, US) – affected by a global and lasting external disruptive event – the COVID-19 pandemic disease. Based on the indicators of operational and economic performances, the results indicate very low resilience and robustness and very high vulnerability of both airports and their other main actors/stakeholders involved. Their resilience and robustness based on the indicators of social and environmental performances were not substantively different from the corresponding vulnerability. In absolute terms, LHR airport has been affected stronger than its NYC JFK counterpart. Savings in costs/externalities during the observed period under the given conditions have modestly compensated for total losses of both airports and their main actors/stakeholders involved.