Close Formation Flight Research Articles

Relative position estimation using modulated magnetic field for close proximity formation flight

This paper presents a method to estimate relative position vectors between spacecraft equipped with magnetic coils and magnetic field sensors for close proximity operation. Filters can segregate a magnetic field with a particular frequency if spacecraft drive their coils with this specific frequency. The proposed method utilizes the amplitude of the magnetic field with a particular frequency to estimate relative position vectors. The method consists of an initial position estimator and a sequential position estimator, which is an unscented Kalman filter. The initial position estimator provides a coarse estimate for the relative position vectors using the segregated magnetic field. Relation between the magnetic field and relative position vector is derived analytically in this article for the initial position estimator. The unscented Kalman filter refines the estimation accuracy by initializing the filter with the estimate by the initial position estimator. It is shown that a spacecraft can conduct relative position vector estimation using the magnetic field of a target spacecraft, provided that a few conditions clarified in the article are satisfied. Finally, the proposed estimators are evaluated numerically via simulations.

Aerodynamic Analysis of Fixed-Wing Unmanned Aerial Vehicles Moving in Swarm

This paper presents a close-formation flight of two unmanned aerial vehicles (UAVs) and the aim of the study is to improve the understanding of the vortex effects between fixed-wing UAVs in a swarm using computational fluid dynamics (CFD) tools. To validate the numerical method, results of a variable-density wind tunnel test from the literature were used. This numerical CFD analysis was used to determine the lift coefficient (CL) and the drag coefficient (CD) values for a single UAV at various angles of attack. When examining the aerodynamic impact areas behind the UAV, the longitudinal distance between the two UAVs is not particularly effective for close flight. Therefore, CFD analyses were carried out on the two UAVs for both vertical and lateral distances. The optimum position for close-formation flight was identified using CL/CD ratios. The results of the analysis indicate that the most effective flights, across all lateral positions, occur when the two UAVs are vertically at the same height. In terms of aerodynamic efficiency, the most effective points for close-formation flight for wingspan b are at lateral distances of 0.875 b and 1 b. At these positions, flight efficiency can be increased by approximately 11.5%.

The formation of unmanned aerial vehicle swarm

The Unmanned Aerial Vehicles (UAVs) have played a much more important role in daily life, ranging from entertainment and military use, in which case UAV swarm is adopted as means to lower the operation cost, as well as to compensate for the insufficient performance of a single drone. However, sharp distinctions between individual drones and UAV swarm exist not only in the field of controlling, but in the area of aerodynamics as well. To conclude, the operator, instead of a team of engineers, needs to perform severe tasks with the help of several drones which act as a swarm rather than interfere with each other. Meanwhile, in order to improve the efficiency of UAV swarm, different formations are looked into from different fields, mainly aerodynamics and control engineering. This review will mainly focus on the aerodynamics performance of formations of swarming UAVs, both in close formation flight and extended formation flight. Comparisons will also be made to show the merits and demerits of these formations, providing convenience for path planning of different tasks.

Reinforcement learning based UAV formation control in GPS-denied environment

Highly accurate positioning is a crucial prerequisite of multi Unmanned Aerial Vehicle close-formation flight for target tracking, formation keeping, and collision avoidance. Although the position of a UAV can be obtained through the Global Positioning System (GPS), it is difficult for a UAV to obtain highly accurate positioning data in a GPS-denied environment (e.g., a GPS jamming area, suburb, urban canyon, or mountain area); this may cause it to miss a tracking target or collide with another UAV. In particular, UAV close-formation control in GPS-denied environments faces difficulties owing to the low-accuracy position, close distance between vehicles, and nonholonomic dynamics of a UAV. In this paper, on the one hand, we develop an innovative UAV formation localization method to address the formation localization issues in GPS-denied environments; on the other hand, we design a novel reinforcement learning based algorithm to achieve the high-efficiency and robust performance of the controller. First, a novel Lidar-based localization algorithm is developed to measure the localization of each aircraft in the formation flight. In our solution, each UAV is equipped with Lidar as the position measurement sensor instead of the GPS module. The k-means algorithm is implemented to calculate the center point position of UAV. A novel formation position vector matching method is proposed to match center points with UAVs in the formation and estimate their position information. Second, a reinforcement learning based UAV formation control algorithm is developed by selecting the optimal policy to control UAV swarm to start and keep flying in a close formation of a specific geometry. Third, the innovative collision risk evaluation module is proposed to address the collision-free issues in the formation group. Finally, a novel experience replay method is also provided in this paper to enhance the learning efficiency. Experimental results validate the accuracy, effectiveness, and robustness of the proposed scheme.

Modeling, simulation, analysis and control of close formation flight

This paper focuses on the aerodynamic characteristics of aircraft close formation flight. The formation model for small unmanned aircraft is studied, and the disturbance of the wake induced velocity generated by the leader aircraft on the tail aircraft is analyzed. It is found that the lead aircraft has a significant effect on the lift and drag of the tail aircraft. It is also demonstrated that the aerodynamic characteristics of the tail plane can be improved when the following plane is in the proper position of the leader in formation flight. Precise position control of the tail plane in general flight operations is achieved under the influence of the tail vortex. Firstly, a model for the wake vortex of the leader was established, and then computational fluid dynamics(CFD) software was used to simulate the two unmanned aerial vehicles (UAVs) to verify the accuracy of the model. A control algorithm was designed to realize the stability of formation flight. Mathematical simulation and validation were performed. The designed control law is able to keep the tail plane in the appropriate position in the formation flight so that the tail plane is subjected to the maximum lift.

A continuous modeling method via improved pigeon-inspired optimization for wake vortices in UAVs close formation flight

This paper explores the modeling of wake vortices to estimate the wake vortex effect in unmanned aerial vehicles (UAVs) close formation flight. A continuous horseshoe vortex method is proposed based on the consideration of a compromise between estimation accuracy and computational efficiency. Using the proposed modeling method, the wake vortex model can easily adapt to UAVs with different wing shapes by adjusting model parameters. Furthermore, the interaction coefficient of filaments of the wake vortex is introduced to improve the estimation accuracy. However, the analytical value is solved difficultly by theoretical derivation. Therefore, the improved pigeon-inspired optimization is developed to search for the optimal value. On the other hand, the wake vortex effect is formulated by the statistical average strategy. The formulated wake vortex effect can be readily utilized to conduct a realistic dynamic model of the vortex-suffering UAV. Simulation results show that the estimation accuracy of the proposed modeling method increases by approximately 30% and 34%, compared with the single and multiple horseshoe vortex methods respectively. Furthermore, the computational efficiency is sufficient enough for the real-time estimation in UAVs close formation flight.

Robust Nonlinear Close Formation Control of Multiple Fixed-Wing Aircraft

This paper investigates robust nonlinear control for close formation flight of multiple fixed-wing aircraft. It aims to achieve precise position control in general flight operation under the aerodynamic impact induced by the trailing vortices of leader aircraft. One crucial concern is the boundedness of position errors subject to uncertainties and disturbances to be regulated with accuracy. This paper develops a robust nonlinear control algorithm to fulfill precise close formation-tracking control. The proposed control algorithm consists of baseline control laws and disturbance observers. The baseline control laws are employed to stabilize the nonlinear dynamics of close formation flight, whereas the disturbance observers are introduced to compensate system uncertainties and formation-related aerodynamic disturbances. The position control performance can be guaranteed within the desired boundedness to harvest enough drag reduction for a follower aircraft in close formation using the proposed design. The effectiveness of the proposed design is demonstrated via the numerical simulation of the close formation flight of two fixed-wing aircraft.

Cooperative positioning for low-cost close formation flight based on relative estimation and belief propagation

Cooperative Positioning (CP) is considered to be a promising method for close formation flight, which can fully exploit the navigation information in a network. This work proposes a new CP framework based on relative position estimation and optimized belief propagation (BP), aiming to enhance the absolute positioning accuracy for low-cost UAVs. Relative estimation is used to augment the BP estimation, which can fully exploit the onboard sensors. For BP, it is widely used as a CP estimator. This work proposes an optimized BP based on vectorized message passing and message evaluation, which can make an effective balance between computational load and estimation accuracy. Simulation results show that the proposed CP framework has better estimation accuracy than traditional CP methods, and has lower computational load than the best existing non-parametric BP (NBP) method with equivalent accuracy.

Vertically Optimal Close Formation Flight Control Based on Wingtip Vortex Structure

In this paper, aiming to drive the unmanned aerial vehicle (UAV) to the optimal position of the vertical plane in the close formation flight, a control method that is based on extended state observer (ESO) and wingtip vortex structure is proposed. This method is suitable for cases where the optimal position is unknown and there are gusts. The scheme is divided into three parts. In the first part, an ESO is designed to estimate the change of the lift and other external disturbances on the follower UAV. In the second part, an algorithm making use of the estimates of the change of the lift to predict the optimal position for the follower UAV is proposed. In the third part, to stabilize the UAV around the optimal position, a sliding mode controller is designed and the external disturbances on the follower UAV are compensated by the ESO. The simulation results show that the followers could automatically adjust their spatial positions to track the predicted optimal positions behind the leader UAV and achieve the precisely close formation flight without the information of leader’s altitude.

Integrated Fault-Tolerant Control for Close Formation Flight

This paper investigates the position-tracking and attitude-tracking control problem of close formation flight with vortex effects under simultaneous actuator and sensor faults. On the basis of the estimated state and fault information from unknown input observers and relative output information from neighbors, an integration of decentralized fault estimation and distributed fault-tolerant control is developed to deal with bidirectional interactions and to guarantee the asymptotic stability and $H_\infty$ performance of close formations.

Tanker Wake Effects on the Trailing UAV in Autonomous Aerial Refueling

Autonomous aerial refueling is a typical close formation flight process, in which the tanker wake has a strong aerodynamic influence to the receiver. In order to develop the accurate aerodynamic models in refueling simulations and design the control laws for autonomous aerial refueling, the tanker wake effects on an Unmanned Aerial Vehicle (UAV) are investigated through ANSYS CFX 15.0. A simplified boom-equipped tanker and a tailless delta wing UAV (named ZD-X) are used in this study. The aerodynamic characteristics of ZD-X in single flight are calculated first and the results are used as the benchmark for comparison. Then the aerodynamic characteristics of ZD-X under the effects of tanker wake are calculated, the final results are given in incremental form to facilitate comparative analysis. Numerical results are obtained from the tanker and receiver at varying lateral, vertical and longitudinal spacings. It is observed that the tanker wake effects on the receiver mostly come from wingtip vortices of the tanker wing and horizontal tail, and the lateral and vertical spacings have significant effects on the aerodynamic characteristics of the receiver, while the longitudinal spacing has almost no effect.

A Hierarchical and Prioritized Framework in Coordinated Maneuver of Multiple UAVs Based on Guidance Regulator

The structure of mission management and maneuver planning for multiple UAVs in close formation flight is investigated. This article provides a distributed and priority-based platform of guidance and control model to meet requirements for each coordinated maneuver. To accomplish the coordinated maneuvers of multiple UAVs, some levels of hierarchy from mission planning to accurate guidance law are presented. The main focuses have been on the structure of equations and vicinity pattern to avoid a probable collision during maneuver so the high-level decision-maker can integrate all irregularities and solve them at the same time. Unlike complex control systems, the proposed algorithm provides outstanding following performance and inherent collision avoidance pattern due to prioritized tracking. The results show the admissible performance of the framework designed for implementing coordinated maneuvers due to its lower collision probability and noise resistance. According to the simulations, this method also resolves irregularity and disarrangements in the close formation flights and tracking media.

Adaptive Fault-Tolerant H-Infinity Output Feedback Control for Lead-Wing Close Formation Flight

This paper investigates the attitude and position tracking control problem of the Lead–Wing close formation system with unknown multiplicative actuator faults. In close formation flight, the movement of the Wing unmanned aerial vehicle (UAV) is influenced by the vortex effects of the neighboring Lead UAV. This situation requires a modeling of the aerodynamic coupling vortex effects and linearization on the basis of optimal close formation geometry. Adaptive actuator fault parameters are identified by merging the improved unknown input observers, and adaptive laws with projection functions are presented for actuator fault tracking. The sufficient condition corresponding to the existence of unknown input observers is given. Then, an adaptive fault-tolerant H-infinity output feedback control scheme is developed to guarantee the asymptotic stability, H-infinity closed-loop system performance, and attitude and position tracking properties while the Lead UAV is being maneuvered. Simulation results of the Lead–Wing close formation flight validate the efficiency of the proposed fault-tolerant control algorithm.

Optimization of positional parameters of close-formation flight for blended-wing-body configuration

In the present study, we study formation flight with two flying wing configurations. A low speed wind tunnel test is conducted to validate the accuracy of the Computational Fluid Dynamics (CFD). Two optimization procedures are implemented at a high subsonic speed. The free stream Mach number is kept at 0.85, the lead aircraft's angle of attack is 2°, and the following aircraft's angle of attack is 2° as well. The maximum lift-to-drag ratio of the following aircraft is achieved as the lateral spacing is 0.853 b, and the vertical offset is 0.022 b (b is the wingspan). As much as 24.7% induced drag reduction is achieved at the optimized state. A pair of counter-rotating vortices interact and weaken each other. By analyzing the Kriging model constructed in the optimization procedure, it seems that the following aircraft's aerodynamic performance is sensitive to lateral spacing and vertical spacing, but insensitive to longitudinal spacing in close-formation flight. The best drag reduction position places in the following aircraft's wing tip is positioned at the core of the leading aircraft's wing tip vortex.

UDE-Based Robust Command Filtered Backstepping Control for Close Formation Flight

This paper presents an uncertainty and disturbance estimator (UDE)-based nonlinear robust controller for close formation flight in light of the command filtered backstepping technique. To maximize the formation aerodynamic benefits at different flight maneuvers, the formation geometry is described in the wind frame of the leader aircraft. A novel nonlinear robust close formation control algorithm with a two-degree-of-freedom nature is developed. The command filtered backstepping technique is employed to design the baseline formation controller, whereas the UDE is introduced to enhance the robustness of the baseline formation control. The proposed control law can lead to desired tracking performance for the close formation flight under different maneuvers without using the acceleration information of the leader aircraft, asymptotical stability for the close formation flight at a level and straight flight with constant speeds, and enough robustness against the formation aerodynamic effects by purely observing system states and inputs. Numerical simulations are performed to show the feasibility and efficiency of the proposed controller.

Numerical Aerodynamic Characteristics Analysis of the Close Formation Flight

The aerodynamic characteristics of the close formation flight are numerically analyzed to facilitate a greater understanding of the vortex effects between UAVs and technically support the application of close formation flight for UAVs. The aerodynamic characteristics of a single UAV are calculated, the results of which are used as the reference to the variation of aerodynamic values in the comparison with close formation flight. The vortex effects of the leading UAV on the aerodynamic characteristics of the trailing UAV in the two UAV close formation flight are analyzed. The position where the trailing UAV obtains the maximum lift-to-drag ratio is defined as the optimal position. Based on the optimal position, three different types of three UAV formations are designed to explore the preliminary application of the aerodynamic benefits in the close formation flight for multiple UAVs. It is observed that the incremental aerodynamic forces and moments of the trailing UAV vary with the lateral and vertical spacing between the two UAVs, and the trailing UAV can obtain significant aerodynamic improvement if positioned at optimal position behind the leading UAV while in close formation flight. It is also proved that the aerodynamic characteristics of the close formation for three UAVs can be improved when the formation is designed based on the optimal position, and this will increase the range and endurance of the UAVs in operational application.

Aerodynamic model-based robust adaptive control for close formation flight

This paper presents an aerodynamic model-based robust adaptive control algorithm for close formation flight. The leader aircraft is assumed to be at level and straight flight which characterizes the most common scenario for close formation flight. The formation aerodynamic effects are assumed to be unknown, but an online formation aerodynamic model is available to predict those effects. In light of the online formation aerodynamic model, a robust adaptive control algorithm is thereafter developed on the follower aircraft to counteract the unknown formation aerodynamic effects and obtain highly accurate formation tracking performance. The proposed control algorithm is composed of a baseline controller and an integrator-augmented robust adaptive controller, which can efficiently deal with both matched and mismatched formation aerodynamic effects and external disturbances. The major advantage of the proposed design is that it can achieve at least ultimate bounded tracking control with certain transient performance guaranty. The efficiency and robustness of the proposed control design are eventually validated via numerical simulations of close formation flight at two different scenarios.

Study on the High-Speed and Close of the UVA Cooperative Formation Controller Design

Aiming at the high-speed flight of the UAVs cooperative formation, when a single UAV has occurred, need to exit the formation flight and be close or super close to form of the formation quickly. A fast close cooperative formation controller design method is proposed to make up for low the fighting robustness, and be shortcomings of timeliness poorly and analyze the dynamic characteristic of UAV formation flight. Taking the external factors known into consideration, setting up for the longitude maneuver of nonlinear thrust vector and unsteady aerodynamic model, according to the formation velocity, flat tail rudder angle and thrust vector and pitch angle velocity for corresponding input commend signals for the controller to research the dynamic characteristic of UAV formation flight. Meanwhile, the formation flight distance error is the convergence to a fixed value, and the stability of the cooperative formation flight is good. The simulation of results show that the controller can effectively improve the speed of the close or super close to formation, and maintain the stability of the formation flight, which provides a method of the close or super close formation flight controller design.

Close formation flight of swarm unmanned aerial vehicles via metric-distance brain storm optimization

Close formation flight of swarm unmanned aerial vehicles (UAVs) has drawn much attention from scholars due to its significant importance in many aspects. In this paper, we focus on an advanced controller design for swarm UAV close formation based on a novel bio-inspired algorithm, i.e., metric-distance brain storm optimization (MDBSO). The proposed method utilizes the brain storm optimization (BSO) which has been extensively adopted in complicated systems with great performances and modifies its basic operators to formulate the formation flight controller design. The original clustering operator in BSO is replaced by a fresh clustering method based on metric distances, while the individual updating operator utilizes Levy distribution to extend search steps to fit into the metric searching regions. Then the proposed algorithm is applied to optimize the benchmark controller in swarm UAV close formation to enhance the tracking performances under complicated circumstances. Simulation results demonstrate that our approach is more superior in stable configuration of swarm UAV close formations by comparing with several generic methods.

Safe control of trailing UAV in close formation flight against actuator fault and wake vortex effect

In the close formation flight, the wake vortex induced by the leading aircraft will have adverse effects on the safe flight of the trailing unmanned aerial vehicle (UAV). Hence, this paper investigates a difficult problem of safe control for the trailing UAV against actuator faults, input saturation, and wake vortex effect. By using disturbance observers, external wake vortex, disturbances, and internal actuator faults are estimated. Then, with the help of estimated knowledge of disturbance, backstepping control laws are developed for the longitudinal dynamics and the lateral-directional dynamics, respectively. One of the key features of the proposed strategy is that, the inherent problem, i.e., “explosion of complexity” in conventional backstepping control, is solved by the presented dynamic surface control scheme. Another key feature is that external wake vortex, disturbances, and internal actuator faults, input saturation are simultaneously considered. It is shown by Lyapunov stability analysis that the closed-loop system is uniformly ultimately bounded with safety requirements guaranteed even in the presence of wake vortex and actuator faults. The effectiveness of the proposed approach is further validated by simulation results.