Aerospace Systems最新文献

Long-distance space systems generate enormous amounts of bigdata. These bigdata can be used to generate intelligent that can help us better understand the behavior of space systems. There is currently no such tool for precisely understanding and predicting the behavior of aerospace systems. In this study, three different aerospace systems are analyzed to build the respective artificial intelligence (AI) models to understand and predict their space behavior using the deep learning (DL) ecosystem. We studied the pulsed plasma thruster (PPT), an electric space propulsion system; the ARTEMIS-P1 spacecraft sensor array; and the UAV battery system. Three sets of comparative analyses are carried out to assess the model accuracy. A number of tests are utilized to assess and predict the exact physical behavior. The comparison and test results show that DL-based artificial models are capable enough (> 99%) to mimic the exact system behaviors. This DL-based approach provides a novel means of understanding and predicting the real behavior of the aerospace systems.

Micro-aerial vehicles (MAVs) find it extremely difficult to navigate in GNSS-denied indoor staircase environments with obstructed Global navigation satellite system (GNSS) signals. To avoid hitting both static and moving obstacles, MAV must estimate its position and heading in the staircase indoor scenes. In order to detect vanishing points and estimate heading for MAV navigation in a staircase environment, five different input colour space image frames—namely RGB image into a grayscale image and RGB image into hyper-opponent colour space—O1, O2, O3, and Sobel R channel image frames—have been used in this work. To determine the position and direction of the MAV, the Hough transform technique and K-means clustering algorithm have been incorporated for line and vanishing point recognition in the staircase image frames. The position of the vanishing point detected in the staircase image frames indicates the position of the MAV (Centre, left or right) in the staircase. In addition, to compute the heading of MAV, the Euclidean distance between the staircase picture centre, mid-pixel coordinates at the image’s last row, and the detected vanishing point pixel coordinates in the succeeding staircase image frames are used. The position and heading measurement can be utilised to send the MAV a suitable control signal and align it at the centre of the staircase when it deviates from the centre. The integrated Hough transform technique and K-means clustering-based vanishing point detection are suitable for real-time MAV heading measurement using the O2 channel staircase image frames for indoor MAVs with a high accuracy of ± 0.15° when compared to the state-of-the-art grid-based vanishing point detection method heading accuracy of ± 1.5°.

This paper proposes a finite-time stable chattering-free output feedback control method for rigid satellites equipped with single gimbal control moment gyro (SGCMG) actuators, considering dynamic uncertainties and external disturbances. The dynamics of a rigid satellite are first represented using the modified Rodrigues parameter (MRP) explanation, and then transformed into Lagrangian state space affine form. Because of cost or technical restrictions, angular velocity data are not always accessible for practical application. So angular velocity is considered to be unmeasurable. In order to avoid increasing mathematical calculations and designing separate observers to estimate external disturbances and system states with finite time convergence, a fast third-order sliding mode state observer has been used to simultaneously estimate disturbances and system states. The main part of the proposed controller is also composed of the fast non-singular terminal sliding mode method, which is a combination of linear sliding mode and terminal sliding mode and guarantees finite-time stability and elimination of chattering phenomenon. For the computation of inverse of Jacobian matrix, off-diagonal singularity robust steering algorithm has been used that capable of escaping any kind of singularities. The stability of the proposed method and the simulation results of the proposed method have been presented and compared with the results of the methods available in the literature, which shows the efficiency of the method proposed.

The electrical actuator is usually used in the navigation and control system of the hypersonic aircraft, and it can be described by a multi-body dynamical system, which contains brushless motor, gear pairs, ball screw, folk, rudder, etc. For such a complex multi-body system, it may contain clearance between the mating components, such as the gear pairs, the nut of the ball screw and the folk. Additionally, the discontinuous friction force is introduced due to the friction sheet between the folk and the rudder shaft. Since the working temperature of the electrical actuator for the hypersonic aircraft can be extremely high and time-varying, the stiffness, clearance and friction coefficient will also change during the maneuvering flight of the hypersonic aircraft. In this paper, the ordinary differential equations of each subsystem of the electrical actuation system for the hypersonic aircraft will be developed. The continuous and discontinuous interaction forces between the mating components will be derived. The temperature effects will be considered such that the stiffness, clearance and the friction coefficient of such an actuation system are in the function of the working temperature. The dynamic responses of such an electrical actuation system for different working temperatures will be compared based on the numerical simulations, which shows the evidence that the temperature can reduce the transmission ratio of such a system, as well as affecting the system flutter behavior, through changing the contact position of the adjacent meshing components.

The development of flight software for Unmanned Aerial Systems (UAS) is challenging due to the absence of an established development process defined by aerospace certification authorities. This research paper outlines our methods and tools for analyzing flight-critical UAS control software on the target hardware. We present our toolchain and methodology for evaluating the flight control computer stack, runtime memory, and timing characteristics. Additionally, we compare the performance of the flight control computer under various hardware and cache settings to justify, which hardware features should be enabled. The tools and processes employed in this research are deployable to any other development environment and are not restricted to the specific target hardware used in this paper.

This article discusses the challenge of defining the geometry parameters for minimum mass stiffened aircraft panels made of composite materials. The thickness and size of the panel elements are unknown variables, and the optimal design is based on the condition of equal buckling. To solve this problem, the authors reduce the optimal design problem to the investigation of the weight function with multiple variables using analytical methods and refined buckling theory restrictions. The article introduces novel mathematical relationships for investigating the buckling of structurally anisotropic composite panels. The model couples bending with a plane stress state, resulting in a boundary value problem that involves solving an eighth-order partial differential equation within a rectangular field. To facilitate this, a software package was developed using the MATLAB operating environment. A set of computer programs was created to conduct multi-criteria optimization of the optimal design of structurally anisotropic aircraft composite panels. The study also examines the impact of design parameters on the critical buckling forces for both bending and torsion modes. The results of a new implementation of an optimal size-weight project for carbon-epoxy skin are given. A project with restrictions on the refined buckling theory for structurally anisotropic aircraft panels made of composite materials has been manipulated in terms of plies thicknesses. Optimal solutions are obtained.

The electrical power subsystem (EPS) is one of the most critical subsystems in a spacecraft (SC). It provides the power needed for SC loads. Any failure in the EPS leads to SC mission failure. However, power budget calculation is necessary for the analysis of the energy flow of the SC subsystems for in-orbit nominal operation and to ensure the adequacy of solar array (SA) power and storage battery capacity. The average power generated by SA of a SC should be carefully calculated to accurately estimate the energy budget process. Nevertheless, SC operational scenarios should be designed and then justified by the power budget calculation. The investigation of power capability is to satisfy the mission requirements for all nominal operating modes of the SC. The solar illumination and orbit shadow period, as well as EPS parameters including SA output power, bus voltage, load profile, and storage battery capacity graph during in-orbit nominal operation, are all taken into consideration. In this paper, a mission profile with the worst-case scenario (WCS) for EPS of a Low-earth orbit (LEO) Cube-Sat is demonstrated. Moreover, a novel energy management strategy is developed using artificial intelligence to justify the power budget calculation of SC EPS.

Nonlinear time-varying system, such as a spacecraft formation flying system with chief spacecraft in elliptical orbit and under the effect of perturbation forces, is difficult to analyze, design, and control based on the presence of time-varying parameters. The proper functioning of aerospace systems and their ability to be able to achieve the designed mission objectives depend largely on proper understanding of their nonlinear time-varying nature, dynamics, and ability to keep them in the required mission operation configurations through high-fidelity optimal control strategy. This paper presents nonlinear dynamics and optimal control of (J_2) perturbed spacecraft formation flying. Via Euler–Lagrange approach, the nonlinear (J_2) perturbed motion dynamics was approximated into a time-varying nonlinear form, having periodic coefficients and time-varying parameters, suitable for designing fuel efficient control strategies, spacecraft formation flying, relative motion, and rendezvous mission analysis. Through the application of State-Dependent Riccati Equation (SDRE) approach, the approximated model was converted into a non-unique, pseudo-linear state-dependent coefficient (SDC) form. The numerical simulations confirmed that the SDRE controllers, developed using SDC parameterized systems, are maximally robust and able to return the system to the desired radial, along-track, and cross-track positions.