Aircraft Dynamics Research Articles

Physics-Based Aircraft Dynamics Identification Using Genetic Algorithms

This research introduces a physics-based identification technique utilizing genetic algorithms. The primary objective is to derive a parametric matrix, denoted as A, describing the time-invariant linear model governing the longitudinal dynamics of an aircraft. This is achieved by proposing a fitness function based on the properties of the transition matrix and taking advantage of some of the capabilities of the genetic algorithm, mainly those of restricting the search ranges of the unknowns. In this case, such unknowns are related to the type of aircraft and flight conditions that are considered during the identification process. The proposed identification method is validated with a reliable nonlinear model that can be found in the literature, as well as with the calculation of the trim condition and linearization generally used in aircraft dynamics. In summary, this study suggests that the genetic algorithm provided with the adequate fitness function could be an appealing alternative for aircraft model identification, even when limited data are available. Furthermore, in some cases, linearization using a genetic algorithm can be more efficient than classical methods.

Exploration of optimal control based surrogate modeling as a basis for fuel efficient 4D aircraft routing on graphs

AbstractFuel efficient coordination of aircraft operations in the Terminal Maneuvering Area of large airports can contribute to the reduction of the environmental impact of air traffic. To exploit the full potential of the air traffic system, coordinated routing in the Terminal Maneuvering Area, runway assignment and scheduling need to be optimized considering detailed models of the aircraft dynamics and performance. Due to the inhomogeneous nature and level of detail of these combined discrete and continuous decision problems, the optimization of the overall operations poses significant challenges. As part of an integrated approach to the solution of this hybrid problem, this work explores the generation of surrogate models for the fuel consumption of individual aircraft using optimal control methods to exploit the physical capability of the aircraft within an operationally permissible envelope. The surrogate models approximate the predicted fuel consumption of a given point-mass aircraft model on short generic trajectory segments. The trade-off between flight duration and fuel consumption on such segments is analyzed, focusing on the influences of initial aircraft mass, altitude, distance, mean climb angle, along-track wind velocity and linear wind shear. An extensive description of the optimal control-based data generation and surrogate modeling methodology is followed by a discussion of the effects of parameter variation. Based on an illustrative case study, the applicability of the approach is critically analyzed.

Quick trim modeling for tiltrotor aircraft in conversion mode

The conversion mode in tiltrotor aircraft is of paramount importance and complexity, necessitating the trim results to ensure stable tilting using the trim model. Quick trim modeling is conducted for tiltrotor aircraft in conversion mode, focusing on the aerodynamics of the rotor using modified lift line theory. Furthermore, we develop the nonlinear flight dynamics of tilt-rotor aircraft. Based on this aircraft model, a double-layer cycle iterations method is employed to establish an efficient and rapid trim model for the tiltrotor in conversion mode at any tilt angle or during any aerial maneuver. Using Boeing Model 222 as an example, trim results for conversion mode are calculated and compared with reference data to validate the effectiveness and precision of our model.

Dynamics simulation model for the analysis of aircraft movement characteristics on an aircraft carrier deck

Aircraft on an aircraft carrier deck are taxied or towed using a tractor. As these vehicles move within a limited area and are affected by the aircraft carrier motion, the possibility of aircraft movement in the entire space must be confirmed. The potential aircraft movements can be determined using simulations, wherein the movement characteristics of the aircraft must be analyzed by considering the movement of the carrier. Therefore, an aircraft dynamics simulation model considering the six-degrees-of-freedom movement of the platform is presented in this study to analyze the aircraft movement characteristics on the deck. The proposed model was verified using various reference data and models, and the simulation results of the multi-body dynamics analysis program DAFUL were employed to estimate the tire stiffness coefficient according to the slope. The proposed model facilitated the analysis of the movement characteristics of the aircraft by implementing driving simulations for various platform movements.

Comprehensive Analysis of Aircraft Dynamics Stability with SCSim: Integration and Assessment

This research presents a comprehensive analysis of the dynamic stability of aircraft using modules of the software named SCSim (Stability and Control Simulation Tool), which is dedicated to the analysis of aircraft stability and control. The stability of an aircraft can be examined in two directions: longitudinal and lateral. The ability to determine an aircraft's limits and handling qualities depends on its stability. This study report demonstrates a complete dynamic stability analysis using SCSim with aerodynamic input data from the commercial software Advanced Aircraft Analysis (AAA). SCSim is implemented within a common framework in MATLAB, adapted from a MATHCAD script, providing an easier way to enter user-defined input data, and introducing a set of new features. The study is divided into three main parts, each based on an analysis of stability. First, static stability is examined to understand how the system behaves when it is in equilibrium. Then, dynamic stability is assessed to understand how the system reacts to perturbations and disturbances. Finally, handling qualities systematically assess the dynamic modes of the aircraft's behavior and establish the levels of handling qualities. In this paper, a generic model of a propeller-driven aircraft is used for the study due to the availability of flight parameters, geometric, and aerodynamic data. The obtained results demonstrate the capabilities of the Stability and Control Simulation Tool (SCSim) in designing and analysing an aircraft's stability under various flight conditions and configurations, with validation using AAA.

Enhanced Unsteady Vortex Lattice Aerodynamics for Nonlinear Flexible Aircraft Dynamic Simulation

Several modeling extensions and numerical improvements to the unsteady vortex-lattice method are discussed for the simulation of very flexible aircraft dynamics. In particular, fuselage aerodynamics are included by means of linear source panels, polar corrections are incorporated on the aerodynamics under potentially large deformations, and a new wake discretization scheme is derived to accelerate the computations. The theory behind each approach is detailed and successfully verified on representative test cases. The resulting modeling environment is then exemplified in a study of the flight dynamics of a flexible aircraft demonstrator model. Results indicate that, for large wing deformations, a noticeable effect of fuselage aerodynamic interference appears on the wing aeroelastic behavior. The polar corrections improve the drag estimations and allow capturing lift decrements due to stall onset at high induced angles of attack, which then affects the gust loads. The wake discretization scheme enables a reduction of the computational time for dynamic simulations on a full aircraft model by about 20% while keeping the arising error negligibly small.

Finite-time SDRE control of F16 aircraft dynamics

Finite-time SDRE control of F16 aircraft dynamics

Full envelope nonlinear flight controller design for a novel electric VTOL (eVTOL) air taxi

AbstractOn-demand urban air transportation gains popularity in recent years with the introduction of the electric VTOL (eVTOL) aircraft concept. There is an emerging interest in short/medium range eVTOL air taxi considering the critical advantages of electric propulsion (i.e. low noise and carbon emission). Using several electric propulsion systems (distributed electric propulsion (DEP)) has further advantages such as improved redundancy. However, flight controller design becomes more challenging due to highly over-actuated and coupled dynamics. This study defines and resolves flight control problems of a novel DEP eVTOL air taxi. The aircraft has a fixed-wing surface to have aerodynamically efficient cruise flight, and uses only tilting electric propulsion units to achieve full envelope flight control via pure thrust vector control. The aircraft does not have conventional control surfaces such as aileron, rudder or elevator. Using pure thrust vector control has some design benefits, but the control problem becomes more challenging due to the over-actuated and highly coupled dynamics (especially in transition flight). A preliminary flight dynamics model is obtained considering the dominant effects at hover and high-speed forward flight. Hover and forward flight models are blended to simulate the transition dynamics. Two central challenges regarding the flight control are significant nonlinearities in aircraft dynamics during the transition and proper allocation of the thrust vector control specifically in limited control authority (actuator saturation). The former challenge is resolved via designing a sensor-based incremental nonlinear dynamic inversion (INDI) controller to have a single/unified controller covering the wide flight envelope. For the latter one, an optimisation-based control allocation (CA) approach is integrated into the INDI controller. CA requires special attention due to the pure thrust vector control’s highly coupled dynamics. The controller shows satisfactory performance and disturbance rejection characteristics. Moreover, the CA plays a vital role in guaranteeing stable flight in case of severe actuator saturation.

An Enhanced Incremental Nonlinear Dynamic Inversion Control Strategy for Advanced Unmanned Aircraft Systems

A cascade control architecture was proposed for the control of advanced unmanned aerial vehicles targeted for operation inside confined hazardous spaces. The aircraft of interest is a highly maneuverable system presenting highly coupled dynamics, enabling it to perform unique flight maneuvers that no other aircraft can. To deal with the complexities inherent to such an aircraft, a novel nonlinear control architecture was proposed. Two outer loop NDI controllers and an inner loop INDI controller were employed for position/velocity and attitude/rotation rate control, respectively. These controllers assist each other, enabling them to decouple the aircraft dynamics while coping with complex external disturbances. The obtained results demonstrate an effective control of the targeted aircraft system to accurately track complex flight maneuvers.

Research on Scenario Modeling for V-Tail Fixed-Wing UAV Dynamic Obstacle Avoidance

With the advantages of long-range flight and high payload capacity, large fixed-wing UAVs are often used in anti-terrorism missions, disaster surveillance, and emergency supply delivery. In the existing research, there is little research on the 3D model design of the V-tail fixed-wing UAV and 3D flight environment modeling. The study focuses on designing a comprehensive simulation environment using Gazebo and ROS, referencing existing large fixed-wing UAVs, to design a V-tail aircraft, incorporating realistic aircraft dynamics, aerodynamics, and flight controls. Additionally, we present a simulation environment modeling approach tailored for obstacle avoidance in no-fly zones, and have created a 3D flight environment in Gazebo, generating a large-scale terrain map based on the original grayscale heightmap. This terrain map is used to simulate potential mountainous terrain threats that a fixed-wing UAV might encounter during mission execution. We have also introduced wind disturbances and other specific no-fly zones. We integrated the V-tail fixed-wing aircraft model into the 3D flight environment in Gazebo and designed PID controllers to stabilize the aircraft’s flight attitude.

Aircraft parameter estimation using a stacked long short-term memory network and Levenberg-Marquardt method

To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data, this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory (LSTM) network model and the Levenberg-Marquardt (LM) method. The stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input–output data of the aircraft system without requiring explicit postulation of the dynamics. The LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic parameters. The proposed method is applied by using the real flight data, generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle (UAV). The investigation reveals that for the two different flight data, the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters (i.e., the initial weights, initial biases, number of hidden cells, time-steps, learning rate, and number of training iterations). Besides, the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.

Spin Aerodynamic Modeling for a Fixed-Wing Aircraft Using Flight Data

Novel techniques are used to identify a nonlinear, quasi-steady, coupled, spin aerodynamic model for a fixed-wing aircraft from flight-test data. Orthogonal phase-optimized multisine inputs are used as excitation signals while collecting spinning flight data. A novel vector decomposition of explanatory variables leads to an elegant model structure for spin flight data analysis. Results show good agreement between model predictions and validation flight data. This effort is motivated by interest in developing a flight termination system for a fixed-wing unmanned aircraft that controls a descending spiral trajectory flight path toward a designated impact area. While investigating the feasibility of a robust control method to guide the spinning trajectory, it was helpful to compare a level flight dynamic model with one of the aircraft dynamics and control authority in the neighborhood of a stable, oscillatory spin. In this paper, a nominal flight aerodynamic model is developed and compared to the stall spin model and the spin model outperforms the nominal model for spinning flight.

A computationally efficient Kalman filter-based RAIM algorithm for aircraft navigation with GPS and NavIC

Integrity monitoring with a Kalman filter (KF) has recently attracted significant attention. In this paper, a computationally efficient architecture of a KF-based receiver autonomous integrity monitoring (RAIM) algorithm is discussed for aviation applications to ensure reliable operations of Global Navigation Satellite Systems (GNSS). It is built on the Schmidt KF navigation processor to model time-correlated measurement errors. Reasons for important design choices of the algorithm are clarified. Different strategies are adopted to efficiently include the contributions of past KF measurements in fault detection as well as protection level (PL) calculations. Module-wise most significant numerical complexity is also analyzed in detail. The algorithm performance is studied with simulated Global Positioning System (GPS) and Navigation with Indian Constellation (NavIC) signals for a number of scenarios. They comprise different configurations related to the number of satellites, geometry, total duration, and aircraft dynamics. Fault detection performance of presented KF RAIM is shown to be superior to another innovation-based test with a moving time window. It is demonstrated that KF RAIM running on a single-core virtual machine can complete processing within a small fraction of each time interval. The performance is also analyzed by restricting CPU usage. The processing time of GPS-NavIC KF RAIM at every interval is shown to be consistently less than that of standalone GPS in all scenarios. Therefore, dual constellations not only result in lower PLs, but also require shorter execution times. An explanation for faster execution times with dual GNSS is provided using the numerical complexity of different modules.

Pilot Command Implementation in Aircrafts: A New Approach Based on Dynamic Inversion

A new approach based on dynamic inversion is proposed in this paper for implementing pilot commands in an aircrafts. The command inputs from the pilot are assumed to be (i) the normal acceleration and forward velocity commands in the longitudinal mode and (ii) roll rate, height and forward velocity commands in the lateral mode. A major difference here is that the second derivatives of the velocities along body y and z directions are assumed to be zero, as opposed to the first derivatives (which is used in many published literature). The new approach leads to a significant reduction of tuning parameters in the control design process, which is a major advantage. Detailed derivations of the modified approach are presented with respect to the generic aircraft dynamics model available in [16]. Extensive Six-DOF simulation studies show that, besides the above advantage, the new approach leads to two other additional advantages; namely reduced oscillatory response and reduced control magnitude. In a comparison study with an existing method using the Six-DOF model for Boeing 747 (with the numerical data available in [16]), numerical results clearly show the improved performance of this new approach. Furthermore, in lateral mode a technique for obtaining a corresponding roll rate command from the desired bank angle command is also implemented. Comparison results show improved performance of the new approach with this modification as well.

Longitudinal Aerodynamic Parameter Estimation Using Neural Network and Gauss-Newton Method

A new parameter estimation method based upon Feed Forward Neural Network is proposed. The proposed method utilizes the universal mapping capability of Feed Forward Neural Network to develop flight dynamic model of aircraft. Gauss-Newton method is used to obtain values of aerodynamic parameters by minimizing a chosen error cost function. The method has then been validated using flight data pertaining to longitudinal dynamics of aircraft. Proof of match approach has been followed to verify the estimated model by the proposed method. The results obtained using the proposed method have also been compared with those obtained using wind tunnel tests, and Filter Error method. Unlike, most of the conventional methods, the proposed method does not require a priori description of the model. It also bypasses the requirement of solving the equations of motion. This feature may have special significance in handling flight data of an unstable aircraft.

Unstable Aircraft Parameter Estimation Using Neural Partial Differentiation

An approach based on neural partial differentiation is suggested, to overcome the numerical problems faced by classical methods, for the parameter estimation of an aerodynamically unstable aircraft. Theoretical analysis of the neural modeling, the parameter estimation process, and the nature of the estimates pertaining to unstable aircraft dynamics using the neural partial differential method, are discussed. Equation for the relative standard deviation, which is equivalent to the Cramer-Rao bound in the method like output error approach, is derived using the neural partial differential method and verified through numerical simulation. The aerodynamic derivatives are derived for the simulated and real longitudinal flight data of an unstable aircraft, and the estimates obtained using the neural partial differentiation are compared with the classical methods such as the equation error and the output error methods. The parameter estimates from the simulated noisy data are also presented to assess and support the theoretical developments presented in this paper. The theoretical analysis and the results presented in this paper make the neural partial differential approach more reliable and widely applicable.

Neural Partial Differentiation for Parameter Estimation of Flexible Aircraft Dynamics

Although the parameter estimation methodologies had been successfully applied for the rigid aircraft dynamics, the aircraft with high degree of flexibility poses challenges to determine the appropriate aeroelastic models for inclusion in the parameter estimation algorithms. Application of the neural networks for the aerodynamic modeling and parameter estimation of an aeroelastic aircraft (or flexible aircraft) is addressed in this paper. A neural network with the scaled conjugate gradient learning algorithm is used for modeling lift and pitching moment coefficients. The partial differentiation of the neural network output is carried out for the estimation of equivalent parameters of an aeroelastic aircraft. It is demonstrated that a reasonable model and estimates of the equivalent parameters for the aeroelastic aircraft are possible with the neural partial differential method by using the measured motion and control variables, without any need for postulating the coupled equations of motion or initialization of the parameters to be estimated. The proposed approach reduces the large number of parameters for aeroelastic aircraft dynamics into fewer equivalent parameters, and this methodology does not require the measurements of the elastic deflections or their derivatives. The neural partial differential method is applied to the simulated flight data of an aeroelastic aircraft for the longitudinal dynamics. The performance of the neural partial differential approach is compared with the estimates obtained from the other methods like classical estimation methods, analytical computation, and values given in the literature for rigid body modeling. The performance is also validated by comparing the measured lift force and pitching moment coefficients with the neural predicted and neural reconstructed coefficients using the estimates obtained through the neural partial differential approach.

Nonlinear system identification of a UAV model with distributed aerodynamics and flexible structure

This paper presents the nonlinear system identification of a slightly flexible 25 kg fixed-wing UAV in the time-domain using a computationally efficient distributed aerodynamics model and a linear structural dynamics representation. The equations of motion are formed by making use of the free vibration modes of the structure and the mean axes formulation. The structural modes and mode shapes are determined from ground vibration tests. The distributed aerodynamics, accounting for elastic deformations, are modeled using a quasi-steady stability and control derivative approach and by applying strip theory. Initial distributions for the derivatives are obtained from vortex-lattice-method calculations. For matching the model response to the measured response, parameters for scaling the initial derivative distributions are introduced. The flexible model is subsequently identified based on flight test data using the output error method in the time-domain and maximum-likelihood estimation. A good overall identification result is achieved with a close match of the fast aircraft dynamics. Finally, an evaluation is given on the suitability of the identified model for real-time simulation, loads’ estimation, and active load control law design.

Advances and Modern Applications of Frequency-Domain Aircraft and Rotorcraft System Identification

This paper provides an overview of advances and applications of aircraft and rotorcraft flight dynamics system identification at the U.S. Army Combat Capabilities Development Command Aviation & Missile Center over the past 20 years. An overarching topic is how frequency-domain system identification has evolved to aid modeling work of modern aircraft and rotorcraft configurations. The paper starts with a brief overview of the frequency-response method for system identification. Subsequently, the paper highlights and demonstrates several new advances using flight-test data from a conventional helicopter, fixed-wing aircraft, advanced coaxial compound rotorcraft, and a small multirotor unmanned aerial vehicle. The first advancement is the use of identification results to improve simulation model fidelity. The next advancement is the Joint Input-Output Method for identification of aircraft with highly correlated inputs. Next, the paper discusses the advancement of flexible constraints, which provide the ability to directly determine physical parameters from flight-test data. The paper then discusses a methodology to identify lower-order linearized dynamic inflow models from higher-order free wake aerodynamic models. Finally, the paper discusses model stitching, which is the technique of combining or stitching together individual linear models and trim data for discrete flight conditions to produce a continuous, full flight-envelope real-time stitched simulation model.

Neuroadaptive Dynamic Surface Asymptotic Tracking Control of a VTOL Aircraft with Unknown Dynamics and External Disturbances

This work studies the asymptotic tracking control problem of a vertical take-off and landing (VTOL) aircraft with unknown dynamics and external disturbances. The unknown nonlinear dynamics of the VTOL aircraft are approximated via the introduction of radial basis function neural networks. Then, the weight update laws are designed. Furthermore, the parameter update control laws are presented to deal with the errors generated during the approximation process and the external disturbances of the aircraft system. Moreover, first-order filters are introduced to avoid repeated differentiation of the designed virtual control laws, thereby effectively eliminating the “complexity explosion” problem caused by traditional backstepping control. Based on the application of the neural network control method, dynamic surface control technique, weight update laws and parameter update control laws, neuroadaptive dynamic surface control laws for the aircraft system are finally proposed. Theoretical analysis shows that the proposed control law can ensure that the aircraft system asymptotically tracks the reference trajectories and the tracking errors can converge to a small neighborhood of zero by choosing the appropriate designed parameters. Finally, simulation examples are provided to verify the effectiveness of proposed control laws.