Event-triggered leader-following formation control for multi-agent systems under communication faults: application to a fleet of unmanned aerial vehicles

The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems(MASs)under communication faults.All the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the agents.Linear matrix inequalities(LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization error.Based on the closed-loop system,an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy consumption.The proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles(UAVs)under communication faults.A comparison between a state-of-the-art technique and the proposed technique has been provided,demonstrating the performance improvement brought by the proposed approach.

Fault Tolerant Control Scheme Design for Formation Flight Control System of Multiple Unmanned Aerial Vehicles

The command tracking problem of formation flight control system(FFCS)for multiple unmanned aerial vehicles(UAVs)with sensor faults is discussed.And the objective of the addressed control problem is to design a robust fault tolerant tracking controller such that,for the disturbances and sensor faults,the closed-loop system is asymptotically stable with a given disturbance attenuation level.A robust fault tolerant tracking control scheme,combining an observer with H∞ performance,is proposed.Furthermore,it is proved that the designed controller can guarantee asymptotic stability of FFCS despite sensor faults.Finally,a simulation of two UAV formations is employed to demonstrate the effectiveness of the proposed approach.

Joint waveform selection and power allocation algorithm in manned/unmanned aerial vehicle hybrid swarm based on chance-constraint programming

In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.

Trophallaxis network control approach to formation flight of multiple unmanned aerial vehicles

A novel network control method based on trophaUaxis mechanism is applied to the formation flight problem for multiple un- manned aerial vehicles （UAVs）. Firstly, the multiple UAVs formation flight system based on trophallaxis network control is given. Then, the model of leader-follower formation flight with a virtual leader based on trophallaxis network control is pre- sented, and the influence of time delays on the network performance is analyzed. A particle swarm optimization （PSO）-based formation controller is proposed for solving the leader-follower formation flight system. The proposed method is applied to five UAVs for achieving a ＇V＇ formation, and a series of experimental results show its feasibility and validity. The proposed control algorithm is also a promising control strategy for formation flight of multiple unmanned underwater vehicles （UUVs）, unmanned ground vehicles （UGVs）, missiles and satellites.

Unmanned Aerial Vehicle Formation Inspired by Bird Flocking and Foraging Behavior

This paper considers a multiple unmanned aerial vehicles （UAV） formation problem and proposes a new method inspired by bird flocking and foraging behavior. A bidirectional communication network, a navigator based on bird foraging behavior, a controller based on bird interaction and a movement switch are developed for multi-UAV formation. Lyapunov＇s second method and mechanical energy method are adopted for stability analysis. Parameters of the controller are optimized by Levy-flight based pigeon inspired optimization （Levy-PIO）. Patrol missions along a square and an S shaped trajectory are designed to test this formation method. Simula- tions prove that the bird flocking and foraging strategy can accomplish the mission and obtain satisfying performance.

Robust leaderless time-varying formation control for unmanned aerial vehicle swarm system with Lipschitz nonlinear dynamics and directed switching topologies

This paper tackles the robust leaderless Time-Varying Formation(TVF)control problem for the Unmanned Aerial Vehicle(UAV)swarm system with Lipschitz nonlinear dynamics,external disturbances and directed switching topologies.In comparison with the previous achievements on formation control problems,the UAV swarm system with Lipschitz nonlinear dynamics can accomplish the pre-designed TVF while tracking a pre-given trajectory which is produced by a virtual leader UAV in the presence of external disturbances.Firstly,by applying the consensus theory,a TVF controller is developed with the local neighborhood status information,the errors of real time status of all UAVs,the expected formation configuration and the pre-given trajectory under directed switching topologies.Secondly,through a certain matrix variable substitution,the UAV swarm system formation control issue is transformed into a lower dimensional asymptotically stable control issue.Thirdly,by introducing the minimum dwell time,the design steps of formation control algorithm are further acquired.In the meantime,the stability of the UAV swarm system is analyzed through the construction of a piecewise continuous Lyapunov functional and via the Linear Matrix Inequalities(LMIs)method.Finally,the comparison results of a numerical simulation are elaborated to verify the validity of the proposed approach.

Semi-global leader-following consensus-based formation flight of unmanned aerial vehicles

In this paper,we investigate a formation control problem of multi-agent systems(specifically a group of unmanned aerial vehicles)based on a semi-global leader-following consensus approach with both the leader and the followers subject to input saturation.Utilizing the low gain feedback design technique,a distributed static control protocol and a distributed adaptive control protocol are constructed.The former solves the problem under an assumption that the communication network is undirected,and it depends on the global information of the graph.For the latter,we relax the undirected graph to directed graph.Moreover,an adaptive updating gain is designed to avoid using the global information of the communication network.It is shown that the consensus protocols can solve the semi-global leader-following consensus problem if the leader agent is globally reachable.The results are verified successfully by both simulation and real flight tests.

Distributed bearing-based formation control of unmanned aerial vehicle swarm via global orientation estimation

Most existing formation control approaches for Unmanned Aerial Vehicle(UAV)swarm assume that global position and global coordinate frame are directly available for each agent.To extend the application domain,this paper proposes a distributed bearing-based formation control scheme,without any reliance on global position or global coordinate frame.The interactions among UAVs are described by a directed topology with two-leader structure.To address the issue of unavailable global coordinate frame,we first present a distributed orientation estimation law for each UAV to determine its orientation under the coordinate frame of the first leader.Based on the orientation estimation,we then design a bearing-based formation control law to globally asymptotically track target moving formations.Finally,simulation results are provided to validate the proposed method,which show that the translation,scale and orientation of the formation can be flexibly controlled via two leaders.

Affine formation tracking control of unmanned aerial vehicles

The affine formation tracking problem for fixed-wing unmanned aerial vehicles(UAVs)is considered in this paper,where fixed-wing UAVs are modeled as unicycle-type agents with asymmetrical speed constraints.A group of UAVs are required to generate and track a time-varying target formation obtained by affinely transforming a nominal formation.To handle this problem,a distributed control law based on stress matrix is proposed under the leader-follower control scheme.It is proved,theoretically,that followers can converge to the desired positions and achieve affine transformations while tracking diverse trajectories.Furthermore,a saturated control strategy is proposed to meet the speed constraints of fixed-wing UAVs,and numerical simulations are executed to verify the effectiveness of our proposed affine formation tracking control strategy in improving maneuverability.

Nonlinear tight formation control of multiple UAVs based on model predictive control

A tight formation of unmanned aerial vehicles(UAVs) has many advantages, such as fuel saving and deceiving enemy radar during battlefield entry. As a result, research on UAVs in close formation has received much attention, and the controller design for formation holding has become a popular research topic in the control field. However, there are many unknown disturbances in tight formation, and the tail aircraft is disturbed by the wake. This paper establishes a mathematical model of wake vortices for tail aircraft that considers uncertainty and strong interference. Two UAVs are simulated by Computational Fluid Dynamics software, followed by the design of a semiphysical simulation model predictive control(MPC) scheme that suppresses uncertainty and interference sufficiently to enable the tail aircraft to accurately track the lead aircraft and maintain a stable, tight formation. The tight formation controller is verified by numerical simulation and semiphysical simulation. The results show that the designed controller has an excellent control effect in the case of disturbance caused by the wake vortex.

Nonlinear direct data-driven control for UAV formation flight system

This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.

A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles

This paper presents the recent developments in Fault-Tolerant Cooperative Control(FTCC)of multiple unmanned aerial vehicles(multi-UAVs).To facilitate the analyses of FTCC methods for multi-UAVs.the formation control strategies under fault-free flight conditions of multi-UAVs are first summarized and analyzed,including the leader-following,behavior-based,virtual structure,collision avoidance,algebraic graph-based,and close formation control methods,which are viewed as the cooperative control methods for multi-UAVs at the pre-fault stage.Then,by considering the various faults encountered by the multi-UAVs,the state-of-the-art developments on individual,leader-following,and distributed FTCC schemes for multi-UAVs are reviewed in detail.Finally,conclusions and challenging issues towards future developments are presented.

Flocking control of a fleet of unmanned aerial vehicles

Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters （UQHs）. Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives （like forest/pipeline surveillance） by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work： first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.

MAV/UAV task coalition phased-formation method

The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.

Three-dimensional formation keeping of multi-UAV based on consensus

Consensus is an emerging technique using neighbor-to-neighbor interaction to generate steering commands for cooperative control of multiple vehicles. A three-dimensional formation keeping strategy for multiple unmanned aerial vehicles(multi-UAV) is proposed based on consensus, aiming at maintaining a specified geometric configuration. A formation control algorithm with guidance and corresponding flight controllers is given, managing position and attitude, respectively. In order to follow a three-dimensional predefined flight path, by introducing the tracking orders as reference states into the consensus, the formation control algorithm is designed, following the predefined flight path and maintaining geometric configuration simultaneously. The flight controllers are constructed by nonlinear dynamic inverse, including attitude design and velocity design. With the whole system composed of a nonlinear six-degree-of-freedom UAV model, the formation control algorithm and the flight controllers, the formation keeping strategy is closed loop and with full states. In simulation, three-dimensional formation flight demonstrates the feasibility and effectiveness of the proposed strategy.

Multiple UAVs cooperative formation forming control based on back-stepping-like approach

To ensure multiple unmanned aerial vehicles （UAVs）reach stable formation quickly, a cooperative guidance law basedon the back-stepping-like approach is designed in this paper.Adopting the guidance mechanism of virtue leader vehicle, thedynamic equation of tracking errors for each UAV is built. Thecommunication interactive relationships are described based ongraph theory, and the guidance law for formation reaching is ob-tained by the back-stepping-like approach. The formation stabilityis analyzed by constructing an appropriate Lyapunov function. Thesimulation results have shown that this guidance and control lawcan make each UAV converge to the trajectory of the virtue leaderultimately, and has the quicker rate of convergence and lowertracking error.

Path planning for UAVs formation reconfiguration based on Dubins trajectory

Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance,search,attack and rescue missions.Formation reconfiguration was inevitable during the flight when the mission was adjusted or the environment varied.Taking the typical formation reconfiguration from a triangular penetrating formation to a circular tracking formation for example,a path planning method based on Dubins trajectory and particle swarm optimization(PSO)algorithm is presented in this paper.The mathematic model of multiple UAVs formation reconfiguration was built firstly.According to the kinematic model of aerial vehicles,a process of dimensionality reduction was carried out to simplify the model based on Dubins trajectory.The PSO algorithm was adopted to resolve the optimization problem of formation reconfiguration path planning.Finally,the simulation and vehicles flight experiment are executed.Results show that the path planning method based on the Dubins trajectory and the PSO algorithm can generate feasible paths for vehicles on time,to guarantee the rapidity and effectiveness of formation reconfigurations.Furthermore,from the simulation results,the method is universal and could be extended easily to the path planning problem for different kinds of formation reconfigurations.

Adaptive distributed formation maintenance for multiple UAVs:Exploiting proximity behavior observations

The formation maintenance of multiple unmanned aerial vehicles(UAVs)based on proximity behavior is explored in this study.Individual decision-making is conducted according to the expected UAV formation structure and the position,velocity,and attitude information of other UAVs in the azimuth area.This resolves problems wherein nodes are necessarily strongly connected and communication is strictly consistent under the traditional distributed formation control method.An adaptive distributed formation flight strategy is established for multiple UAVs by exploiting proximity behavior observations,which remedies the poor flexibility in distributed formation.This technique ensures consistent position and attitude among UAVs.In the proposed method,the azimuth area relative to the UAV itself is established to capture the state information of proximal UAVs.The dependency degree factor is introduced to state update equation based on proximity behavior.Finally,the formation position,speed,and attitude errors are used to form an adaptive dynamic adjustment strategy.Simulations are conducted to demonstrate the effectiveness and robustness of the theoretical results,thus validating the effectiveness of the proposed method.

Dynamic affine formation control of networked under-actuated quad-rotor UAVs with three-dimensional patterns

This paper focuses on the solution to the dynamic affine formation control problem for multiple networked underactuated quad-rotor unmanned aerial vehicles(UAVs)to achieve a configuration that preserves collinearity and ratios of distances for a target configuration.In particular,it is investigated that the quad-rotor UAVs are steered to track a reference linear velocity while maintaining a desired three-dimensional target formation.Firstly,by integrating the properties of the affine transformation and the stress matrix,the design of the target formation is convenient and applicable for various three-dimensional geometric patterns.Secondly,a distributed control method is proposed under a hierarchical framework.By introducing an intermediary control input for each quad-rotor UAV in the position loop,the necessary thrust input and the desired attitude are extracted.In the attitude loop,the desired attitude represented by the unit quaternion is tracked by the designed torque input.Both conditions of linear velocity unavailability and mutual collision avoidance are also tackled.In terms of Lyapunov theory,it is prooved that the overall closed-loop error system is asymptotically stable.Finally,two illustrative examples are simulated to validate the effectiveness of the proposed theoretical results.

A modified consensus algorithm for multi-UAV formations based on pigeon-inspired optimization with a slow diving strategy

This paper considers the formation control problem for a group of unmanned aerial vehicles( UAVs)employing consensus with different optimizers. A group of UAVs can never accomplish difficult tasks without formation because if disordered they do not work any better than a single vehicle,and a single vehicle is limited by its undeveloped intelligence and insufficient load. Among the many formation methods,consensus has attracted much attention because of its effectiveness and simplicity. However,at the beginning of convergence,overshoot and oscillation are universal because of the limitation of communication and a lack of forecasting,which are inborn shortcomings of consensus. It is natural to modify this method with lots of optimizers. In order to reduce overshoot and smooth trajectories, this paper first adopted particle swarm optimization( PSO), then pigeon-inspired optimization( PIO) to modify the consensus. PSO is a very popular optimizer,while PIO is a new method,both work but still retain disadvantages such as residual oscillation. As a result,it was necessary to modify PIO,and a pigeon-inspired optimization with a slow diving strategy( SD-PIO) is proposed. Convergence analysis was performed on the SD-PIO based on the Banach fixed-point theorem and conditions sufficient for stability were achieved.Finally,a series of comparative simulations were conducted to verify the feasibility and effectiveness of the proposed approach.