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

Unmanned aerial vehicles (UAVs) have been widely used in industry and daily life, where safety is the primary consideration, resulting in their use in open outdoor environments, which are wider than complex indoor environments. However, the demand is growing for deploying UAVs indoors for specific tasks such as inspection, supervision, transportation, and management. To broaden indoor applications while ensuring safety, the quadrotor is notable for its motion flexibility, particularly in the vertical direction. In this study, we developed an improved probabilistic roadmap (PRM) planning method for safe indoor flights based on the assumption of a quadrotor model UAV. First, to represent and model a 3D environment, we generated a reduced-dimensional map using a point cloud projection method. Second, to deploy UAV indoor missions and ensure safety, we improved the PRM planning method and obtained a collision-free flight path for the UAV. Lastly, to optimize the overall mission, we performed postprocessing optimization on the path, avoiding redundant flights. We conducted experiments to validate the effectiveness and efficiency of the proposed method on both desktop and onboard PC, in terms of path-finding success rate, planning time, and path length. The results showed that our method ensures safe indoor UAV flights while significantly improving computational efficiency.

/pdf/an-improved-probabilistic-roadmap-planning-method-for-safe-13wi5nb4.pdf

An Improved Probabilistic Roadmap Planning Method for Safe Indoor Flights of Unmanned Aerial Vehicles

This paper develops a Neural Network (NN) event-triggered finite-time consensus control method for uncertain nonlinear Multi-Agent Systems (MASs) with dead-zone input and actuator failures. In practical applications, actuator failures would inevitably arise in MASs. And the time, pattern, and value of the failures are unknown. Besides, the actuators of MASs also suffer from dead-zone nonlinearity. No matter actuator failures or dead-zone input would dramatically affect the performance and stability of MASs. To address these issues, finite-time adaptive controllers capable of simultaneously compensating for actuator failures and dead-zone input are constructed by adopting the backstepping technology. Meanwhile, the NN control scheme is adopted to handle the unknown nonlinear dynamics of each agent. Furthermore, an event-triggered control mechanism is established that no longer requires continuous communication on the control network. Under the proposed control method, all followers achieve finite-time synchronization, irrespective of the presence of limited bandwidth, unknown failures, and dead-zone input. These results are demonstrated by simulations. 

NN event-triggered finite-time consensus control for uncertain nonlinear Multi-Agent Systems with dead-zone input and actuator failures.

This paper presents a secure formation control design of multi-agent systems under denial of service (DoS) attacks. Multiple unmanned aerial vehicle systems (UAVs) are considered in this paper. The proposed technique takes into account communication time delay, as well as formation and cyberattack, and provides a robust guidance method as well as a reliable middleware for information transfer and sharing. To ensure optimal guidance and coordination, a combined approach of L1 adaptive control and graph theory is used. The packet transmission between all UAVs is handled by the data distribution services (DDS) middleware, which overcomes the interoperability problem when dealing with multiple UAVs of different platforms and can be considered as an extra security level based on its quality of service (QoS). The graph theory is utilized to coordinate multiple UAVs in a hexagon formation, while the L1 controller is utilized as a local controller to stabilize the UAV’s dynamic model. A robust control security level is built to handle the effect of cyberattacks based on linear matrix inequalities (LMIs) control. Simulations are used to verify and show the performances of the proposed technique under the conditions indicated earlier. 

/pdf/denial-of-service-attack-of-qos-based-control-of-multi-agent-4sbld3uu.pdf

Denial of Service Attack of QoS-Based Control of Multi-Agent Systems

Multi‐agent system (MAS) is a common cyber‐physical system (CPS). Due to it often uses a relatively open network platform, it is vulnerable to malicious cyber attacks in the process of system operation, so the control scheme design is critical to ensure the system operation security. In this article, we propose a new resilient neuroadaptive dynamic surface control scheme for non‐linear MASs with potential cyber attacks (false data injection and denial‐of‐service), system uncertainty, unknown control gain, and output constraints which are usually seen on CPSs. In this scheme, the neuroadaptive controller design ensures that all signals of the closed loop system are semi‐globally uniform ultimately bounded when the MAS even exists time‐varying cyber attacks on data links among agents, and the links between controllers, actuators, and sensors. Using Gaussian radial basis function neural network, the system uncertainty, non‐strict feedback terms, unknown control gain, and some cyber attacks are effectively solved and the process of controller design is extremely simplified. Finally, we provide a simulation result to verify the effectiveness and superiority of the proposed control scheme.

Consensus tracking control for uncertain non‐strict feedback multi‐agent system under cyber attack via resilient neuroadaptive approach

In this paper, a novel robust fault detection and identification and fault-tolerant control (RFDI-FTC) system is proposed for thrust-vectoring aircraft (TVA) during supermaneuverable flight. To this end, a TVA model that incorporates control surface damage, actuator faults, disturbances, and aerodynamic parameter uncertainty is described, and a novel RFDI-FTC system is designed for the TVA model, which includes 1) an RFDI subsystem with robustness to disturbances and parameter uncertainty and sensitivity to control surface damage and actuator faults by multiple adaptive observers; 2) a command filter FTC subsystem to eliminate the differential expansion in traditional backstepping control and to compensate for control surface damage, actuator faults, disturbances and parameter uncertainty; and 3) a stability analysis for the RFDI-FTC system. The simulation results are given to demonstrate the effectiveness and potential of this system.

/pdf/a-novel-rfdi-ftc-system-for-thrust-vectoring-aircraft-3ukujjytqm.pdf

A Novel RFDI-FTC System for Thrust-Vectoring Aircraft Undergoing Control Surface Damage and Actuator Faults During Supermaneuverable Flight

Comprehensive fault-tolerant control of leader–follower unmanned aerial vehicles (uavs) formation

A fault-tolerant control method for the UAV formation that has topological fault, control surface fault, actuator fault and uncertainty is proposed. Firstly, the formation motion model and the UAV motion model are established. Then based on the topological fault detection method, the topological fault reconstruction and optimization algorithm is proposed to realize the formation topological fault reconstruction and optimization with minimum communication cost and formation reconstruction cost. In designing the backstepping fault-tolerant control method, the actuator's fault identification module and the auxiliary system module are used to estimate and compensate for the faults of the actuator and the control surface respectively so as to realize the stable flight of the UAV formation under the conditions of actuator fault, control surface fault and uncertainty. The simulation results verify the superiority of the fault-tolerant control method for the UAV formation with topological faults.

/pdf/a-fault-tolerant-control-method-for-unmanned-aerial-vehicle-5cdh0iwzds.pdf

A Fault-Tolerant Control Method for Unmanned Aerial Vehicle (UAV) Formation with Topological Faults Considered

In this paper, a backstepping fault-tolerant control based on sliding-mode observer is proposed for the unmanned thrust-vectoring aircraft (UTVA) control. First, the UTVA model with the uncertainty, control surface damage and actuator faults is described, which is divided into fast loop and slow loop. Next, the cascade observers including a high-order SMO and the discontinuous projection adaptive law are proposed to estimate the states with compensating the uncertainty and control surface damage, and the sliding-mode observer is designed to identify actuator faults and estimate fault parameters. Then, the backstepping fault-tolerant control combining the estimation of states and fault parameters is proposed to achieve the global fault-tolerant control, which compensates the uncertainty, control surface damage and actuator faults. Finally, simulation results are given to demonstrate the effectiveness for UTVA.

/pdf/backstepping-fault-tolerant-control-for-unmanned-thrust-1dlp2sr3hh.pdf

Backstepping Fault-Tolerant Control for Unmanned Thrust-Vectoring Aircraft Based on Sliding-Mode Observer

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