Follower Unmanned Aerial Vehicles Research Articles

Formation flight of fixed-wing UAV swarms: A group-based hierarchical approach

This paper investigates a formation control problem of fixed-wing Unmanned Aerial Vehicle (UAV) swarms. A group-based hierarchical architecture is established among the UAVs, which decomposes all the UAVs into several distinct and non-overlapping groups. In each group, the UAVs form hierarchies with one UAV selected as the group leader. All group leaders execute coordinated path following to cooperatively handle the mission process among different groups, and the remaining followers track their direct leaders to achieve the inner-group coordination. More specifically, for a group leader, a virtual target moving along its desired path is assigned for the UAV, and an updating law is proposed to coordinate all the group leaders’ virtual targets; for a follower UAV, the distributed leader-following formation control law is proposed to make the follower’s heading angle coincide with its direct leader, while keeping the desired relative position with respect to its direct leader. The proposed control law guarantees the globally asymptotic stability of the whole closed-loop swarm system under the control input constraints of fixed-wing UAVs. Theoretical proofs and numerical simulations are provided, which corroborate the effectiveness of the proposed method.

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.

Distributed adaptive fractional‐order fault‐tolerant cooperative control of networked unmanned aerial vehicles via fuzzy neural networks

This study presents a distributed fault-tolerant cooperative control (FTCC) strategy to achieve the attitude synchronisation tracking control of networked unmanned aerial vehicles (UAVs) in the presence of actuator faults and model uncertainties. By utilising the fuzzy neural networks (FNNs), the unknown non-linear terms induced by actuator faults and model uncertainties are estimated as lumped uncertainties. A set of distributed sliding-mode estimators (DSMEs) is then employed to estimate the leader UAV's attitudes for the follower UAVs via a distributed communication network. Based on the estimated knowledge from FNNs and DSMEs, a group of distributed FTCC laws is developed for all follower UAVs by using the fractional-order calculus. It is proven that with the proposed control scheme, all follower UAVs can track the attitudes of the leader UAV and the tracking errors are uniformly ultimately bounded even when a portion of networked UAVs encounters multiple actuator faults. Comparative simulation results are presented to demonstrate the effectiveness of the proposed approach.

Distributed Fault-Tolerant Cooperative Control for Multi-UAVs Under Actuator Fault and Input Saturation

This paper investigates a difficult problem of distributed fault-tolerant cooperative control for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and input saturation. To eliminate the “explosion of complexity” in the traditional backstepping architecture, the dynamic surface control is utilized to construct the distributed fault-tolerant control scheme. Moreover, by using the disturbance observer technique, actuator faults and external disturbances are estimated as lumped uncertainties. Furthermore, to reduce the adverse influence caused by the control input saturation of UAVs, auxiliary dynamic systems are introduced to regulate the control signals when the input signals are saturated for a long time. The key feature is that the proposed fault-tolerant cooperative controller is designed based on the local information of neighboring UAVs and the factors including actuator faults, input saturation, and external disturbances are simultaneously addressed. It is shown by Lyapunov approach and graph theory that the synchronization tracking stability can be guaranteed and all follower UAVs can track the leader UAV. The effectiveness of the proposed control scheme is further validated by numerical simulation results.

Coordinated flight control of miniature fixed-wing UAV swarms: methods and experiments

In this paper, we present our recent advances in both theoretical methods and field experiments for the coordinated control of miniature fixed-wing unmanned aerial vehicle (UAV) swarms. We propose a multi-layered group-based architecture, which is modularized, mission-oriented, and can implement large-scale swarms. To accomplish the desired coordinated formation flight, we present a novel distributed coordinated-control scheme comprising a consensus-based circling rendezvous, a coordinated path-following control for the leader UAVs, and a leader-follower coordinated control for the follower UAVs. The current framework embeds a formation pattern reconfiguration technique. Moreover, we discuss two security solutions (inter-UAV collision avoidance and obstacle avoidance) in the swarm flight problem. The effectiveness of the proposed coordinated control methods was demonstrated in field experiments by deploying up to 21 fixed-wing UAVs.

UAV Group Formation Collision Avoidance Method Based on Second-Order Consensus Algorithm and Improved Artificial Potential Field

The problem of collision avoidance of an unmanned aerial vehicle (UAV) group is studied in this paper. A collision avoidance method of UAV group formation based on second-order consensus algorithm and improved artificial potential field is proposed. Based on the method, the UAV group can form a predetermined formation from any initial state and fly to the target position in normal flight, and can avoid collision according to the improved smooth artificial potential field method when encountering an obstacle. The UAV group adopts the “leader–follower” strategy, that is, the leader UAV is the controller and flies independently according to the mission requirements, while the follower UAV follows the leader UAV based on the second-order consensus algorithm and formations gradually form during the flight. Based on the second-order consensus algorithm, the UAV group can achieve formation maintenance easily and the Laplacian matrix used in the algorithm is symmetric for an undirected graph. In the process of obstacle avoidance, the improved artificial potential field method can solve the jitter problem that the traditional artificial potential field method causes for the UAV and avoids violent jitter. Finally, simulation experiments of two scenarios were designed to verify the collision avoidance effect and formation retention effect of static obstacles and dynamic obstacles while the two UAV groups fly in opposite symmetry in the dynamic obstacle scenario. The experimental results demonstrate the effectiveness of the proposed method.

Multivariable adaptive control based consensus flight control system for UAVs formation

Formation flight contributes to improving the attack, reconnaissance and survival ability of the multiple unmanned aerial vehicles (UAVs). This paper studies a multivariable adaptive control based consensus flight method for UAVs formation. A majority of existing research is focused on the leader-following consensus problem assuming that only the parameters of followers are uncertain. However, they do not consider the leader dynamic uncertainty and the unknown external disturbances. Therefore, this paper addresses the problem of the UAVs consensus flight control with parametric uncertainties and unknown external disturbances for both the leader and follower. A multivariable model reference adaptive control (MRAC) based consensus flight control scheme is designed for UAVs formation, which enables the follower UAV to track the leader UAV. The stability of the multivariable MRAC based consensus flight control system is analyzed. Simulation results show that the proposed adaptive consensus flight control scheme has stronger robustness and adaptivity than the fixed control scheme.

Drones Chasing Drones: Reinforcement Learning and Deep Search Area Proposal

Unmanned aerial vehicles (UAVs) are very popular and increasingly used in different applications. Today, the use of multiple UAVs and UAV swarms are attracting more interest from the research community, leading to the exploration of topics such as UAV cooperation, multi-drone autonomous navigation, etc. In this work, we propose two approaches for UAV pursuit-evasion. The first approach uses deep reinforcement learning to predict the actions to apply to the follower UAV to keep track of the target UAV. The second approach uses a deep object detector and a search area proposal (SAP) to predict the position of the target UAV in the next frame for tracking purposes. The two approaches are promising and lead to a higher tracking accuracy with an intersection over union (IoU) above the selected threshold. We also show that the deep SAP-based approach improves the detection of distant objects that cover small areas in the image. The efficiency of the proposed algorithms is demonstrated in outdoor tracking scenarios using real UAVs.

Adaptive finite-time reconfiguration control of unmanned aerial vehicles with a moving leader

This paper investigates adaptive reconfiguration control problem for unmanned aerial vehicle (UAV) helicopter system with a moving leader. Only part of UAV helicopter is informed to have access to the leader’s position. The six degree-of-freedom UAV system is composed of position outer loop and attitude inner loop. In this paper, we introduce a new fully distributed, finite-time reconfiguration controller and the problem of inter-UAVs collision avoidance was solved using potential energy function approach, extending the asymptotical formation controller without collision avoidance from the literature. The distinctive feature of our algorithm from existing works is that the novel formation reconfiguration controller can achieve finite-time, collision avoidance and fully distributed formation only based on relative positions between UAV and its adjacents. It means that the control algorithm is independent of any global information that requires to be calculated by each follower UAV. The system uncertainties are estimated by radial basis function neural network in practical finite time. Simulation results are shown to demonstrate the efficiency of the designed strategy.

Time-Varying Formation Tracking for UAV Swarm Systems With Switching Directed Topologies

Time-varying formation tracking (TVFT) control problems for a team of unmanned aerial vehicles (UAVs) with switching and directed interaction topologies are investigated, where the follower UAVs realize a given time-varying formation while tracking the leader UAV. A TVFT control protocol is firstly constructed utilizing local neighboring information, where the information of the leader UAV is only available to partial followers and the neighborhood can be switching. An algorithm composed of four steps is provided to design the TVFT protocol. It is proved that the UAV swarm system can realize the TVFT using the designed protocol if the dwell time for the switching directed topologies is larger than a fixed threshold and the TVFT feasibility condition is satisfied. Based on the ultrawideband positioning technology, a quadrotor UAV formation control platform with four quadrotor UAVs is given. The obtained theoretical results are applied to solve the target enclosing problems of the UAV swarm systems. A flying experiment for three follower quadrotor UAVs to enclose a leader quadrotor UAV is carried out to verify the effectiveness of the presented results.

Fault-Tolerant Cooperative Control for Multiple UAVs Based on UDE and Model Following SMC

This paper presents a fault-tolerant cooperative control (FTCC) design approach with application to multiple unmanned aerial vehicles (UAVs), where the outer-loop control and the inner-loop control are designed. By virtue of a proportional control, the outer-loop of the follower UAV is able to generate reference commands. Moreover, within the proposed FTCC context, the inner-loop control is designed by resorting to the uncertainty and disturbance estimator (UDE) and model following sliding mode control (SMC) techniques, such that the deleterious effects of failed actuators can be counteracted and the safety of the cooperative flight can be ensured. The effectiveness of the developed FTCC scheme is illustrated by the numerical simulations of UAVs cooperative flight.

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

Time-Varying Formation Tracking for Second-Order Multi-Agent Systems Subjected to Switching Topologies With Application to Quadrotor Formation Flying

Time-varying formation tracking analysis and design problems for second-order Multi-Agent systems with switching interaction topologies are studied, where the states of the followers form a predefined time-varying formation while tracking the state of the leader. A formation tracking protocol is constructed based on the relative information of the neighboring agents. Necessary and sufficient conditions for Multi-Agent systems with switching interaction topologies to achieve time-varying formation tracking are proposed together with the formation tracking feasibility constraint based on the graph theory. An approach to design the formation tracking protocol is proposed by solving an algebraic Riccati equation, and the stability of the proposed approach is proved using the common Lyapunov stability theory. The obtained results are applied to solve the target enclosing problem of a multiquadrotor unmanned aerial vehicle (UAV) system consisting of one leader (target) quadrotor UAV and three follower quadrotor UAVs. A numerical simulation and an outdoor experiment are presented to demonstrate the effectiveness of the theoretical results.

Fault-tolerant cooperative control for multiple UAVs based on sliding mode techniques

This paper proposes a fault-tolerant cooperative control (FTCC) design approach for multiple unmanned aerial vehicles (UAVs), where the outer-loop control and the inner-loop fault accommodation are explicitly considered. The reference signals for the inner-loop of the follower UAV can be directly produced by resorting to a proportional control. In the presence of actuator faults, the estimation of the fault information can be completed within finite time. Moreover, the control of the inner-loop is reconfigured based on the fault information adaptation and sliding mode techniques, such that the deleterious effects due to failed actuators can be compensated within finite time. Simulations of UAV cooperative flight are conducted to illustrate the effectiveness of this FTCC scheme.

Fault-tolerant communication topology management based on minimum cost arborescence for leader–follower UAV formation under communication faults

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.

Chaotic Biogeography-Based Optimization Approach to Receding Horizon Control for Multiple UAVs Formation Flight

In this paper, we proposed a Receding Horizon Control (RHC) scheme which converts multiple Unmanned Aerial Vehicle (UAVs) formation flight problem to a sequence of online optimization problems over a planning horizon. A novel Chaotic Biogeography-Based Optimization (CBBO) approach is presented to find the optimal control inputs for the follower UAVs to maintain coordinated flight with the minimum input cost in each of the planning horizons. Series of simulation results verified the feasibility and effectiveness of our presented approach.

Hybrid formation control of the Unmanned Aerial Vehicles

An essential issue in the formation control of Unmanned Aerial Vehicles (UAVs) is to design a reliable controller in their path planner level to handle all interactions between the continuous dynamics of the system and inherent discrete nature of the decision making unit, which has been embedded to coordinate the control submodules. In this paper, we have proposed a new approach of hybrid supervisory control of UAVs for a two-dimensional leader follower formation scenario. The approach is able to comprehensively capture internal relations between the path planner dynamics and the decision making unit of the UAVs. To design such a hybrid supervisory controller for the formation problem, we have introduced a new method of abstraction, based on polar partitioning of the state space. Furthermore, we have utilized the properties of multi-affine vector fields over the polar partitioned space. Within this framework, we design a modular decentralized supervisor in the path planner level of the UAVs to achieve two major goals: first, reaching the formation and second, keeping the formation. In addition, an inter-collision avoidance mechanism has been considered in the controller structure. The approach is robust against uncertainty in the initial state of the system, in the sense that it can bring the follower UAV to the desired position, starting from any arbitrary initial position inside the control horizon. Moreover, the velocity bounds are applied through the design procedure so that the generated velocity references can be given to the lower level of the control hierarchy, as the references to be followed.

Nonlinear Control for Reconfiguration of Unmanned-Aerial-Vehicle Formation

The design of a nonlinear controller to reconfigure a formation of a group of unmanned aerial vehicles (UAVs) is described. Reconfiguration of the formation might be needed to maintain the efficiency of the formation. Nonlinear six-degree-of-freedom, rigid-body, equations of motion developed in the virtual leader (VL)’s frame are used to model the UAVs in the formation. The formulation of the formation flight in VL frame enables the formationkeeping and formation reconfiguration to be treated in the same framework. The nonlinear equations of motion contain the wind effect terms and their time derivatives to represent the aerodynamic coupling involved in close formation flight. These wind terms are obtained by using an averaging technique that computes the effective induced wind components and wind gradients in the UAV’s body frame. Dynamics of the engine and the actuators are also included in the study. An algorithm that generates a safe and feasible trajectory, given the current position and the position to go to, has been developed. A combination of integral control, optimal LQR design, and nonlinear state feedback linearization is used in the design of the position-tracking controller. Simulation results demonstrate that the controller is capable of producing a smooth reconfiguration without using the information of the vortex-induced wind effects on the follower UAV.