Unmanned Aerial Vehicles Formation Flight Research Articles

Predictor-based constrained fixed-time sliding mode control of multi-UAV formation flight

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicle formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational burden. Initially, using the Taylor series concept, we derive the predictive models for the fixed-time sliding surface and reaching law. Subsequently, we formulate a constrained performance index by integrating these predictions with the control input. Ultimately, the optimal control input is computed through solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop fixed-time system stability in the presence of external disturbances and constraints. Furthermore, the comparative analysis with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, an experimental test is conducted to demonstrate the algorithm's potential for hardware implementation by employing the Hardware-in-the-Loop test.

Vehicle-to-Vehicle Based Autonomous Flight Coordination Control System for Safer Operation of Unmanned Aerial Vehicles

The exponential growth of unmanned aerial vehicles (UAVs) or drones in recent years has raised concerns about their safe operation, especially in beyond-line-of-sight (BLOS) scenarios. Existing unmanned aircraft system traffic management (UTM) heavily relies on commercial communication networks, which may become ineffective if network infrastructures are damaged or disabled. For this challenge, we propose a novel approach that leverages vehicle-to-vehicle (V2V) communications to enhance UAV safety and efficiency in UAV operations. In this study, we present a UAV information collection and sharing system named Drone Mapper®, enabled by V2V communications, so that UAVs can share their locations with each another as well as with the ground operation station. Additionally, we introduce an autonomous flight coordination control system (AFCCS) that augments UAV safety operations by providing two essential functionalities: UAV collision avoidance and UAV formation flight, both of which work based on V2V communications. To evaluate the performance of the developed AFCCS, we conducted comprehensive field experiments focusing on UAV collision avoidance and formation flight. The experimental results demonstrate the effectiveness of the proposed system and show seamless operations among multiple UAVs.

Flight Test of Autonomous Formation Management for Multiple Fixed-Wing UAVs Based on Missile Parallel Method

This paper reports on the formation and transformation of multiple fixed-wing unmanned aerial vehicles (UAVs) in three-dimensional space. A cooperative guidance law based on the classic missile-type parallel-approach method is designed for the multi-UAV formation control problem. Additionally, formation transformation strategies for multi-UAV autonomous assembly, disbandment, and special circumstances are formed, effective for managing and controlling the formation. When formulating the management strategy for formation establishment, its process is divided into three steps: (i) selecting and allocating target points, (ii) forming loose formations, and (iii) forming short-range formations. The management of disbanding the formation is formulated through reverse thinking: the assembly process is split and recombined in reverse, and a formation disbanding strategy that can achieve a smooth transition from close to lose formation is proposed. Additionally, a strategy is given for adjusting the formation transformation in special cases, and the formation adjustment is completed using the adjacency matrix. Finally, a hardware-in-the-loop simulation and measured flight verification using a simulator show the practicality of the guidance law in meeting the control requirements of UAV formation flight for specific flight tasks.

Hybrid Dec-POMDP/PID Guidance System for Formation Flight of Multiple UAVs

This paper proposes a guidance system with a new hybrid architecture for multiple fixed-wing unmanned aerial vehicles (UAVs) formation flight. The proposed architecture is hybrid in the sense of combining two control policies found in guidance systems: the Decentralized Partially Observable Markov Decision Process (Dec-POMDP) policy and the well-known PID controller. The Dec-POMDP policy part enables every UAV to avoid collision with any other UAV from the formation. The PID part is activated for regions far from the collision risk zone and is implemented in such a way that each UAV is completely controlled by only its own data, independent of its neighbors. The major novelty of the proposed system, compared to other hybrid approaches, is its decentralized nature which favors overcoming the usual problems that come with centralization such as the high dependence on a central decision node, a leader, or a ground station. Inherited from both parts, the overall system performance is robust in noisy and uncertain environments. Simulations were extensively performed to show the effectiveness of the proposed guidance system in distinct scenarios.

Relative Navigation in UAV Applications

This paper is committed to the relative navigation of Unmanned Aerial Vehicles (UAVs) flying in formation flight. The concept and methods of swarm UAVs technology and architecture have been explained. The relative state estimation models of unmanned aerial vehicles which are based on separate systems as Inertial Navigation Systems (INS)&Global Navigation Satellite System (GNSS), Laser&INS and Vision based techniques have been compared via various approaches. The sensors are used individually or integrated each other via sensor integration for solving relative navigation problems. The UAV relative navigation models are varied as stated in operation area, type of platform and environment. The aim of this article is to understand the correlation between relative navigation systems and potency of state estimation algorithms as well during formation flight of UAV.

Obstacle avoidance in V-shape formation flight of multiple fixed-wing UAVs using variable repulsive circles

ABSTRACTA formation control and obstacle avoidance algorithm has been introduced in this paper for the V-shape formation flight of fixed-wing UAVs (Unmanned Aerial Vehicles) using the potential functions method. An innovative vector approach has been suggested to fix the conventional challenge in employing the artificial potential field (APF) approach (the creation of local minimums). A method called variable repulsive circles (VRC) has been then presented aimed at designing proper flight paths tailored with functional limitations of fixed-wing UAVs in facing obstacles. Finally, the efficiency of the designed algorithm has been examined and evaluated for different flight scenarios.

Navigation information augmented artificial potential field algorithm for collision avoidance in UAV formation flight

In recent years, multiple Unmanned Aerial Vehicle (UAV) formation flight has attracted worldwide research interest, for its potential benefits of scalability and flexibility. In complex urban environments, the successful operation of those UAVs requires the system to provide certain safety level. As one of the key requirements, collision avoidance improves the system’s ability to accommodate operational environment variations, and to perform multiple tasks. To achieve this, artificial potential field (APF) has been recognized as one of the most suitable methods along with drone control. Although there has been substantial relevant work on the APF for single UAV in static environment, more efforts are desired to address formation maneuvers in complex environments such as urban. Most importantly, the traditional APF algorithms do not account for random errors in navigation solutions, which can bring potential risk to the UAV system. In response, this paper proposes a new APF algorithm that employs navigation information in complex urban environments, and the goal is to realize UAV formation collision avoidance. By augmenting the APF algorithm with UAV navigation information, the potential risk caused by navigation uncertainty can be mitigated, especially in the Global Navigation Satellite System (GNSS) challenged environment. The principle of the new APF approach is adaptively estimating the parameters of potential field force function, using the variance of navigation information and user-defined confidence probability. This new approach is applied in the synchronized UAV formation collision avoidance control. As a result, the UAVs can achieve fast position and attitude adjustment with high safety confidence. To verify the algorithm, quadrotors with emulated GNSS receivers are used to generate observation data. These data are incorporated into a complex urban environment simulation, where multiple sets of virtual obstacles are injected. Results show that the proposed method can achieve safe and efficient collision avoidance for cooperative formation flight in urban GNSS challenged environment.

Adaptive model predictive control with extended state observer for multi‐UAV formation flight

SummaryThis article studies the adaptive model predictive control with extended state observers (ESO) to deal with multiple unmanned aerial vehicles formation flight in presence of external disturbances and system uncertainties. Specifically, to deal with the mismatch of predictive model caused by external disturbances and system uncertainties, ESOs are introduced to estimate the lumped disturbances, where the ultimately bounded property of observer system can be guaranteed by using the Lyapunov stability theorem. With these observations, the distributed adaptive model predictive controller is designed to achieve trajectory tracking and disturbance rejection simultaneously for multiple unmanned aerial vehicles, as well as taking the state and input saturation into account. Moreover, the stability of proposed model predictive controller is analyzed. Finally, the simulation examples are provided to illustrate the validity of the proposed control scheme.

Distributed backstepping based control of multiple UAV formation flight subject to time delays

In this study, the authors propose a backstepping-based, distributed formation control method that is stable independent of time delays in communication among multiple unmanned aerial vehicles (UAVs). Centralised formation control of UAVs requires each agent to maintain a separation distance from other agents, which burdens the communication network of the UAVs. To overcome this problem, the authors consider a distributed control scheme wherein each agent updates its attitude and position based on the state information gathered through its neighbours. Instead of directly controlling the thrust generated by the propellers, they partition the mathematical model of the UAV into two subsystems, a linear attitude control loop and a non-linear position control loop. A backstepping-based outer position controller is then designed that interfaces seamlessly with the inner attitude controller of the cascaded control system. The closed-loop stability is established using a rigorous Lyapunov–Krasovskii analysis under the influence of distributed network time delays. Using the directed graph topology and a distributed backstepping structure, it is shown that the stability criterion is delay-independent. The proposed control algorithms are verified in simulation and then implemented in hardware, and actual flight test experiments prove the validity of these algorithms.

A Novel Control Approach for Flight-Stability of Fixed-Wing UAV Formation With Wind Field

This article addressed the flight-stability of the closed-loop system for a three fixed-wing unmanned aerial vehicles (UAVs) formation flight with wind field. A novel control strategy is presented to resist the influence of the wind field and then achieve a precise strike on the ground targets in the process of UAV air-to-ground strike mission. It is theoretically proved that the proposed controller system can be asymptotically stabilized. Both the dynamic response and steady-state error can converge to zero, respectively. The main contribution of this article is to establish a theoretical framework for designing an integrated controller to ensure that the UAVs precisely attack ground targets by adjusting the relevant parameters of the designed controller. The integrated controller we designed can control the consensus of the velocity for the UAV formation, and the distance between any two UAVs in three-dimensional space remains unchanged so that the UAV formation keeps a fixed geometry in case of decoupling. The effectiveness of the proposed controller is fully proved by a three fixed-wing UAVs formation flight. The simulation results show that the integrated control method integrates the advantages of the robust control with uncertain factors and the proportion-integration-differentiation control with rapid response.

Flocking of UAV Formation with Wireless Ultraviolet Communication

Wireless solar blind ultraviolet (UV) scattering communication is a new type of atmosphere optics communication technology with the important and potential advantages of all-weather, non-line-of-sight and secret communication, which is suitable for the needs of cluster security of Unmanned Aerial Vehicle (UAV) formation flight. UV communication technology can be applied to share UAVs status information, combined with efficient formation control method can achieve autonomous assembly, collision avoidance and formation keeping in UAV formation flight. In order to avoid the collision avoidance problem between the UAVs in the classic formation control algorithm. In this paper, the artificial potential function of the formation control algorithm is improved and the improved algorithm is applied to a single virtual leader UAV and multi-virtual leader UAVs. The simulation results show that the algorithm can ensure that the UAVs speed in the formation is consistent with the speed of the virtual leader UAV. In the course of the flight, the UAVs can avoid collision. Finally, the formation flight is completed with the desired formation.

Fully distributed guidance laws for unmanned aerial vehicles formation flight

In this paper, three fully distributed guidance laws are designed for unmanned aerial vehicles formation flight, which have the following advantages. Adaptive technology in novel guidance laws can adapt to various graphs that only need one spanning tree. Cooperative formation does not need to set the virtual structure of formation in advance, but only needs to adjust the formation parameters in the guidance law to achieve the desired time-varying formation. This paper uses a guidance law perpendicular to the line of sight to make the flight trajectory more straight; hence, enhancing its applicability in real-world scenarios. These new guidance laws also enable group formation transformation and can optimize the unmanned aerial vehicles’ formation without global information to obtain the optimum performance of the formation. The simulation results show the practicability and effectiveness of the new method.

Tracking control of multiple unmanned aerial vehicles incorporating disturbance observer and model predictive approach

This paper studies the disturbance observer-based model predictive control approach to deal with the unmanned aerial vehicle formation flight with unknown disturbances. The distributed control problem for a class of multiple unmanned aerial vehicle systems with reference trajectory tracking and disturbance rejection is formulated. Firstly, a local distributed controller is designed by using the model predictive control method to achieve stable tracking, where the local optimization problem is solved by an adaptive differential evolution algorithm. Then, a feedforward compensation controller is introduced by using a disturbance observer to estimate and compensate disturbances, and improve the ability of anti-interference. Besides, the stability of the proposed composite controller is analyzed as well. Finally, the simulation examples are provided to illustrate the validity of proposed control structure.

Formation Control of Multiple UAVs Incorporating Extended State Observer-Based Model Predictive Approach

This paper studies the extended state observer-based state space predictive control approach to deal with the multiple unmanned aerial vehicle formation flight with unknown disturbances. The distributed control problem for a class of multiple unmanned aerial vehicle systems with reference trajectory tracking and disturbance rejection is formulated. Firstly, a local distributed controller is designed by using the state space predictive control approach based on an error model to achieve stable tracking. Then, a feedforward compensation controller is introduced by using the extended state observer to estimate and compensate disturbances and improve the ability of anti-interference. Besides, the bounded stability of the designed extended state observer is analyzed as well. Finally, the simulation examples are provided to illustrate the validity of the proposed control structure.

Design and flight-stability analysis of a closed fixed-wing unmanned aerial vehicle formation controller

This article addresses a flight-stability problem for the multiple unmanned aerial vehicles cooperative formation flight in the process of the closed and high-speed flight. The main objective is to design a cooperative formation controller with known external factors, and this controller can keep the consensus of attitude and position and reduce the communication delay between any two unmanned aerial vehicles and increase unmanned aerial vehicles formation cruise time under the known external factors. Known external factors are taken into consideration, and longitude maneuvers using nonlinear thrust vectors were employed with unsteady aerodynamic models, according to the attitude and position of unmanned aerial vehicles, which were employed as corresponding input signals for studying the dynamic characteristics of unmanned aerial vehicles formation flight. In addition, the relative distance between any two unmanned aerial vehicles was not allowed to exceed their safe distance so that the controller could perform collision avoidance. An analysis of formation flight distance error shows that it converged to a fixed value that well ensured unmanned aerial vehicles formation flight stability. The experimental results show that the controller can improve the speed of a closed formation effectively and maintain the stability of formation flight, which provides a method for closed formation flight controller design and collision avoidance for any two unmanned aerial vehicles. Meanwhile, the effectiveness of proposed controller is fully proved by semi-physical simulation platform.

Collision Avoidance in Fixed-Wing UAV Formation Flight Based on a Consensus Control Algorithm

This paper addresses a collision avoidance problem for multiple unmanned aerial vehicles (UAVs) in the process of high-speed flight, thereby enabling UAV cooperative formation flight and effective mission completion. The main contribution is to propose a collision avoidance control algorithm for a multi-UAV system based on a bi-directional network connection structure. To effectively avoid collisions between UAVs and between UAVs and obstacles, the proposed consensus-based algorithm and a “leader-follower” control strategy are simultaneously applied for UAV formation control to ensure the convergence of the formation. Each of the UAVs has the same forward velocity and heading angle in the horizontal plane, and they maintain a constant relative distance in the vertical direction. This paper proposes a consensus-based collision avoidance algorithm for multiple UAVs based on an improved artificial potential field method. Simulation tests involving multiple UAVs were performed to validate the proposed control algorithm and to provide a reference for engineering applications.

Optimal formation control with limited communication for multi-unmanned aerial vehicle in an obstacle-laden environment

This paper investigates the formation control problem of multiple unmanned aerial vehicles (UAVs) with limited communication in a known and realistic obstacle-laden environment. In order to deal with the limited communication constraints, the leader–follower strategy and the virtual leader strategy are integrated into an optimal control framework to formulate this formation control problem. This combination formation framework can be achieved by integrating a redefined directed graph and a proposed information vector. In more practical applications, an obstacle/collision avoidance strategy is achieved by constructing a non-quadratic cost function innovatively using a virtual flow field approach. The proposed optimal control laws, which derive from the local information rather than the global information, are proved to guarantee the stability of the close-loop system by an inverse optimal control approach. The simulation results demonstrate the effectiveness of the formation flight of multiple UAVs with limited communication in an obstacle-laden environment.

Real-time Autonomous UAV Formation Flight with Collision and Obstacle Avoidance in Unknown Environment

In this paper autonomous formation control for Unmanned Aerial Vehicles (UAVs) has been discussed and a real time solution has been put forward by benefiting General Purpose Graphical Processing Units (GPGPU) accelerated potential field approach while ensuring obstacle and collision avoidance in unknown environment by using real-time sensors. GPGPU accelerated real time formation control for UAVs was designed and the basic model of the approach has been explained in our previous work (Cetin and Yilmaz 2014). As the deficiencies of the previous approach, autonomous real time collision and coordinated obstacle avoidance features in unknown environments are also handled while maintaining formation flight conditions in this work. With these features, improved autonomous formation control approach is discussed as a real time solution. The computation is performed by using Graphical Processing Units (GPUs) as parallel computation architectures by benefiting from Single Instruction Multiple Data (SIMD) type parallel algorithms. Classic binary map conversation, connected component labeling and minimum bounding box algorithms which are commonly used for image processing applications, has been evaluated for real time obstacle detection and avoidance features by developing GPGPU suitable parallel algorithms. Real-time solution has been developed by integrated these parallel algorithms with parallel Artificial Potential Field (APF) computation algorithm. Simulation results are proved that this novel autonomous improved formation control approach is successful and it would be used in real time applications like UAV formation flight missions.

Fault‐tolerant formation control of multiple UAVs in the presence of actuator faults

SummaryIn order to counteract actuator faults in formation flight of multiple unmanned aerial vehicles (UAVs), this paper presents a fault‐tolerant formation control (FTFC) design methodology, in which the reference generator and the finite‐time convergence of FTFC gains are explicitly considered. Feasible references in response to actuator faults can be generated by considering the health and mission conditions of an overall team of UAVs. Moreover, by applying an auxiliary integrated regressor matrix and vector method, FTFC gains can converge within a finite amount of time to facilitate the fault accommodation process. Thus, the negative effects resulting from failed actuators can be compensated by the healthy/redundant actuators in UAVs. Simulation studies of UAV formation flight are carried out to exemplify the effectiveness of this design approach. Copyright © 2015 John Wiley & Sons, Ltd.

Multi-UAVs formation autopilot design and performance analysis under interconnection topologies

This paper employs a unique extension-decomposition-aggregation (EDA) scheme to solve the formation flight control problem for multiple unmanned aerial vehicles (UAVs). The corresponding decentralised longitudinal and lateral formation autopilots are novelly designed to maintain the overall formation stability when encountering changes of the formation error and topologies. The concept of propagation layer number (PLN) is also proposed to provide an intuitive criterion to judge which type of formation topology is more suitable to minimise formation error propagation (FEP). The criterion states that the smaller the PLN of the formation is, the quicker the response to the formation error is. A smaller PLN also means that the resulting topology provides better prevention to the FEP. Simulation studies of formation flight of multiple Aerosonde UAVs demonstrate that the designed formation controller based on the EDA strategy performs satisfactorily in maintaining the overall formation stable, and the bidirectional partial-mesh topology is found to provide the best overall response to the formation error propagation based on the PLN criterion.