Dynamic Control Design for UAV Formation Tracking with Time Delays

This paper proposes a method of unmanned aerial vehicle (UAV) formation with connecting devices to take advantage of the aerodynamic advantages of the UAV fleet during close range formation flight. By combining the theory of multi-rigid-body system with the traditional six-degree-of-freedom equations of aircraft, a multi-rigid-body dynamics model of the connected UAV formation is established, which can describe the dynamic characteristics of the UAV formation when the formation changes. On this basis, the attitude control system of the UAV formation consisting of UAVs with only one control surface is designed, and the full-state non-linear numerical simulation model of the UAV formation is built in Simulink. The simulation results validate the rationality of the modeling method, and show that the attitude control system designed can effectively deal with the difficulties caused by the coupling of longitudinal and lateral controls and the complex aerodynamic forces of UAV formation.

This paper analyzes the motion capability of multiple fixed-wing unmanned aerial vehicle (UAV) formations by taking speed and heading rate constraints of individual UAVs into account. Unlike most of the existing literature investigating multi-UAV formation flying problems, which mainly focus on planner/controller design in order to achieve desired configurations, this paper aims at providing a quantitative description of the UAV formation maneuverability, which can serve as a metric for evaluating formation trajectory plans. Three common formations, namely perfect rigid formation, semiperfect rigid formation, and flexible formation are considered in this paper. Motion capabilities of these formations are analyzed in terms of turning performance. In particular, the feasible set of the formation heading rate is employed as the evaluation metric, based on which the relationships among these three formations are discussed. It has been proven that perfect rigid formation suffers from a rather limited mobility, while flexible formation has the largest feasible set of the formation heading rate in some situations. An interesting finding of this paper is that flexible formation is not necessarily more agile than semiperfect rigid formation with the same formation width, due to the special stall speed constraint of fixed-wing UAVs. Besides rigorous mathematical derivations, simulations have also been performed to further support the theoretical analyses.

This manuscript presents an application of the multi-layer control scheme to guide a formation of unmanned aerial vehicles (UAV) in positioning and trajectory tracking missions. In such case, each part of the formation control problem is dealt by an individual layer, which is independent module dealing with a specific part of the navigation problem. These layers are responsible to generate the desired path of the formation, to provide the desired posture of the robots, and to establish the control signal of each robot to reach their desired positions. The formation controller here introduced is able to coordinate the robots to the desired formation, including the possibility of time-varying position and/or shape, while a nonlinear underactuated controller previously proposed is responsible to guide the UAVs to their desired positions. The stability analysis of the closed-loop system is demonstrated in the sense of Lyapunov, resulting that the formation errors are ultimately bounded. In the sequel, a strategy to guide a formation of multiple unmanned aerial vehicles (MUAV) to accomplish positioning and trajectory-tracking tasks is also proposed. Delaunay triangulation is here used to split the platoon of UAVs in N-triangles, which are individually guided by the multi-layer control scheme (MLCS). The advantage of the MLCS in such proposal is the maintenance of the the Jacobian matrix order, regardless of the number of robots in the formation, which reduces the complexity of the control problem. Simulation results demonstrate the ability to accomplish the aforementioned tasks, thus validating the proposal.

This paper proposes an algorithm for cooperative guidance of an unmanned aerial vehicle (UAV) formation following a set of waypoints. Waypoints are linked by straight lines to form a sequence, which effectively tasks the formation to cooperatively follow a rectilinear path between these points. Unlike in earlier known papers, we propose a Fermat’s spiral rather than a circular arc as a fillet to smooth the trajectory. This is because a Fermat’s spiral has zero curvature at its origin, which helps avoid breaks in curvature observable when using straight lines and circular arcs. To make a UAV formation and to follow the path, we propose a novel guidance vector field that is direction- and magnitude-nonuniform. This is where the novelty of this paper lies, as it proposes the vector field method for following a Fermat’s spiral. Known studies used line-of-sight (LOS) guidance to that end. In that case, the UAV formation shapes itself using consensus-based coordination topology, i.e. the group has no leader. To test the algorithm for cooperative waypoint following when smoothing is provided by fillets, we utilized complete nonlinear models of two fixed-wing UAVs, each equipped with a tuned autopilot. Numerical simulation shows the proposed approach efficient.

The traditional leader-follower Unmanned Aerial Vehicle (UAV) formation cooperative positioning (CP) algorithm, based on relative ranging, requires at least four leader UAV positions to be known accurately, using relative distance with leader UAVs to achieve the unknown position follower UAV’s high-precision positioning. When the number of the known position leader UAVs is limited, the traditional CP algorithm is not applicable. Aiming at the minimum cooperative unit, which consists of a known position leader UAV and an unknown position follower UAV, this paper proposes a CP method based on the follower UAV’s moving vector. Considering the follower UAV can only acquire the single distance with the leader UAV at each distance-sampling period, it is difficult to determine the follower UAV’s spatial location. The follower UAV’s moving vector is used to construct position observation of the follower UAV’s inertial navigation system (INS). High-precision positioning is achieved by combining the follower UAV’s moving vector. In the process of CP, the leader UAV obtains a high-precision position by an INS/Global Positioning System (GPS) loosely integrated navigation system and transmits its position information to the follower UAV. Based on accurate modeling of the follower UAV’s INS, the position, velocity and heading observation equation of the follower UAV’s INS are constructed. The improved extended Kalman filtering is designed to estimate the state vector to improve the follower UAV’s positioning accuracy. In addition, considering that the datalink system based on radio signals may be interfered with by the external environment, it is difficult for the follower UAV to obtain relative distance information from the leader UAV in real time. In this paper, the availability of the relative distance information is judged by a two-state Markov chain. Finally, a real flight test is conducted to validate the performance of the proposed algorithm.

Unmanned Aerial Vehicle (UAV) is a new type of flying work tool with the ability to execute tasks. Under strong electromagnetic interference, communication can be carried out by ultraviolet (UV) .Ultraviolet Communication was a communication mode used 200nm~280nm wavelength ultraviolet light as an information carrier. It has the advantage of all-weather operations, non-line-of-sight (NLOS) communication and strong anti- interference. When performing a mission, the UAV formation usually needs to form a fixed formation during the flight to ensure the stability of the link communication network. Moreover, due to the limited energy carried by the UAV, the energy consumption of UAV network should be reduced as much as possible on the basis of maintaining communication in order to maximize the flight time of UAV. The UAVs form persistent formation that need to know the location information of all the UAVs in the formation. When the GPS is not working properly, a kind of two dimensional (2D) localization algorithm which based on the wireless UV ranging method provides relative location information for the UAV formation. This paper proposes a persistent formation generation algorithm for the location information of UAVs that are not shared, the algorithm enables the UAV formation to generate a stable network topology with the least communication links and low energy consumption.

The development of hierarchical structures of unmanned aerial vehicles (UAVs) increases the efficiency of unmanned aerial systems. The grouping of UAVs increases the region of recognition or force of assault. Achieving these requirements is possible through a UAV formation. The UAVs in the formation must be controlled and managed by a commander, but the commander cannot control individual UAVs. The UAVs within the formation have assigned specific individual tasks, so is possible to achieve the flight of the formation with minimum collisions between UAVs and maximized equipment utilization. This paper aims to present a method of formation control for multiple UAVs that allows dynamic changes in the constellations of UAVs. The article includes the results of tests and research conducted in real-world conditions involving a formation capable of adapting its configuration. The results are presented as an element of research for the autonomy swarm, which can be controlled by one pilot/operator. The control of a swarm consisting of many UAVs (several hundred) by one person is now a current problem. The article presents a fragment of research work on high-autonomy UAV swarms. Here is presented a field test that focuses on UAV constellation control.

A new consensus theory-based method for formation control and obstacle avoidance of UAVs

For an Unmanned Aerial Vehicle (UAV) formation in “leader-follower” mode, a bran-new concept of nonlinear elastic distance vector is proposed, which helps achieve much more excellent control effect. Based on the nonlinear elastic distance vector, through a big mountain of mathematical work the mathematical model of UAV formation flight is built and linearized skillfully. A new model of UAV formation flight is obtained, which has distinct physical meaning and simple form. And on this basis, by introducing some simplification and symmetry of feedback gain, a fire-new high-efficiency distributed controller of elastic formation is designed. Even better, it expends munch small control cost while providing such better control effect. Then the stability of the controller is proved subtly and a very important theorem offers sufficient conditions for the stability of the model is proposed. Simulation results show that controller can keep the formation much more effectively. In addition, the control quantity is only related to two elements: One is the speed of controlled vehicle itself, the other is the relative distance between controlled vehicle and its neighbor. For this reason, the control problem becomes more simple.

This paper investigates a pure azimuth passive positioning model for unmanned aerial vehicle (UAV) formations, with a focus on circular formations as an example. The model utilizes the polar coordinate system and geometric principles to derive formulas for calculating the azimuth angle, distance angle, and ideal position coordinates of UAVs. It also accounts for receiving errors and proposes a positioning adjustment method to address deviations from ideal positions. Mathematical induction is employed to unify the relationships between variables under different conditions. The developed model enables the extraction of azimuth angles from received signals and calculates UAV positions within the polar coordinate system. Results demonstrate the model's effectiveness in determining the precise location of UAVs in formations, even under non-ideal conditions. This work fills a gap in the field of UAV formation positioning, providing a theoretical foundation for accurate and reliable positioning. Furthermore, the proposed approach paves the way for future improvements in real-time compensation mechanisms for dynamic errors, with potential applications in diverse UAV formation configurations.

Local and asymmetrical potential field approach to leader tracking problem in rigid formations of fixed-wing UAVs

This paper addressed a well documented open problem on the asymptotic flight-stability of the closed-loop system in the process of the windy field for a three fixed-wing unmanned aerial vehicles (UAVs) formation. The problem of stability can be converted to the analysis of dynamic response and steady-state error. The robust control compared with phononic crystal control method, it can realize the high speed and close cooperative formation of precision combat. Adding phononic crystal is not only capable of reducing the body vibration and steady-state tracking error, but also owns better robustness. The horizontal dynamic analysis of the formation of UAVs is carried out in the presence of external unknown factors. Then, an “integrated” controller is designed to control leader’s speed so that “follower” can track the “leader” in the case of decoupling, while maintaining the consensus of relative speed. The simulation results show that the “integrated” control method integrates the advantages of robust control and phononic crystal vibration attenuation.

A novel fault-tolerant communication topology management method for the leader–follower unmanned aerial vehicle (UAV) formation is proposed to minimize the formation communication cost while keeping the formation shape, even in the case of communication faults during the formation flight. This method is based on Edmonds’ algorithm for the minimum cost arborescence problem in graph theory. When a formation shape is given before the formation flight, this method can get the optimal initial communication topology with the minimum formation communication cost for keeping the formation shape. When some communication faults occur during the formation flight, which will cause the formation shape cannot be kept, this method can reconfigure the communication topology in time to guarantee the safety of all UAVs and recover the formation shape, and then it can reoptimize the communication topology by UAV position reconfiguration in the formation shape to minimize the formation communication cost for continuously keeping the formation shape. The effectiveness of this method is demonstrated through several simulation experiments.

In this study, the time‐varying formation control problem for the second‐order discrete‐time multi‐agent systems is investigated, where both the non‐uniform communication time‐delays and switching topology are taken into account. A linear discrete‐time formation protocol is developed based on the neighbouring relative position and velocity information. Using the state transformation method and properties of the stochastic matrix, the formation feasibility condition is given and sufficient conditions for the discrete‐time multi‐agent systems to accomplish the time‐varying formation are established. An unmanned aerial vehicles (UAVs) formation experiment platform is constructed. Using four quadrotor UAVs, UAV formation flying experiments are performed to verify the effectiveness and reliability of the discrete‐time formation protocol. The experimental results show that the theoretical results can be used to deal with the time‐varying formation control problem for multiple UAVs system with communication delays and switching topology.

Formation coordination can improve the overall performance of unmanned aerial vehicle (UAV) systems, so it is important to realize coordinated formation control. To solve the problems of ineffective internal collision avoidance and communication distance maintenance in existing formation control methods, a UAV formation control algorithm based on an improved artificial potential field and consensus is proposed. First, an improved artificial potential field obstacle avoidance method is used to solve the problems of collision avoidance and communication distance maintenance within the formation by setting a communication risk zone and a collision risk zone and by defining the dynamic adjustment parameters of the inter‐UAV virtual force to improve the traditional artificial potential field method. Second, a time integrating factor is introduced, and an improved consensus‐based formation control method is employed to overcome the problem of the artificial potential field method falling into the local optimum easily. Simulation experiments were designed to analyse the trends of the UAV formation motion trajectory, inter‐UAV relative distance, attitude, and formation time. The analysis results show that the method can make the UAV formation consistent with the flight trajectory of the intended formation, solving the problems of collision avoidance and communication distance maintenance within the UAV formation.