Control Of Multiple Unmanned Aerial Vehicles Research Articles

A systematic approach for threat and vulnerability analysis of unmanned aerial vehicles

The proliferation of Unmanned Aerial Vehicles (UAVs) is expected to experience a substantial rise in the next years, driven by their ever-increasing application across various domains. However, ensuring secure communication between UAVs and their ground stations is crucial to prevent the unauthorized disclosure of sensitive information that could jeopardize the mission’s integrity when exploited by malicious actors. Despite this importance, several UAV systems currently operate based on open-source command and control technologies, which have overlooked several security considerations while focusing on availability and safety. To address this concern, this study conducts a comprehensive security assessment of UAV-based systems starting with a systematic literature review whose main purpose is building a comprehensive catalog of threats associated with this technology. Particular attention has been paid to the MAVlink protocol, an open-source protocol commonly utilized for telemetry and command and control for multiple UAVs. Therefore, drawing upon the built catalog, a threat modeling and penetration testing technique has been employed to examine the MAVlink implementation on a real UAV. A threat model developed for a specific case study is also presented, leading to the discovery of four new vulnerabilities, some of which were successfully exploited through attacks. By shedding light on these vulnerabilities, this work seeks to encourage further investigation and research to develop robust security mechanisms for UAV communication systems. It is imperative to address these vulnerabilities proactively to enhance the overall security posture and safeguard against potential threats in the UAV ecosystem.

Formation fault-tolerant control for multiple UAVs with external disturbances

PurposeThe purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.Design/methodology/approachFirst, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.FindingsIt achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.Originality/valueA formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Fault-Tolerant Event-Triggrred Control for Multiple UAVs with Predefined Tracking Performance

This paper proposes an event-triggered fault-tolerant time-varying formation control method dedicated to multiple unmanned aerial vehicles (UAVs). We meticulously design a formation-tracking controller with a predefined tracking performance to accommodate the presence of actuator faults and external disturbances. Firstly, the formation-tracking controller acquires the desired heading using the line-of-sight algorithm. Secondly, in the presence of actuator faults and external disturbances, we introduce the radial basis function neural network (RBFNN) and adaptive law tracking control to effectively compensate for their effects. Additionally, we design adaptive tracking controllers and event-triggering conditions to increase the computational frequency. The predefined tracking performance, implemented via a Lyapunov function, ensures the convergence of the tracking error over time. Finally, we conduct a thorough analysis of the system’s stability, successfully eliminating the possibility of Zeno behavior. The simulation results thoroughly validate the effectiveness of the theoretical analysis.

Fixed‐time disturbance observer based distributed cooperative containment control with fixed‐time anti‐saturation compensator for multi‐unmanned aerial vehicles

AbstractThis article proposes a fixed‐time backstepping distributed cooperative containment control scheme for multiple unmanned aerial vehicles (UAVs). A fixed‐time compensator is designed for the fixed‐wing UAVs actuator saturation problem. Based on this, an improved fixed‐time disturbance observer is proposed for the problem of the excessive initial peak. The problem of “complexity explosion” is solved by the fixed‐time differential filter. For the distributed containment control of multiple UAVs, a cooperative control architecture based on a fixed‐time anti‐saturation compensation system is proposed. The proposed algorithm can be shown practicable by using Lyapunov stability theory and graph theory. Simulation results are given to demonstrate the effectiveness of the proposed control scheme.

Distributed adaptive event‐triggered fault‐tolerant cooperative control of multiple UAVs and UGVs under DoS attacks

AbstractHere, the issue of distributed adaptive event‐triggered fault‐tolerant cooperative control (FTCC) is studied for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults under denial‐of‐service attacks. To save the limited communication network resources, the distributed adaptive event‐triggered FTCC scheme is investigated for the multiple UAVs and UGVs which does not require continuous information relating to its neighbours. It is proven that the tracking errors are uniformly ultimately bounded by utilizing the Lyapunov function approach. Furthermore, the Zeno behaviour is excluded with the proposed scheme. Finally, simulation studies are provided to demonstrate the efficiency of the proposed scheme.

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.

Path driven formation-containment control of multiple UAVs: A path-following framework

In this article, a formation-containment control problem of networked unmanned aerial vehicles (UAVs) guided by multiple leaders evolving along implicit paths is addressed, comprising of a two-layer control design. At the leader layer, by formulating a novel collaborative error associated with projective arc length rather than relative distance, a special path-following control law with characteristics of spatial-temporal decoupling is proposed to allow for a predetermined formation with a desired spacing, successfully evading the unnecessary transient maneuvering behaviors. At the follower layer, under the premise of neighboring interaction, a containment controller is presented that enables several UAVs to enter into the convex hull formed by the leaders. Moreover, unknown system dynamics estimators (USDEs) are elaborated in both layers to accommodate the wind perturbations based on ideal invariant manifold and straightforward filtering operations. The prominent merits are twofold, one is that formation-containment issue is firstly resolved in path-following paradigm, where multiple leaders are cooperatively deployed along the predefined curves without temporal constraints and a consensus in velocity can be achieved without considering uncertainties. Another is that higher adaptiveness against time-varying wind can be implemented using a concise filtering without resorting to prevailing disturbance observers. The input-to-state stability of entire system is proved according to Lyapunov principles. Finally, the efficacy and superiority of suggested method are validated by simulations.

Decentralized modular hybrid supervisory control for the formation of unmanned helicopters

Formation control of Unmanned Aerial Vehicles (UAVs) requires them to tightly cooperate to reach and keep the formation, while avoiding collision. This paper proposes a novel decentralized hybrid supervisory control approach for the formation control of multiple UAVs. This is achieved by developing a symbolic motion planning technique to polarly partition the motion space resulting in a finite state discrete event model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Further, for the collision avoidance mechanism, a novel top-down decomposition-based approach is developed to design local supervisors decentralizedly. It is formally proved that with the proposed top-down decomposition-based approach, the (locally) supervised UAVs, as a whole, can cooperatively satisfy the desired (global) collision avoidance specification. The proposed decentralized supervisory control algorithm is also verified through a hardware-in-the-loop simulator for the formation control of unmanned helicopters.

Distributed Cooperative Control of Multiple UAVs in the Presence of Actuator Faults and Input Constraints

A distributed cooperative control algorithm of multiple unmanned aerial vehicles (UAVs) with directed topology is investigated in this brief. To overcome the actuator faults and external disturbance, incremental sliding mode formation controller is developed to realize the distributed coordination of the UAVs system, where an adaptive mechanism is utilized to deal with the chattering problem. Moreover, to reduce the adverse influence of input saturation, an auxiliary system is introduced to regulate the control signals. It is shown by Lyapunov method that the stability of the proposed algorithm can be guaranteed. A numerical example is given to illustrate that all follower UAVs can track the leader UAV.

Vision-based formation control of multiple UAVs with event-triggered integral sliding mode control

ABSTRACT Vision-based formation control offers an alternate solution for unmanned aerial vehicles (UAVs) to work together in the external position system denied environment. In this paper, we present a vision-based formation control strategy with the advantages of high tracking performance and low consumption of communication resources. A vision-based multi-robot localisation methods is applied to get precise position information, and the extended Kalman filter (EKF) is used to fuse measurement data from different sensors. The integral sliding mode controller (ISMC) is utilised to ensure the fast convergence and robustness to the desired formation, and the event-triggered communication scheme is employed to reduce redundant transmission of state information used in the formation controller. The simulation results in Gazebo with a team of three UAVs are given to illustrate the effectness of the proposed control strategy.

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.

Distributed integral control of multiple UAVs: precise flocking and navigation

The authors interest in this work is to perform a precise real-time flocking of multiple unmanned aerial vehicles (UAVs). A consensus-based flocking algorithm that ensures a precise security distance between UAVs is proposed. By using Lyapunov theoretical analysis, the authors propose a flocking algorithm that ensures the ultimate boundedness of multiple-UAV system solutions. Moreover, this algorithm is enhanced by a distributed integral control that renders the inter-distances between UAVs more precise. Finally, experimental results are provided to prove and show the efficiency of these algorithms.

Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology

In this paper, a decentralized fault-tolerant cooperative control scheme is developed for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and a directed communication network. To counteract in-flight actuator faults and enhance formation flight safety, neural networks (NNs) are used to approximate unknown nonlinear terms due to the inherent nonlinearities in UAV models and the actuator loss of control effectiveness faults. To further compensate for NN approximation errors and actuator bias faults, the disturbance observer (DO) technique is incorporated into the control scheme to increase the composite approximation capability. Moreover, the prediction errors, which represent the approximation qualities of the states induced by NNs and DOs to the measured states, are integrated into the developed fault-tolerant cooperative control scheme. Furthermore, prescribed performance functions are imposed on the attitude synchronization tracking errors, to guarantee the prescribed synchronization tracking performance. One of the key features of the proposed strategy is that unknown terms due to the inherent nonlinearities in UAVs and actuator faults are compensated for by the composite approximators constructed by NNs, DOs, and prediction errors. Another key feature is that the attitude synchronization tracking errors are strictly constrained within the prescribed bounds. Finally, simulation results are provided and have demonstrated the effectiveness of the proposed control scheme.

Effects of Touch, Voice, and Multimodal Input, and Task Load on Multiple-UAV Monitoring Performance During Simulated Manned-Unmanned Teaming in a Military Helicopter.

We evaluated three interface input methods for a simulated manned-unmanned teaming (MUM-T) supervisory control system designed for Air Mission Commanders (AMCs) in Black Hawk helicopters. A key component of the U.S. Army's vision for unmanned aerial vehicles (UAVs) is to integrate UAVs into manned missions, called MUM-T (Department of Defense, 2010). One application of MUM-T is to provide the AMC of a team of Black Hawk helicopters control of multiple UAVs, offering advanced reconnaissance and real-time intelligence of flight routes and landing zones. Participants supervised a (simulated) team of two helicopters and three UAVs while traveling toward a landing zone to deploy ground troops. Participants classified aerial photographs collected by UAVs, monitored instrument warnings, and responded to radio communications. We manipulated interface input modality (touch, voice, multimodal) and task load (number of photographs). Compared with voice, touch and multimodal control resulted in better performance on all tasks and resulted in lower subjective workload and greater subjective situation awareness, ps < .05. Participants with higher spatial ability classified more aerial photographs ( r = .75) and exhibited shorter response times to instrument warnings ( r = -.58) than participants with lower spatial ability. Touchscreen and multimodal control were superior to voice control in a supervisory control task that involved monitoring visual displays and communicating on radio channels. Although voice control is often considered a more natural and less physically demanding input method, caution is needed when designing visual displays for users sharing common communication channels.

ArduSim: Accurate and real-time multicopter simulation

As the popularity and the number of Unmanned Aerial Vehicles (UAVs) increases, new protocols are needed to coordinate UAVs when flying autonomously, and to avoid that these UAVs collide with each other. Directly testing such novel protocols on real UAVs is a complex procedure that requires investing much time, money and research effort. Hence, it becomes necessary to have the possibility to first test different solutions using simulation. Unfortunately, existing tools present significant limitations: some of them only simulate accurately the flight behavior of one UAV, while some other simulators can manage several UAVs simultaneously, but not in real-time, thus loosing accuracy regarding the mobility pattern of the UAV. In this work we address such problem by introducing ArduSim, a novel simulator that allows controlling in soft real-time the flight and communications of multiple UAVs, being the developed protocols directly portable to real devices. The contributions of this work include: (i) the ArduSim simulation platform, which allows realistic simulation and control of multiple UAVs simultaneously, offering functionalities not provided by existing alternatives; (ii) a model for the WiFi communications link between UAVs, based on real experiments, and that is integrated into ArduSim itself; and (iii) a thorough study of the scalability performance of our simulator.

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.

Formation Control of Multiple Unmanned Aerial Vehicles by Event-Triggered Distributed Model Predictive Control

This paper proposes an event-triggered model predictive control (MPC) scheme for the formation control of multiple unmanned aerial vehicles (UAVs). A distributed MPC framework is designed in which each UAV only shares the information with its neighbors, and the obtained local finite-horizon optimal control problem (FHOCP) can be solved by a swarm intelligent optimization algorithm. An event-triggered mechanism is proposed to reduce the computational burden for the distributed MPC scheme, which takes into consideration the predictive state errors as well as the convergence of cost function. Furthermore, a safe-distance-based strategy for no-fly zone avoidance is developed and integrated into the local cost function for each FHOCP. Numerical simulations show that the proposed event-triggered distributed MPC is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.

On decentralized adaptive full-order sliding mode control of multiple UAVs

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system.

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 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 &amp; Sons, Ltd.