Aircraft Control Research Articles

Closed-Loop Control of Dynamic Oblique Shock with Arc Plasma

The fluctuations caused by the dynamic shock wave and its interaction with the boundary layer bring formidable challenges for aerodynamic design and stable control of supersonic aircraft. The mechanism of closed-loop control for dynamic oblique shock stabilizing with arc plasma is numerically studied. Two types of dynamic oblique shocks are formed in supersonic airflow by a compression ramp rotation and incoming Mach number variation, respectively. A closed-loop controller is established to connect the arc plasma deposited power with the pressure ratio across the dynamic shock by using the proportional-integral method. It realizes the shock pressure ratio stabilized in the desired target value with a local overshoot appearing at the initial excitation and a more stable flow downstream of the oblique shock during excitation state for both types of dynamic shock control. The effects of arc plasma length and ramp rotating speed on the closed-loop control for the dynamic shocks induced by ramp rotation are further discussed. Results show that the arc plasma with longer length is more favorable to the dynamic oblique shock control with lower energy consumption and total pressure loss. The pressure ratio fluctuation is increased at higher ramp rotation speed, but its standard deviation is still limited to 0.3% of the desired target value during excitation state.

Dynamic Takeoff and Landing Control for Multi-Rotor eVTOL Aircraft

Dynamic Takeoff and Landing Control for Multi-Rotor eVTOL Aircraft

Less conservative robust reference governors and their applications

The applications of reference governors to systems with unmeasured set-bounded disturbances can lead to conservative solutions. This conservatism can be reduced by estimating the disturbance from output measurements and canceling it in the nominal control law. In this paper, a reference governor based on such an approach is considered and time-varying, disturbance and state estimation errors bounding sets are derived. Consequently, the traditional implementation of a reference governor, which exploits a constraint admissible positively-invariant set of constant commands and initial states, is replaced by one which utilizes a time-dependent sequence of similar sets (which are not necessary nested). Examples are reported which include two applications to longitudinal control of aircraft that illustrate handling of elevator uncertainty and wing icing.

Extended State Observer Based Generalized Predictive Control for Aircraft at High Angle of Attack

Extended State Observer Based Generalized Predictive Control for Aircraft at High Angle of Attack

Finite-Time Guidance and Control for Uncrewed Receiver Aircraft in Aerial Refueling Rendezvous

Finite-Time Guidance and Control for Uncrewed Receiver Aircraft in Aerial Refueling Rendezvous

Prediction model of aircraft hinge moment: Compressed sensing based on proper orthogonal decomposition

By hinge moment, we mean the aerodynamic torque exerted on the rudder shaft by the airflow passing through the aircraft control surface, with obtaining high-precision results often relying on wind tunnel tests. Due to the complex aerodynamic balance insulation and installation errors that must be considered in cryogenic wind tunnels, the main method for calculating hinge moments is to directly integrate surface pressure distribution information. However, it is usually difficult to arrange enough pressure taps, resulting in the accuracy failing to meet expectations. Combining the sparse wind tunnel test data and low-precision computational fluid dynamics results, this paper introduces the compressed sensing based on proper orthogonal decomposition (CS-POD) method and presents the sub-Ma model and the full-Ma model for predicting hinge moments. The number of sensors and sensor positions are determined based on the sparsity of the numerical simulations and basis functions. Then, the CS algorithm solves the basis coefficients. Finally, the hinge moments are obtained by integrating the reconstruction pressure distribution which is calculated by linearly combining the basis functions and basis coefficients. The result shows that the full-Ma model exhibits higher prediction accuracy with approximately five sensors under subsonic and transonic cases, reducing the relative error of the sub-Ma model by 2–10 times, even at high angles of attack. The mean reconstruction accuracy for the hinge moments is 97.6%, and for the normal forces, it is 94.3%. Therefore, adding relevant terms when the number of samples is small can effectively improve modeling accuracy.

Feature Engineering for a MIL-STD-1553B LSTM Autoencoder Anomaly Detector

The MIL-STD-1553B data bus protocol is used in both civilian and military aircraft to enable communications between subsystems. These interconnected subsystems are responsible for core services such as communications, flow of instrument data and aircraft control. With aircraft modernization, threat vectors are introduced through increased inter-connectivity internal and external to the aircraft. The resulting potential for exploitation introduces a requirement for an intrusion detection capability in order to maintain the integrity, availability and reliability of data transmitted using the MIL-STD-1553B protocol, safety of the aircraft and overall, to achieve mission assurance. Research in recent years has investigated signature, statistical and machine learning based solutions to detect attacks on MIL-STD-1553B buses. Of the different techniques, those based on machine learning have shown extremely good results. The aim of this research is to improve the performance of an existing Long Short-Term Memory Auto-Encoder by refining the feature engineering phase of its pipeline. The improvement in the detector’s overall effectiveness was accomplished through feature engineering focused on feature generation and selection. Five different attack datasets were used as the starting point, consisting of four different denial of service attacks and one data integrity attack. From initial feature extraction of 155 features, two feature generation techniques were employed to create over 38,000 features as a starting point. Using five different MIL-STD-1553B datasets and three feature selection techniques, fifteen different Long Short-Term Memory Auto-Encoder models were created, trained and evaluated using common performance metrics and compared to those of the original anomaly detector. This research demonstrated marked performance improvement achieved by the feature engineering refinements made in comparison to those of the original model. Equally important, this research also showed a significant reduction in the number of features required to achieve this performance gain. In the context of miliary air operations, the ability to improve detection capabilities with less data is important to the technical solutions that contribute to the achievement of cyber mission assurance.

Research on an Ice Tolerance Control Method for Large Aircraft Based on Adaptive Dynamic Inversion

Considering the effect of icing on aircraft control performance, this paper proposes an adaptive dynamic inverse ice tolerance control method based on piecewise constant. A control allocation algorithm is introduced to compensate for the change of control surface performance caused by icing. This method can achieve satisfactory disturbance estimation accuracy under a given sampling time, and thus ensure a closed-loop system error within an acceptable range. The proposed design method is applied to the design of a flight control law for a transport aircraft, aiming to solve the problem of ice-tolerant flight control, reduce the influence of icing conditions on controllability and safe flight of the transport aircraft, and thus improve the flight quality of the transport aircraft. The simulation results are verified under the influence of both standby ice type and failure ice type, and the interference effect on aircraft aerodynamic parameters is further added. The simulation results show that adaptive dynamic inverse control based on piecewise constant can overcome the influence caused by icing and aerodynamic parameter interference, achieve accurate tracking of command, and provide excellent fault tolerance and robustness, which ensures that the transport aircraft can achieve the desired control performance and safe flight capability.

Incremental Nonlinear Dynamics Inversion and Incremental Backstepping: Experimental Attitude Control of a Tail-Sitter UAV

Incremental control strategies such as Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities, which is of particular relevance for tail-sitters as these perform complex, hard to model manoeuvres when transitioning to and from aerodynamic flight. In this research article, a quaternion-based form of IBKS is originally deduced and applied to the stabilization of a tail-sitter in vertical flight, which is then implemented in a flight controller and validated in a Hardware-in-the-Loop simulation, which is also made for the INDI controller. Experimental validation with indoor flight tests of both INDI and IBKS controllers follows, evaluating their performance in stabilizing the tail-sitter prototype in vertical flight. Lastly, the tracking results obtained from the experimental trials are analysed, allowing an objective comparison to be drawn between these controllers, evaluating their respective advantages and limitations. From the successfully conducted flight tests, it was found that both incremental solutions are suited to control a tail-sitter in vertical flight, providing accurate tracking capabilities with smooth actuation, and only requiring the actuation model. Furthermore, it was found that the IBKS is significantly more computationally demanding than the INDI, although having a global proof of stability that is of interest in aircraft control.

Neural network-based adaptive optimal tracking control for hypersonic morphing aircraft with appointed-time prescribed performance

In this paper, an adaptive optimal attitude tracking controller for hypersonic morphing aircraft with appointed-time prescribed performance is presented. A proper error transformation methodology is developed to ensure the performance constraints are met without knowing initial tracking conditions. Subsequently, an adaptive composite control scheme is devised for the transformed system, comprising a feedforward neuro-backstepping controller and a feedback optimal controller. The former is employed to convert the optimal tracking problem into an equivalent optimal regulation problem, while the latter is constructed using adaptive dynamic programming (ADP) with a single critic network to achieve optimality. A novel weight-tuning law for the critic network is introduced, incorporating a stability indicator and the concurrent learning technique. This approach relaxes the underlying restrictive conditions in ADP, improving the robustness and availability of the system. The stability of the closed-loop system is analyzed using the Lyapunov direct method. Finally, the effectiveness and improved performance of the proposed control scheme are validated through numerical simulations.

Adaptive PI Control Based Stability Margin Configuration of Aircraft Control Systems with Unknown System Parameters and Time Delay

Adaptive PI Control Based Stability Margin Configuration of Aircraft Control Systems with Unknown System Parameters and Time Delay

Adaptive dynamic programming base on MMC device of a flexible high-altitude long endurance aircraft

Flexible high-altitude long endurance (HALE) aircraft face challenges such as the delay effect caused by aeroelasticity and low efficiency during high-altitude cruising. This paper addresses a new active control scheme that replaces traditional aerodynamic control surfaces with longitudinal and lateral moving masses and adopts an observer-based adaptive dynamic programming (ADP) control strategy, aiming to solve the attitude control of HALE aircraft with flexible wings. Firstly, considering the account of unsteady aerodynamics, attitude angular velocity, and moving masses, complete dynamic model is established for a flexible aircraft, in order to more accurately describe the state of the HALE aircraft. This model includes two moving masses to replace traditional ailerons and elevators. It is difficult to design attitude control strategies considering the delay effects and unknown dynamic disturbances of HALE aircraft. To this end, the actor-critic structure of the ADP approach is designed to achieve the near-optimal control strategy of the system, which eliminates the need for prior knowledge of model parameters. A fixed time disturbance observer (FTDO) is proposed to estimate the future tracking error information and unknown disturbances to improve the control performance of the attitude. Finally, the stability of the system is proved via the Lyapunov technique and a comprehensive simulation of HALE aircraft is provided. The simulation results show that the proposed control algorithm can enable the aircraft attitude angles to quickly response and maintain stability under gust wind. Compared with a single ADP control strategy, this paper's algorithm has advantages in response speed and error.

SPE-SHAP: Self-paced ensemble with Shapley additive explanation for the analysis of aviation turbulence triggered by wind shear events

Aviation safety is critically challenged by significant turbulence, often triggered by wind shear events, which jeopardize aircraft controllability and may cause structural damage to the fuselage. Current predictive models, primarily based on Pilot Reports (PIREPs), suffer from data imbalance, undermining their reliability and accuracy. This research addresses the need for a robust approach to accurately estimate and classify aviation turbulence events. We propose a novel framework, the Self-Paced Ensemble (SPE), integrated with Shapley Additive Explanation (SHAP) analysis. This framework utilizes tree-based classifiers such as Gradient Boosting Decision Trees (GBDT), Random Forests (RF), Extreme Gradient Boosting (XGBoost), and Extra Trees (ET) to enhance predictive accuracy and reliability. The SPE model, particularly when combined with XGBoost, demonstrated superior performance with a recall of 70.16 %, specificity of 74.75 %, G-Mean of 73.67 %, Matthews correlation coefficient (MCC) of 0.352, and area under the Receiver Operating Characteristic (ROC) curve of 0.726. Comparatively, the SPE model with RF achieved a recall of 70.05 %, specificity of 73.89 %, G-Mean of 72.57 %, MCC of 0.347, and AU-ROC of 0.721. Post-hoc Wilcoxon signed-rank tests further validated these results. SHAP analysis identified wind shear altitude, magnitude, and causes as the most influential factors affecting significant aviation turbulence prediction. The SPE-SHAP framework not only significantly improves the prediction of aviation turbulence but also enhances model transparency by elucidating key contributing factors. These insights can inform updates to aircraft operation protocols and enhance flight training, thereby increasing safety during wind shear events.

Advanced autopilot design with extremum-seeking control for aircraft control

Abstract The aim of this research is to enhance adaptive autopilots for the effective management of aircraft systems, control maintenance, and the rejection of external disturbances. To achieve this objective, we propose the design of an autopilot integrated with the extremum-seeking control (ESC) algorithm. Although autopilots proficiently manage the lateral and longitudinal modes of aircraft control, they lack filtering or adaptive capabilities, thereby exposing the system to significant external threats. To mitigate these risks, the ESC method is employed. This adaptive approach can operate in a disturbance rejection manner by adjusting parameters for unknown inputs and restoring the system to its original controlled response. ESC represents a versatile control method suitable for effective application in simulations or experimental models. Through the incorporation of this method, the pitch attitude hold autopilot, altitude hold autopilot, and yaw autopilot acquire advanced disturbance rejection capabilities with adaptive ESC features. The novelty of the proposed method lies in providing advanced disturbance rejection properties to conventional autopilots, thereby rendering them innovative and superior disturbance rejection controllers. The newly developed autopilots are capable of eliminating severe disturbances from the system response, including ramp, sinusoidal, and step disturbances. The integration of autopilots with ESC offers significant advantages, such as superior disturbance rejection properties for the aircraft unmanned aerial vehicle (UAV) system. The proposed method successfully eliminates severe disturbances, as demonstrated in simulation results, surpassing previous methods in effectiveness. Furthermore, the Autopilot-ESC method enhances aircraft operation even under disturbances, minimizing energy consumption and ensuring stability and control. This novel method reduces operator workload and ensures reliable and efficient autonomous flight capabilities. Additionally, the adaptability of the Autopilot-ESC to changing environmental conditions make it well-suited in aircraft UAVs. This upgraded version of autopilot surpasses other robust controllers, such as Linear Quadratic Gaussian (LQG) regulator and Model Predictive Control (MPC), as it can effectively address ramp, sinusoidal, and step disturbances, which LQG and MPC cannot handle.

Numerical analysis of aerodynamic performance of the Ram Air Turbine in an aircraft

A rotor design of a Ram Air Turbine (RAT) for a commercial aircraft was created taking three sections with different airfoils along the blade; those sections were assessed to evaluate their performance at different critical velocities (41, 81 and 251 m/s) and choose the best profile configuration generating a new proposal to increase the glide ratio by reducing the drag, which is helpful in emergency cases. The Blade Element Momentum (BEM) theory and Computational Fluid Dynamics (CFD) were used to analyze an initial design, then validating these results with the open software QBlade. For the BEM theory a program was created for the design and performance of the RAT adding the Viterna methodology for airfoil analysis. 16 designs were proposed by strategically interchanging wing profiles in different blade sections. These designs were analyzed by CFD, using the complete rotor and the SSTk−ω turbulence model. An optimal geometry was found, presenting a significant drag reduction of 25% generating an increase in the glide ratio and improving aircraft control in addition to maintaining the power generation above the desired values; therefore, it recommends using different airfoils for each section of a RAT's rotor blade.

Controllability Evaluation for VTOL Aircraft in Velocity Envelope: A Distance-Based Metric

This paper introduces an approach for evaluating and quantifying the controllability of vertical takeoff and landing (VTOL) aircraft across various flight states. By employing the controllability theory for linear systems subject to bounded control, this study derives sufficient conditions for the local controllability of the nonlinear VTOL system. These conditions are cohesively integrated with the trimmability condition directly derived from nonlinear dynamics, establishing a comprehensive criterion that facilitates the assessment of both trimmability and controllability of VTOL aircraft. This unified criterion elucidates the relation between desired and achievable specific forces and moments with clear implications for flight mechanics. Building upon this criterion, a distance-based metric is proposed to quantify the controllability, with an optimization-based algorithm developed for its calculation. Focusing on an exemplary lift plus cruise VTOL aircraft, this study investigates controllability variations within the aircraft’s velocity envelope and assesses the impact of rotor failures on controllability. These applications demonstrate the proposed method’s effectiveness in quantifying the controllability of VTOL aircraft in various flight conditions.

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.

Trajectory Tracking Control of Variable Sweep Aircraft Based on Reinforcement Learning.

An incremental deep deterministic policy gradient (IDDPG) algorithm is devised for the trajectory tracking control of a four-wing variable sweep (FWVS) aircraft with uncertainty. The IDDPG algorithm employs the line-of-sight (LOS) method for path tracking, formulates a reward function based on position and attitude errors, and integrates long short-term memory (LSTM) units into IDDPG algorithm to enhance its adaptability to environmental changes during flight. Finally, environmental disturbance factors are introduced in simulation to validate the designed controller's ability to track climbing trajectories of morphing aircraft in the presence of uncertainty.

Математическая модель сопутствующей деятельности пилота и ее применение для объективной оценки его состояния и профессиональной подготовки

<p>A new approach to analysis and diagnostics of the pilots’ activities is presented, which makes it possible to compare both different options of the aircraft cockpit information and control field and the professional training of flight personnel from the viewpoint of application effectiveness. A mathematical model of the associated activities in use represents the pilot work via the matrix of transition probabilities, where transitions occur between the operations he performs. The approach under consideration is based on the convolution of the applied Markovian processes, which are created using the pilot activity protocols, into the quantum representations, making it possible to reveal the structure of these processes by the quantum spectral analysis. Application of the quantum filtering makes it possible to obtain quantitative diagnostic assessments of the pilot activity. Analysis of the experimental results for pilots of various training levels is given to demonstrate the possibility for assessing their professional skills as well as the prospects for using the proposed methods.</p>

Full-Envelope Flight Control for Compound Vertical Takeoff and Landing Aircraft

This paper presents a flight control design for compound vertical takeoff and landing (VTOL) vehicles. With their multitude of degrees of controllability as well as the significant variations in their flight characteristics, VTOL vehicles present challenges when it comes to designing their flight control system, especially for the transition phase where the vehicle transitions between near-hovering and high-speed wing-borne flights. This work extends previous research on the design of unified and generic control laws that can be applied to a broad class of vehicles such as hovering vehicles and fixed-wing aircraft. This paper exploits this unifying property and presents an extension for the case of compound VTOL vehicles. The proposed control approach consists of nonlinear geometric control laws that are continuously applicable over the entire flight envelope, excluding the use of switching policies between different control algorithms. A transition strategy consisting of a sequence of high-level set points is associated with the flight control laws; it is defined with respect to flight envelope limitations and is applied in this work to a commercially available compound unmanned aerial vehicle. The control algorithms are implemented on a Pixhawk controller; they are evaluated via hardware-in-the-loop simulations and finally validated in a flight experiment.