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A new fault detection scheme for aircraft Inertial Measurement Unit (IMU) sensors is developed in this paper. This scheme adopts a deep neural network with a CNN-LSTM-fusion architecture (CNN: convolution neural network; LSTM: long short-term memory). The fault detection network (FDN) developed in this paper is irrelative to aircraft model or flight condition. Flight data is reformed into a 2D format for FDN input and is mapped via the net to fault cases directly. We simulate different aircrafts with various flight conditions and separate them into training and testing sets. Part of the aircrafts and flight conditions appears only in the testing set to validate robustness and scalability of the FDN. Different architectures of FDN are studied, and an optimized architecture is obtained via ablation studies. An average detecting accuracy of 94.5% on 20 different cases is achieved.

Small satellites have gradually become an important mean of space scientific exploration. The Tsinghua University developed a spherical small satellite, Q-SAT, which is aimed at detecting the Earth gravity and atmosphere parameters. In the current paper, thermal control for Q-SAT is discussed. For heat exchange between the satellite and the environment, radiation plays the main part. Different from traditional cuboid satellites, the current spherical satellite has no individual heat input and output plane which brings challenges to the thermal design of the satellite. In addition, the cost of small satellites is required to be as low as possible. A passive thermal control solution based on integrated spherical structure is employed on the Q-SAT. The combination of two integrated hemispheres is designed to facilitate the heat conduction. Different materials are utilized to control the heat transfer path. Firstly, a set of numerical simulations demonstrate that the current design can be well adapted to complex flight environment. Next, the thermal design is verified by thermal tests. As the traditional heat radiation lamps cannot meet the test requirements of the spherical satellite, an external heat flow test method which is based on distributed heaters is proposed. Results from numerical simulations agree well with the experimental test results. Both results show that the thermal system can guarantee the functions of the satellite. Q-SAT was successfully launched into orbit on August 6, 2020. The telemetry data from Q-SAT verified the effectiveness of the satellite thermal system. The thermal design and test method proposed in present paper can potentially be adopted to other small scientific satellites as well.

In this paper, the typical fault estimation and dynamic analysis are presented for a leader-follower unmanned aerial vehicle (UAV) formation system with external disturbances. Firstly, a dynamic model with proportional navigation guidance (PNG) control of the UAV formation is built. Then, an intermediate observer design method is adopted to estimate the system states and faults simultaneously. Based on the graph theory, the topology relationship between each node in the UAV formation has been also analyzed. The estimator and the system error have been created. Moreover, the typical faults, including the components failure, airframe damage, communication failure, formation collision, and environmental impact, are also discussed for the UAV system. Based on the fault-tolerant strategy, five familiar fault models are proposed from the perspectives of fault estimation, dynamical disturbances, and formation cooperative control. With an analysis of the results of states and faults estimation, the actuator faults can be estimated precisely with component failure and wind disturbances. Furthermore, the basic dynamic characteristics of the UAV formation are discussed. Besides, a comparison of two cases related to the wind disturbance has been accomplished to verify the performance of the fault estimator and controller. The results illustrate the credibility and applicability of the fault estimation and dynamic control strategies for the UAV system which are proposed in this paper. Finally, an extension about the UAV formation prognostic health management system is expounded from the point of view of the fault-tolerant control, dynamic modeling, and multifault estimation.

This paper investigates the application of particle swarm optimization (PSO) algorithm to plan joint trajectories of the space modular reconfigurable satellite (SMRS). SMRS changes its configuration by joint motions to complete various space missions; its movement stability is affected by joints motions because of the dynamic coupling effect in space. To improve the movement stability in reconfiguration progress, this paper establishes the optimization object equation to characterize the movement stability of SMRS in its reconfiguration process. The velocity-level and position-level kinematic models based on the proposed virtual joint coordinate system of SMRS are derived. The virtual joint coordinate system solves the problem of asymmetric joint coordinate system resulted by the asymmetric joint arrangement of SMRS. The six-order and seven-order polynomial curves are chosen to parameterize the joint trajectories and ensure the continuous position, velocity, and acceleration of joint motions. Finally, PSO algorithm is used to optimize the trajectory parameters in two cases. Consistent optimization results in terms of the six-order and seven-order polynomial in both cases prove the PSO algorithm can be effectively used for joint trajectory planning of SMRS.

This paper deals with the design of a novel modified supertwisting fast nonlinear sliding mode controller (MSTFNSMC) to stabilize a quadrotor system under time-varying disturbances. The suggested control strategy is based on a modified supertwisting controller with a fast nonlinear sliding surface to improve the tracking performance. The paper suggests a simple optimization tool built-in MATLAB/Simulink to tune the proposed controller parameters. Fast convergence of state variables is established by using a nonlinear sliding surface for rotational and translational subsystems. The modified supertwisting controller is developed to suppress the effect of chattering, reject disturbances, and ensure robustness against external disturbance effect. The stability of the proposed controller (MSTFNSMC) is proved using the Lyapunov theory. The performance of the proposed MSTFNSMC approach is compared with the supertwisting sliding mode controller (STSMC) by numerical simulations to verify its effectiveness.

It is well known that the application of radar is becoming more and more popular with the development of the signal technology progress. This paper lists the current radar signal research, the technical progress achieved, and the existing limitations. According to radar signal respective characteristics, the design and classification of the radar signal are introduced to reflect signal’s differences and advantages. The multidisciplinary processing technology of the radar signal is classified and compared in details referring to adaptive radar signal process, pulse signal management, digital filtering signal mode, and Doppler method. The transmission process of radar signal is summarized, including the transmission steps of radar signal, the factors affecting radar signal transmission, and radar information screening. The design method of radar signal and the corresponding signal characteristics are compared in terms of performance improvement. Radar signal classification method and related influencing factors are also contrasted and narrated. Radar signal processing technology is described in detail including multidisciplinary technology synthesis. Adaptive radar signal process, pulse compression management, and digital filtering Doppler method are very effective technical means, which has its own unique advantages. At last, the future research trends and challenges of technologies of the radar signals are proposed. The conclusions obtained are beneficial to promote the further promotion applications both in theory and practice. The study work of this paper will be useful for choosing more reasonable radar signal processing technology methods.

This paper addresses the disturbance change control problem with an active deformation adjustment mechanism on a 5-meter deployable antenna panel. A fuzzy neural network Q-learning control (FNNQL) strategy is proposed in this paper for the disturbance change to improve the accuracy of the antenna panel. In the proposed method, the error of the model disturbance is reduced by introducing the fuzzy radial basis function (RBF) neural network into Q-learning, and the parameters of the fuzzy RBF neural network were optimized and adjusted by a Q-learning method. This allows the FNNQL controller to have a strong adaptability to deal with the disturbance change. Finally, the proposed method has been adopted in the middle plate of a 5-meter deployable antenna panel, and it was found that the method could successfully adapt the model disturbance change in the antenna panel. Results of the simulation also show that the whole control system meets the required accuracy requirements.

The evasion maneuver problem of hypersonic vehicles differs from those of ballistic missiles and other traditional weapons, showing distinctive properties including expansive maneuver range and weak maneuverability. How to avoid the disadvantage of low available overload and ensure follow-up tasks are the main concerns of the hypersonic penetration. This paper presents a penetration trajectory optimization algorithm for an air-breathing hypersonic vehicle, where the prerequisite penetration condition is analyzed and control costs are chosen as an objective function to minimize the fuel consumption and maneuver range. This paper focuses on how to formulate the complex, highly constrained nonconvex penetration problem to be a sequence of easily solved second-order cone programming through a combination of successive linearization and relaxation techniques. Innovation lies in the raising of the penetration angle and the relaxation technique of nonlinear and nonconvex elements. Various numerical simulations are conducted to verify the validity of penetration condition and to demonstrate that the proposed method is effective and has a good computational performance irrespective of initial guesses.

A tilt-rotor aircraft can switch between two flight configurations (the helicopter configuration and the fixed-wing plane configuration) by tilting its rotors. In the process of rotor tilting, the nacelles which drive the rotors tilt together with the rotors. Because the mass of the nacelles cannot be ignored compared to the mass of the whole aircraft, the tilting of the nacelles is a coupling motion of the body and the nacelles. In order to better character the aircraft dynamics during the nacelle tilting, a multibody model is established in this paper. In this multibody model, Kane’s method is used to build a dynamic model of a tilt-rotor aircraft. The generalized rates are used to describe the movement of the body and the nacelles (with rotors). The generalized active forces and generalized inertial forces of both the body and the nacelles (with rotors) are obtained, respectively, and the first-order differential equations of the generalized rates are obtained. The longitudinal trim of the XV-15 aircraft is calculated according to the single-body model and our multibody model, in this paper, and the results verify the correctness of the multibody model. In the process of nacelle inclination angle command tracking, the multibody model can provide more information about the disturbance torque of the nacelle than the single-body model, and model inversion control based on the proposed multibody model can obtain a better tracking result than a PID control method only using nacelle angle feedback information.

The active defense scenario in which the attacker evades from the defender and pursues the target is investigated. In this scenario, the target evades from the attacker, and the defender intercepts the attacker by using the optimal strategies. The evasion and the pursuit boundaries are investigated for the attacker when the three players use the one-to-one optimal guidance laws, which are derived based on differential game theory. It is difficult for the attacker to accomplish the task by using the one-to-one optimal guidance law; thus, a new guidance law is derived. Unlike other papers, in this paper, the accelerations of the target and the defender are unknown to the attacker. The new strategy is derived by linearizing the model along the initial line of sight, and it is obtained based on the open-loop solution form as the closed-loop problem is hard to solve. The results of the guidance performance for the derived guidance law are presented by numerical simulations, and it shows that the attacker can evade the defender and intercept the target successfully by using the proposed strategy.

In this paper, we consider the fault-tolerant control problem for aerial vehicles with redundant actuators. The redundant actuator brings difficulty in fault identification and isolation. Active fault-tolerant control is adopted in this paper as it can detect actuator fault. The entire proposed fault-tolerant control algorithm contains a baseline controller, the fault detection and isolation scheme, and the controller reconstruction module. A robust parameter identification method is designed to identify the torque and thrust generated by the actuators. The feasibility of isolating the fault for the redundant actuators is analyzed through mathematical proof. Through the analysis, the practical fault isolation algorithm is also proposed. Two typical aerial vehicles with redundant actuators, an eight-rotor aircraft and a hexa-rotor aircraft, are adopted in numerical simulations to verify the effectiveness of the proposed fault-tolerant control approach.

This paper describes a novel transformable land/air robot that is capable of terrestrial locomotion and aerial locomotion. What is unusual about the robot is that it can transform between the two modes of locomotion at will through the transformable mechanism, allowing the robot to overcome large obstacles in their mission environment. The wheel mechanism of the robot is shared by both terrestrial and aerial locomotion, instead of simply adding a quadrotor to a wheeled mobile robot. The objective of this paper is to design the robot and establish the kinematic and dynamic models for the transformable process. Herein, we focus on the design of the driving wheels and transformable mechanism. A series of experiments about the energy analysis and the transformation from aerial locomotion mode to terrestrial locomotion mode were performed with the physical prototype; the experiment results confirmed the validity of our design and the theoretical analysis that are helpful to optimize the key parameters in our design. Moreover, our work can provide a reference for the study of the flying car.

This paper focuses on the problem of automatic carrier landing control with time delay, and an antidelay model predictive control (AD-MPC) scheme for carrier landing based on the symplectic pseudospectral (SP) method and a prediction error method with particle swarm optimization (PE-PSO) is designed. Firstly, the mathematical model for carrier landing control with time delay is given, and based on the Padé approximation (PA) principle, the model with time delay is transformed into an equivalent nondelay one. Furthermore, a guidance trajectory based on the predicted trajectory shape and position deviation is designed in the MPC framework to eliminate the influence of carrier deck motion and real-time error. At the same time, a rolling optimal control block is designed based on the SP algorithm, in which the steady-state carrier air wake compensation is introduced to suppress the interference of the air wake. On this basis, the PE-PSO delay estimation algorithm is proposed to estimate the unknown delay parameter in the equivalent control model. The simulation results show that the delay estimation error of the PE-PSO algorithm is smaller than 2 ms, and the AD-MPC algorithm proposed in this paper can limit the landing height error within ±0.14 m under the condition of multiple disturbances and system input delay. The control accuracy of AD-MPC is much higher than that of the traditional pole assignment algorithm, and its computational efficiency meets the requirement of real-time online tracking.

In this paper, the multibody parachute-payload system is simplified and analyzed. A six-degree-of-freedom rigid body flight dynamic model is established to calculate the flight trajectory, attitude, velocity, and drop point of the parachute-payload system. Secondly, the random interference factors that may be encountered in the actual airdrop test of the parachute system are analyzed. According to the distribution law of the interference factors, they are introduced into the flight dynamic model. The Monte Carlo method is used to simulate the target and predict the flight trajectory and landing point distribution of the parachute system. The simulation results can provide technical support and theoretical basis for the parachute airdrop test. Finally, the genetic algorithm is used to identify the aerodynamic parameters of the large-scale Disk-Gap-Band parachute. The simulation results are in good agreement with the test results, which shows that the research method proposed in this paper can be applied to study practical engineering problems.

An optimization technique called shape-linked optimization, which is different from the traditional optimization method, is introduced in this paper. The research introduces an updated wing optimization design in an effort to adapt to continuous structure changes and shapes while optimizing for a lighter weight of the structure. The changing tendencies of the thickness of wing skins and the cross-section areas of the wing beams are fitted to continuous polynomial functions, whose coefficients are designed as variables, which is a different engineering approach from the size variants of the thickness and the area in the traditional optimization. The structural strength, stiffness, and stability are constraints. Firstly, this research unearths the significance of utilizing a modernized optimization process which alters the production of the traditional 12 or over 12 segment wing design and applies new approaches and methods with less variables that contribute to expedited design cycles, decreased engineering and manufacturing expenditures, and a lighter weight aircraft with lower operating costs than the traditional design for the operators. And then, this paper exemplifies and illustrates the validity of the above claims in a detailed and systematic approach by comparing traditional and modernized optimization applications with a two-beam wing. Finally, this paper also proves that the new optimized structure parameters are easier than the size optimization to process and manufacture.

This paper presents a novel nonlinear sliding mode control scheme that combines on-line model modification, a nonlinear sliding mode controller, and a disturbance observer to solve the essential problems in spacecraft electromagnetic docking control, such as model uncertainties, unknown external disturbances, and inherent strong nonlinearity and coupling. An improved far-field model of electromagnetic force which is much more accurate than the widely used far-field model is proposed to enable the model parameters to be on-line self-adjusting. Then, the relationship between magnetic moment allocation and energy consumption is derived, and the optimal direction of the magnetic moment vector is obtained. Based on the proposed improved far-field model and the research results of magnetic moment allocation law, a fast-nonsingular terminal mode controller driven by a disturbance observer is designed in the presence of model uncertainties and external disturbances. The proposed control method is guaranteed to be chattering-free and to possess superior properties such as finite-time convergence, high-precision tracking, and strong robustness. Two simulation scenarios are conducted to illustrate the necessity of modifying the far-field model and the effectiveness of the proposed control scheme. The simulation results indicate the realization of electromagnetic soft docking and validate the merits of the proposed control scheme. In the end of this paper, some conclusions are drawn.

The cooperative control in complex multitasks using unmanned aerial vehicle and unmanned ground vehicle (UAV/UGV) is an important and challenging issue in the multirobot cooperative field. The main goal of the task studied in this paper is to minimize the time and energy consumed by the system to complete the assigned tasks. In this paper, a complex multitask problem using the hybrid UAV/UGV system is studied, which is divided into three stages, namely, the stage of finding the optimal locations of the relay stations for the UGV; the stage of solving the path planning problem for the UGV; and the stage of the task assignment for multi-UAVs. Furthermore, an improved integrated method is proposed to deal with the cooperative control problems in these three stages. Firstly, an adaptive clustering method is proposed to determine the locations of the UGV relay stations, and then an improved cuckoo search algorithm is used to find the shortest path for the UGV. Finally, a grouping method is presented to solve the multitask allocation problem of UAVs, based on an improved dynamic programming algorithm. In addition, some simulations are carried out and the results show that the proposed method has better performance when it comes to the time and energy consumption and can effectively guide the hybrid UAV/UGV system to carry out the complex multitasks.

Aiming at a space manipulator with a joint-locked failure, a halt optimization strategy is proposed in this paper. Firstly, a halt configuration optimization model (HCOM) is constructed, to select an optimal configuration where the kinematic ability of the manipulator is the best. Secondly, considering the constraint of joint running parameters and the disturbance torque of the base, we construct and solve the halt motion optimization model (HMOM), which can achieve a steady halt and ensure the safety of the manipulator. The correctness and effectiveness of the proposed strategy in this paper are verified with a 7-DOF space manipulator. This strategy firstly puts forward the idea of halt configuration optimization and realizes the minimum global disturbance torque of the base in the halt process.

Global Navigation Satellite System (GNSS) has been the most popular tool for providing positioning, navigation, and timing (PNT) information. Some methods have been developed for enhancing the GNSS performance in signal challenging environments (urban canyon, dense foliage, signal blockage, multipath, and none-line-of-sight signals). Vector Tracking Loop (VTL) was recognized as the most promising and prospective one among these technologies, since VTL realized mutual aiding between channels. However, momentary signal blockage from part of the tracking channels affected the VTL operation and the navigation solution estimation. Moreover, insufficient available satellites employed would lead to the navigation solution errors diverging quickly over time. Short-time or temporary signal blockage was common in urban areas. Aiming to improve the VTL performance during the signal outage, in this paper, the deep learning method was employed for assisting the VTL navigation solution estimation; more specifically, a Long Short-Term Memory-Recurrent Neural Network (LSTM-RNN) was employed to aid the VTL navigation filter (navigation filter was usually a Kalman filter). LSTM-RNN obtained excellent performance in time-series data processing; therefore, in this paper, the LSTM-RNN was employed to predict the navigation filter innovative sequence values during the signal outage, and then, the predicted innovative values were employed to aid the navigation filter for navigation solution estimation. The LSTM-RNN was well trained while the signal was normal, and the past innovative sequence was employed as the input of the LSTM-RNN. A simulation was designed and conducted based on an open-source Matlab GNSS software receiver; a dynamic trajectory with several temporary signal outages was designed for testing the proposed method. Compared with the conventional VTL, the LSTM-RNN-assisted VTL could keep the horizontal positioning errors within 50 meters during a signal outage. Also, conventional Support Vector Machine (SVM) and radial basis function neural network (RBF-NN) were compared with the LSTM-RNN method; LSTM-RNN-assisted VTL could maintain the positioning errors less than 20 meters during the outages, which demonstrated LSTM-RNN was superior to the SVM and RBF-NN in these applications.

Estimating the 3D pose of the space object from a single image is an important but challenging work. Most of the existing methods estimate the 3D pose of known space objects and assume that the detailed geometry of a specific object is known. These methods are not available for unknown objects without the known geometry of the object. In contrast to previous works, this paper devotes to estimate the 3D pose of the unknown space object from a single image. Our method estimates not only the pose but also the shape of the unknown object from a single image. In this paper, a hierarchical shape model is proposed to represent the prior structure information of typical space objects. On this basis, the parameters of the pose and shape are estimated simultaneously for unknown space objects. Experimental results demonstrate the effectiveness of our method to estimate the 3D pose and infer the geometry of unknown typical space objects from a single image. Moreover, experimental results show the advantage of our approach over the methods relying on the known geometry of the object.

The configuration information of Integrated Modular Avionics (IMA) system includes almost all details of whole system architecture, which is used to configure the hardware interfaces, operating system, and interactions among applications to make an IMA system work correctly and reliably. It is very important to ensure the correctness and integrity of the configuration in the IMA system design phase. In this paper, we focus on modelling and verification of configuration information of IMA/ARINC653 system based on MARTE (Modelling and Analysis for Real-time and Embedded Systems). Firstly, we define semantic mapping from key concepts of configuration (such as modules, partitions, memory, process, and communications) to components of MARTE element and propose a method for model transformation between XML-formatted configuration information and MARTE models. Then we present a formal verification framework for ARINC653 system configuration based on theorem proof techniques, including construction of corresponding REAL theorems according to the semantics of those key components of configuration information and formal verification of theorems for the properties of IMA, such as time constraints, spatial isolation, and health monitoring. After that, a special issue of schedulability analysis of ARINC653 system is studied. We design a hierarchical scheduling strategy with consideration of characters of the ARINC653 system, and a scheduling analyzer MAST-2 is used to implement hierarchical schedule analysis. Lastly, we design a prototype tool, called Configuration Checker for ARINC653 (CC653), and two case studies show that the methods proposed in this paper are feasible and efficient.

This paper discusses the creation of a genetic algorithm to locate and optimize interplanetary trajectories using gravity assist maneuvers to improve fuel efficiency of the mission. The algorithm is implemented on two cases: (i) a Centaur-class target close to the ecliptic plane and (ii) a Centaur-class target with a high inclination to the ecliptic plane. Cases for multiple numbers of flybys (up to three) are discussed and compared. It is shown that, for the targets considered here, a single flyby of Jupiter is the most efficient trajectory to either target with the conditions and limitations discussed in this paper. In this paper, we also iterate on possible reasons for certain results seen in the analysis and show how these previously observed behaviors could be present in any trajectory found. The parameters and methods used in the algorithm are explained and justified over multiple real-life interplanetary missions to provide deeper insights into the development choices.

The paper addresses a problem of ballistic object tracking with the use of the cinetheodolite electro-optical tracking system. Electro-optical systems are applied for acquiring the trajectory data of missiles, satellites, and rockets used for delivery of satellites to their prevised orbits. Despite the importance of such systems and their applications, in the open literature there are no publications describing tracking algorithms processing data from cinetheodolites. The paper describes a model-based algorithm of estimation of position and parameters of target motion for such a system, developed by the authors. The model of the system, nonlinear both in its description of the target dynamics and the measurement equations, is presented in detail. The proposed algorithm of estimation is also described, and chosen simulation results are included in the paper. Furthermore, a comparison of the proposed estimation algorithm with other possible, but simpler algorithms is presented.

The advanced nonlinear sliding mode control method of DGEN380 aero engine is presented in this paper. This aero engine is a small high bypass ratio turbofan engine by which the nonlinear control approach of the aero engine is invested. And this paper focuses on the power management function of the aero engine control system which includes steady control and transient control. The mathematical model of DGEN380 aero engine is built by a set of nonlinear dynamic equation that is validated by experimental data. The single controller based on sliding mode approach is designed that can keep some certain thrust levels during steady state and maintain repeatable performance during transient operation from one requested thrust level to another. The single controller can offset the impact of the signal noise and harmonic disturbance at a certain power point. And the dynamic performance of the single controller is satisfactory at the transient process. The experiment is conducted by aero engine test bench for the single control.

In this paper, adaptive tracking control is applied to improve performances of an underactuated quadrotor helicopter with respect to attitude and position control. Firstly, the dynamic model is presented. Then a new trajectory tracking algorithm is designed by using the sigma-pi neural network and backstepping. The paper designs the sigma-pi neural network compensation control law and gives the Lyapunov-type stability analysis. Then the corresponding numerical simulations are performed by using MATLAB. Simulation results are shown to demonstrate the effectiveness of the proposed control strategy, which could reduce tracking error, decrease tracking time, and improve the anti-interference ability of the system.

This paper presents a globe coverage of constellation satellite in one revisit and the regional coverage at defined latitude. This constellation seems to be very close to optimal under the maximum revisit time comparing to the results in other papers. They are produced easily by using tables and data achievements. These satellites are fully connected by crosslinks sweeping the Earth. This model is more optimal comparing to the conventional constellations that distribute satellites evenly in the space. Since satellites on the LEO orbit are side by side, in most cases, they can maintain communication continuously. This special feature allows all satellites in the constellation connecting ground at any time when a satellite is available to the stations. Length of the crosslink is allowed to reject location connection or real-time data transmission. For example, six satellites in the constellation cover the whole Earth within one revisit time and all the data are collected by two Earth stations for keeping continuous coverage. Thus, the adjacent satellites may be more efficient and provide more coverage.

Chinese space station has been in construction phase, and it will be launched around 2020. Lots of orbital replacement units (ORUs) are installed on the space station, and they need to be replaced on orbit by a manipulator. In view of above application requirements, the control method for ORU changeout is designed and verified in this paper. Based on the analysis of the ORU changeout task flow, requirements of space station manipulator’s control algorithms are presented. The open loop path planning algorithm, close loop path planning algorithm based on visual feedback, and impedance control algorithm are researched. To verify the ORU changeout task flow and corresponding control algorithms, a ground experiment platform is designed, which includes a 6-DOF manipulator with a camera and a force/torque sensor, an end effector with clamp/release and screwing function, ORU module, and ORU store. At last, the task flow and control algorithms are verified on the test platform. Through the research, it is found that the ORU changeout task flow designed in this paper is reasonable and feasible, and the control method can be used to control a manipulator to complete the ORU changeout task.

With radar and surface-to-air missiles posing an increasing threat to on-orbit spacecraft, low-observable satellites play an important role in low-thrust transfers. This paper presents the design for a low-thrust geostationary earth orbit (GEO) transfer control strategy which takes into consideration the low-observable constraint and discusses Earth shadow and perturbation. A control parameter optimization addresses the orbit transfer problem, and five thrust modes are used. Simulation results show that the method outlined in this paper is simple and feasible and results in reduced transfer time with a small amount of calculation. The method therefore offers a useful reference for low-thrust GEO transfer design.

The aeroelastic model of a folding wing varies with different configurations, so it actually represents a parameter-varying system. Firstly, a new approach based on interpolation of local models is proposed to generate the linear parameter-varying model of a folding wing. This model is capable of predicting the aeroelastic responses during the slow morphing process and is suitable for subsequent control synthesis. The underlying inconsistencies among local linear time-invariant (LTI) models are solved through the modal matching of structural modes and the special treatment of the rational functions in aerodynamic models. Once the local LTI models are represented in a coherent state-space form, the aeroservoelastic (ASE) model at any operating point can be immediately generated by the matrix interpolation technique. Next, based on the present ASE model, the design of a parameterized controller for suppressing the gust-induced vibration is studied. The receptance method is applied to derive fixed point controllers, and the effective independence method is adopted and modified for optimal sensor placement in variable configurations, which can avoid solving ill-conditioned feedback gains. Numerical simulation demonstrates the effectiveness of the proposed interpolation-based modeling approach, and the parameterized controller exhibits a good gust mitigation effect within a wide parameter-varying range. This paper provides an effective and practical solution for modeling and control of the parameterized aeroelastic system.

Considering recurrent optimization process in model predictive control (MPC), the model uncertainties and disturbances terms in the missile’s guidance and control model can degrade recursive feasibility, and there are control mutation problems in common MPC algorithm. This paper presents a disturbance rejection model predictive control algorithm for missile integrated guidance and control (IGC). Firstly, a sliding mode observer (SMDO) is designed to estimate the unknown disturbances caused by target maneuvering. Secondly, the method of optimizing control increment is adopted in MPC to avoid the phenomenon of control mutation in the model calculation. By limiting the control increment in each cycle, it ensures the continuity of the control input. Thirdly, by combining the SMDO and MPC, an IGC algorithm is presented, and the stability of the algorithm is proved by using Lyapunov stability theory. Finally, the simulation results with different impact angles verify the effectiveness of the proposed algorithm for intercepting maneuver target.

Since the beampattern has the characteristics of range-angle dependence, frequency diverse array multiple-input multiple-output (FDA-MIMO) radar has a good application prospect. There have been many studies to improve the performance of the beampattern by optimizing the frequency offset. However, on the basis of fully understanding the time parameters, the relationship between the array element frequency offset and the beampattern performance still needs to be clarified. Based on a new FDA-MIMO radar framework, this paper presents an analytical solution of the beampattern, which removes the influence of the time parameter. Taking the minimum main lobe as the objective function, an analytical method for solving a better frequency offset is given. Then, a method of using the window function was proposed to reduce the high side lobes of the range dimension. Comparing with the existing FDA radar beampattern design methods, it can achieve a more focusing beampattern. The simulation results verify the correctness of the theory.

The intelligent auxiliary decision-making (IADM) is emerging as a feasible solution for air traffic control (ATC) to reduce undesirable conflicts in shared airspace; meanwhile, unmanned aerial vehicles (UAVs) can be operated with enhanced efficiency and safety using IADM. This paper presents the conflict risk framework of the MAV\UAV flight that improves flight safety of MAVs and UAVs in shared airspace. This is accomplished by focusing on two steps: First, determine the minimum safety communication interval between the UAV and controller; second, build a conflict risk model to detect which decision mechanism will minimize risk. Our approach provides a standard model to start with to improve IADM and allow engineers to focus on the operational purpose of MAV/UAV. Results show that our work presented here is practical and straightforward, and it brings an evident engineering application prospect.

A fan-blade out (FBO) event may cause complex vibrations in an aeroengine. A fusing structure protects the structural integrity of the whole aeroengine after an extreme accident, such as a blade-loss event. In this paper, we investigate not only the transient and steady responses of a simulated aeroengine model with a fusing structure after an FBO event but also the changes made to the model because of the fusing structure. Our simulated model of an aeroengine includes two rotors, bearings, and a casing. The results for the dynamic response of the simulated model show that the fusing structure can reduce the steady-state response and the impact load on the support bearings in the rotor system. The rubbing impact between the blades and casing was accounted for. A fast method for calculating the response of fused structures was developed, which may be useful when designing the stiffness of the fusing structure.

Aeroengine is one of the most concerned objects of the relevant aviation industry and researchers, and it is a hard work to assess and predict performance degradation due to the complex structure and the changeable operating condition of the engine. In order to realize the performance degradation assessment and remaining useful life (RUL) prediction of aeroengine, this paper proposes a two-stage assessment and prediction method based on data fusion. First, the standard deviation merged by multiple selected features is used as the health indicator to characterize the engine performance. Second, a sliding window detection method called average local window slope is proposed to determine the current health state of observations by a specified rule. Finally, the RUL prediction is performed on the observation in the two stages, respectively. On the one hand, a similarity-based RUL prediction method is used to engines in the health stage, and on the other hand, for engines in the degradation stage, a RUL prediction method based on a mapping function of the standard deviation and the current using cycle is established. The proposed method has been applied and verified on the NASA’s C-MAPSS simulation data. Results of degradation assessment and prediction show that the proposed method is trustworthy and feasible from the engineering perspective, and it has better performance in the comprehensive indicator compared with other methods.

A common assumption in SAR image formation and processing algorithms is that the chirp rates of the transmitted and received radar signals are exactly the same. Dechirp processing is also done based on this common assumption. In real scenarios, the chirp rate of the received signal is different from that of the transmitted signal due to several reasons. In case the difference between the chirp rates of the transmitted and received signals is obvious, the demodulation and compression of the received pulse are not carried out precisely and defocusing the targets and the output images of the SAR processor results. In the present paper, a new technique is proposed to improve the image formation quality of SAR by exploiting chirp rate estimation methods. Based on the proposed technique, the chirp rate of the received signal is estimated, and then, dechirp is carried out by using a time-reversed complex conjugate filter constructed based on the estimated chirp rate. In this stage, the existing chirp rate estimation algorithms can be used. The quality of the output image is assessed using PSLR as a quantitative criterion and the average number of point target extension pixels along the azimuth direction. Simulation results indicated that the smaller the average number of point target extension pixels along with azimuth and the higher the PSLR average is, the better the output image quality would be. Therefore, output images obtained from the proposed method by exploiting chirp rate estimation algorithms would have a better quality with a higher PSLR average (14.1 and 13.6) and also the lower average number of point target extension pixels along the azimuth directions (2.1 and 4.9) than the common method with PSLR average (8.3) and an average number of point target extension pixels along the azimuth direction (7.1).

In this paper, a bounded finite-time control strategy is developed for the final proximity maneuver of spacecraft rendezvous and docking exposed to external disturbance and input quantization. To realize the integrated control for spacecraft final proximity operation, the coupling kinematics and dynamics of attitude and position are modeled by feat of Lie group SE 3 . With a view to improving the convergence rate and reducing the chattering, an adaptive finite-time controller is proposed for the error tracking system with one-step theoretical proof of stability. Meanwhile, the hysteresis logarithmic quantizer is implemented to effectively reduce the frequency of data transmission and the quantization errors are reduced under the proposed controller. The algorithms outlined above are based on an integrated model expressed by SE 3 and denoted by uniform motion states, which can simplify the design progress and improve control precision. Finally, simulations are provided to exhibit the effectiveness and advantages of the designed strategy.

The advantages of the Low Earth Orbit (LEO) satellite include low-latency communications, shorter positioning time, higher positioning accuracy, and lower launching, building, and maintenance costs. Thus, the introduction of LEO satellite constellation as a regional navigation augmentation system for the current navigation constellations is studied in this paper. To achieve the navigation performance requirement with the least system cost, a synthetic approach is presented to design and deploy a cost-efficient LEO navigation augmentation constellation over 108 key cities. To achieve lower construction costs, the constellation is designed to be deployed by constrained piggyback launches, which brings additional complexity to the constellation design. Two optimization models with discrete and continuous performance indices are established. They are solved by the genetic algorithm and differential evolution algorithm, and both Walker and Flower constellations are adopted. Results for 77 and 70 satellites are obtained. During the construction phase, a synthesis procedure containing five impulses is proposed by utilizing natural drift under J 2 perturbation. This work presents a method for designing the optimal LEO navigation constellation under a constraint deployment approach with the lowest construction cost and a strategy to deploy the constellation economically.

As an emerging topic, the swarm of autonomous unmanned aerial vehicles (UAVs) has been attracting great attention. Due to the indeterminacy of sensors, distributed cooperative swarms have been considered to be efficient and robust but challenging to design and test. To facilitate the development of distributed swarms, it has been proposed to utilise a simulation platform for cooperative UAVs using imperfect perception. However, the existing simulation platforms cannot satisfy this demand due to a few reasons. First, they are designed for a specific purpose, and their functionalities are difficult to extend. Second, the existing platforms lack compatibility to be applied to different types of scenarios. Third, the modelling of these platforms is too simplified to simulate flight motion dynamic and noisy communication accurately, which may cause a difference in performance between the simulation and real-world application. To address the mentioned issues, this paper models the problem and proposes a simulation platform for distributed swarm cooperative perception, which addresses software engineering concerns and provides a set of extendable functionalities of a cooperative swarm, including communication, estimation, perception fusion, and path planning. The applicability of the proposed platform is verified by simulations with the real-world application. The simulation results demonstrate that the proposed system is viable.

In this paper, Proper net is proposed to construct variable cycle engine’s analytical redundancy, when all control variables and environmental variables change simultaneously, also accompanied with the whole engine’s degradation. In another word, Proper net is proposed to solve a multivariable, strongly nonlinear, dynamic, and time-varying problem. In order to make the topological structure of Proper net physically explainable, Proper net’s topological structure is designed according to physical relationship between variables, by which means analytical redundancy based on Proper net achieves higher accuracy with less calculation time. Experiments were compared with performance of analytical redundancy based on Proper net, seven convolutional neural network topological structures, and five shallow learning methods. Results demonstrate that under condition of average relative error less than 1.5%, Proper net is the most accurate and the least time-consuming one, which proves not only the effectiveness of Proper net but also the feasibility of topological structures’ design method based on physical relationship.

Hypersonic vehicle has gained increasing attention due to its high cruise speed and long voyage. In this paper, an enhanced Sequential Approximate Optimization method is proposed for aerodynamic optimization of a hypersonic vehicle. In this method, a constrained design of experiment method is adopted to generate the initial sampling set with adequate number of feasible points. A field metamodel is proposed to surrogate the aerodynamic parameters distributions in the flow field obtained by the aerodynamic simulation. A hybrid metamodel combing radial basis functions and polynomial chaos expansion is applied to construct the field metamodel with good approximate performance. A robust mesh morphing scheme based on radial basis functions is developed to generate high-quality meshes for the sequential optimization scheme. The hypersonic vehicle aerodynamic optimization problem is performed using the proposed optimization framework and satisfactory results are obtained with limited computational budgets. Results show that the proposed field metamodel-enhanced Sequential Approximate Optimization method possesses powerful optimization performance and promising prospects in the field of hypersonic vehicle optimization design.

Aiming at the uncertainty and external disturbance sensitivity of the near space vehicles (NSV), a novel sliding mode controller based on the high-order linear extended state observer (LESO) is designed in this paper. In the proposed sliding mode controller, the double power reaching law is adopted to enhance the state convergence rate, and the high-order LESO is designed to improve the antidisturbance ability. Moreover, the appropriate observer bandwidth and extended order are selected to further reduce or even eliminate the disturbance by analyzing their influences on the observer performance. Finally, the simulation demonstrations are given for the NSV control system with uncertain parameters and external disturbances. The theoretical analyses and simulation results consistently indicate that the proposed high-order LESO with carefully selected extended order and observer bandwidth has better performance than the traditional ones for the nonlinear NSV system with parametric uncertainty and external disturbance.

The stowing and deployment processes of a self-deployable sunshield are investigated numerically in this paper. The composition of the self-deployable sunshield is described. Deployed moment theoretical models for lenticular booms are formulated based on the bending theory of curved shell. The numerical analysis method of deployed moment is proposed. Two types of control methods for a fold crease are presented, and a dynamic analysis model considering geometry and nonlinear contact is built. The analysis results indicate that the press flattening method can be used effectively for controlling the fold crease, and the analytical results of the deployed moment are very close to the theoretical results. A stowing and deployment process analysis of the self-deployable sunshield is conducted. Thus, the deployment configurations and the time history curves of the dynamic behaviors are obtained. The results verify the feasibility of the analysis model, and this study can provide technical support for the engineering application of the self-deployable sunshield.

This paper presents an adaptive, simple, and effective guidance approach for hypersonic entry vehicles with high lift-to-drag (L/D) ratios (e.g., hypersonic gliding vehicles). The core of the constrained guidance approach is a closed-form, easily obtained, and computationally efficient feedback control law that yields the analytic bank command based on the well-known quasi-equilibrium glide condition (QEGC). The magnitude of the bank angle command consists of two parts, i.e., the baseline part and the augmented part, which are calculated analytically and successively. The baseline command is derived from the analytic relation between the range-to-go and the velocity to guarantee the range requirement. Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. The inequality path constraints in the velocity-altitude space are translated into the velocity-dependent bounds for the magnitude of the bank angle based on the QEGC. The sign of the bank command is also analytically determined using an automated bank-reversal logic based on the dynamic adjustment criteria. Finally, a feasible three-degree-of-freedom (3DOF) entry flight trajectory is simultaneously generated by integrating with the real-time updated command. Because no iterations and no or few off-line parameter adjustments are required using almost all analytic processing, the algorithm provides remarkable simplicity, rapidity, and adaptability. A considerable range of entry flights using the vehicle data of the CAV-H is tested. Simulation results demonstrate the effectiveness and performance of the presented approach.

In this paper, a real-time optimal attitude controller is designed for staring imaging, and the output command is based on future prediction. First, the mathematical model of staring imaging is established. Then, the structure of the optimal attitude controller is designed. The controller consists of a preprocessing algorithm and a neural network. Constructing the neural network requires training samples generated by optimization. The objective function in the optimization method takes the future control effect into account. The neural network is trained after sample creation to achieve real-time optimal control. Compared with the PID (proportional-integral-derivative) controller with the best combination of parameters, the neural network controller achieves better attitude pointing accuracy and pointing stability.

This paper addresses the analytical formation control and cooperative guidance problem for multiple hypersonic gliding vehicles under distributed communication. The gliding flight of the hypersonic gliding vehicle is divided into formation control phase and time coordination phase. In formation control phase, based on the idea of path tracking, the formation controller is designed using the second-order consensus protocol with normal positions as the coordination variables. In time coordination phase, based on the quasi-equilibrium gliding condition and the assumption of uniform deceleration motion, the analytical expression of time to go is derived. Then, the cooperative guidance method is developed using the first-order consensus protocol with time to go as the coordination variable. The proposed method takes full consideration of the characteristics of hypersonic gliding vehicle, such as complex nonlinear dynamics, no thrust, and quasi-equilibrium gliding condition, and no online numerical iteration is needed, which is well applicable for hypersonic gliding vehicles. Simulation results demonstrate the effectiveness of the formation control and cooperative guidance method.

The paper summarizes the experiences with the operation of the piNAV GPS receiver in a 1U unstabilized CubeSat operated on LEO orbit. piNAV L1 is a GPS receiver developed by an author for small satellite missions. The receiver is equipped with the 15 GPS L1 C/A channels and acquisition accelerator that shortens the cold start of the receiver on LEO to 65 s. The typical power consumption is 120 mW. Lucky-7 is a private 1U technological CubeSat with power budget 1 W that operates on the quasisynchronous polar orbit at altitude 520 km. One of its scientific missions is to test the operation of GPS. The space experiments proved the successful operation of the GPS receiver. The position information was available for approximately 80% of the time, where the position outage was caused by a satellite rotation and relatively long navigation signal reacquisition. The experimental data proved that the position availability can be improved by a higher-performance signal acquisition engine.

To meet the different requirements in the industrial area, a novel reconfigurable parallel mechanism is proposed based on the spatial multiloop overconstrained mechanism. The configurations can be changed by driving the low-DOF (degree-of-freedom) overconstrained mechanism. The mobility of this mechanism is investigated. And the kinematic model and Jacobian matrix are both established. Based on the Jacobian matrix, the workspace, stiffness, and conditional number are all analyzed. To focus on the application in the industrial area, this paper proposes a method to establish the relationship between the performance and the structural parameters by using the modified BP neural network. Based on this method, the structural parameters can be chosen by the requirements of the special task in the industrial area. Finally, some numerical examples are presented to verify the method.

The aerospace industry needs to be provided with system solutions to technologically challenging and mission-critical problems. Based on the industrial control point of view, development engineers must take costs and existing standards into account in order to effectively design, implement, and deploy control systems with reasonable costs. The customization and reusability are important factors associated with the production of new applications in order to reduce their costs, resources, and development time. In this work, the Model-Driven Architecture (MDA)/Model-Based Systems Engineering (MBSE) approach combined with the real-time Unified Modeling Language (UML)/Systems Modeling Language (SysML), Unscented Kalman Filter (UKF) algorithm, and hybrid automata is specialized to obtain a hybrid control model in order to conveniently deploy controllers of Quadrotor Unmanned Aerial Vehicles (Q-UAVs). This hybrid control model also provides a real-time capsule pattern, which allows the designed elements to be customizable and reusable in new applications of various multirotor UAVs of the Vertical Take-Off and Landing (VTOL) type. The Q-UAV dynamics and control architecture are combined with the MDA/MBSE specialization as follows: the Computation Independent Model (CIM) is defined by specifying the use-case model together with the UKF algorithm and hybrid automata to intensively gather the control requirements. The Platform Independent Model (PIM) is then designed by specializing the real-time UML/SysML’s features to obtain the main control capsules, ports, and protocols, together with their dynamic evolution. The detailed PIM is subsequently transformed into the PSM by open-source platforms to rapidly implement and deploy the Q-UAV controller. The paper ends with trial flights and deployment results that show good feasibility to be used for a trajectory-tracking controller of a low-cost Q-UAV. In this case study, the Q-UAV controller is implemented with the simulation model in the OpenModelica tool. The obtained simulation results then allow the main control elements and their properties to be defined, as well as building the implementation libraries in the Arduino environment based on C++ language to quickly perform the realization model in the ATMEGA32-U2 and STM32 Cortex-M4 microcontrollers.

This paper investigates the design problem of the attitude controller for air-breathing supersonic vehicle subject to uncertainties and disturbances. Firstly, the longitudinal model is established for the attitude controller design which is devised as a strict feedback formulation, and a transformed tracking error is derived with the prescribed performance control technique such that it can limit the tracking error to a predefined region. Then, a novel linear active disturbance rejection control scheme is proposed for the attitude system to enhance the steady-state and transient-state performances by incorporating the transformed tracking error. On the basis of the Lyapunov stability theorem, the convergence and stability characteristics are both rigorously proved for the closed-loop system. Finally, extensive contrast simulations are conducted to demonstrate the effectiveness, robustness, and advantage of the proposed control strategy.