78 results about "Virtual leader" patented technology

The invention relates to the technical field of multi-agent cooperative control, and discloses a multi-agent reinforcement learning formation adaptive method fusing a graph attention mechanism. According to the method, a dynamic graph state space is constructed, and a speed self-adaptive communication mechanism and a multi-target return function are combined, so that the problem of insufficient generalization ability during intelligent agent number change or topological structure dynamic adjustment is solved. The scheme comprises the following steps: establishing a virtual leader-following formation model and a motion dynamics model; designing an adaptive communication radius formula based on speed change; constructing a graph state space, and dynamically aggregating neighbor information by using a multi-head attention mechanism; designing a strategy network and a value evaluation network with residual connection; and a centralized training distributed execution framework is adopted to update model parameters. Adaptive extraction of key neighbor information is realized through a graph attention mechanism, and adaptability and stability of a formation system in a complex environment are improved by combining dynamic communication range adjustment. The method is suitable for unmanned aerial vehicle group control, robot cooperation and other scenes.

The invention provides a zero-sum game-based distributed elastic consensus optimal control method under denial of service attack of a multi-agent system, and the method specifically comprises the steps: firstly, constructing a multi-agent formation model in which a leader and a plurality of followers cooperatively move through graph theory knowledge and a multi-agent second-order state equation; secondly, in order to reduce the influence of denial of service attack on communication topology, a time-varying weight distributed elastic observer is provided to estimate the state of a leader, and the attacked condition of the leader is considered; then, by constructing an augmentation system, a distributed consistency tracking problem with a leader is converted into a local tracking problem between each follower and a virtual leader thereof; and finally, in order to solve the zero-sum game problem, introducing a Hamiltonian-Jacobian-Ansaxophone equation to realize optimal control input under maximum external disturbance, and realizing algorithm design by using single-evaluation reinforcement learning with experience playback and combining a gradient descent method.

The invention provides an unmanned aerial vehicle formation conflict avoidance control method and system and a medium, and the method comprises the steps: introducing a virtual leader-follower-based Stackelberg game architecture, enabling a virtual leader unmanned aerial vehicle to adaptively adjust the trajectory according to the formation state, and enabling the follower unmanned aerial vehicle to maintain the stability of the formation while completing a set tracking task; constructing an obstacle avoidance penalty term based on a speed obstacle method, and embedding the obstacle avoidance penalty term into an optimization objective function of the follower unmanned aerial vehicle to ensure that the follower unmanned aerial vehicle realizes collision avoidance in an obstacle environment; and respectively solving Hamiltonian-Jacobian-Bellman equations corresponding to the leader unmanned aerial vehicle and the follower unmanned aerial vehicle by adopting a single-network ADP algorithm, and generating a controller in real time. According to the invention, the problems of safe obstacle avoidance and tracking control of a multi-unmanned aerial vehicle system with formation stability requirements are effectively solved.

The invention discloses a spacecraft cluster robust formation control method based on a dynamic event trigger mechanism, which is applied to the technical field of spacecraft cluster formation control, and aims to solve the problem that the prior art still has certain limitations under the complex conditions of limited communication, unknown control input of a virtual leader, external disturbance and the like. The method comprises the following steps: firstly, constructing a six-degree-of-freedom attitude and orbit coupling spacecraft cluster system model influenced by external disturbance and model uncertainty; on the basis, a robust formation control scheme based on a dynamic event trigger communication mechanism is designed, and the scheme comprises three key components, the three mechanisms are respectively a self-adaptive second-order expansion system based on local discontinuous communication, a multi-spacecraft robust formation device based on neural network self-adaptive estimation and a unified dynamic event trigger communication mechanism.

The invention discloses a cross-domain cluster system distributed safety formation control method in an urban interference environment, and the method comprises the steps: constructing a distributed elastic observer to estimate the state of a virtual leader, and providing a formation output reference for cooperative formation tracking control; the augmentation system of the air-ground unmanned cluster system is constructed by combining the state data of the distributed elastic observer and the state data of the air-ground unmanned cluster system, and a control gain matrix is constructed by using a feedforward-feedback control method. Initial excitation is applied to an augmentation system of the air-ground unmanned cluster system, when operation time meets an initial excitation condition, state data of operation of the air-ground unmanned cluster system is collected, optimal formation tracking control is determined by using an online double-integrator reinforcement learning method, and optimal formation tracking control of the air-ground unmanned cluster system is realized. According to the method, the optimal safe formation tracking control of the cross-domain air-ground unmanned cluster system can be realized under the conditions that the dynamic model of the system is unknown and the distributed denial of service is attacked.

The invention discloses a heterogeneous multi-agent time-varying formation tracking control method based on output adjustment, and the method comprises the steps: firstly, converting a time-varying formation control problem of a heterogeneous multi-agent system into an optimal cooperative output adjustment problem under multiple constraints; then, considering that only part of followers can acquire dynamic pilot information, constructing a distributed trajectory generator based on adjacent information for each follower, and asymptotically estimating output state information of a virtual pilot, so as to accurately acquire an expected signal of an intelligent agent; secondly, performing optimization solution on a collaborative output adjustment problem through a shrinkage constraint-based variable time domain DMPC algorithm; finally, the effectiveness of the algorithm is verified through simulation of the multi-rotor unmanned aerial vehicle. According to the invention, the heterogeneous unmanned aerial vehicle formation can complete trajectory tracking and formation keeping tasks under multiple constraints.

The invention discloses a multi-unmanned ship distributed cooperative maneuvering dynamic target tracking control method, and relates to the field of unmanned ship cooperative control. In order to solve the defect that high-precision maneuvering tracking of a dynamic target cannot be realized in an irregular water area in the prior art, the technical scheme provided by the invention comprises the following steps: generating a new position expression with a clear definition relative degree according to preset parameters based on an original position and a course of an unmanned ship; carrying out online estimation on the dynamic target speed, and outputting a target speed estimation value; gathering the information of each virtual leader, and estimating the speed of the leader; formation rotation, scaling and translation parameters are generated according to the affine transformation theory; and performing online compensation on system uncertainty and external disturbance, and outputting a final control signal for realizing maneuvering tracking control. The method is suitable for a control task that a plurality of under-actuated unmanned ship clusters perform autonomous cooperative maneuvering tracking on a dynamic moving target under a complex sea condition.

The present disclosure discloses a method and system for formation control for an USV swarm via a CEDRL. The method includes: designing a desired formation pattern based on a formation hierarchical virtual leader strategy, establishing an USV desired location library, and assigning a location index to a desired location of each USV in a formation; updating the desired location of each USV and the corresponding location index via an USV formation local consensus strategy in a case where there is a risk of collision between USVs; and acquiring an actual geolocation of each USV in real time, and adopting a surface vessel control decision-making network to direct the USV toward a latest desired location. An autonomous collaborative formation of a large-scale USV swarm may be realized by the present disclosure.

A dynamic target tracking control method for distributed cooperative maneuvering of multiple unmanned boats relates to the field of cooperative control of unmanned boats. In order to solve the defect in the existing technology that it is impossible to achieve high-precision maneuvering tracking of dynamic targets in irregular waters, the technical solution provided by the present invention includes: based on the original position and heading of the unmanned boat, a new position expression with clearly defined relative degrees is generated according to preset parameters; the speed of the dynamic target is estimated online, and the target speed estimate is output; the information of each virtual leader is aggregated to estimate the leader speed; the formation rotation, scaling and translation parameters are generated according to the affine transformation theory; the system uncertainty and external disturbance are compensated online, and the final control signal for achieving maneuvering tracking control is output. It is suitable for the control task of multiple under-actuated unmanned boat clusters to perform autonomous cooperative maneuvering tracking of dynamic moving targets in complex sea conditions.

The invention discloses a multi-robot affine formation path optimization method driven by a virtual navigator, and the method comprises the steps: firstly setting a point set composed of the virtual navigator and followers, enabling the virtual navigator to form a convex hull and meet an affine localization condition, so as to guarantee that the followers are always located in the convex hull; generating a collision-free reference trajectory of the mass center of the virtual navigator based on a fast random tree algorithm; constructing a nonlinear constraint optimization problem NCO which contains linear transformation constraint and meets smoothness, obstacle avoidance, speed and angular speed constraint; and establishing a communication graph of the virtual navigator and the follower, calculating balance stress, designing a smoother follower distributed differential speed control law, and realizing formation path optimization and obstacle avoidance control. Compared with an existing method, the formation path generation method has the advantages that the smooth and stable formation path fitting the reference trajectory can be generated while obstacle avoidance and physical feasibility are guaranteed, and the cooperative motion capability and the control performance of a multi-robot system in a complex environment are improved.

The invention provides a control method, system and device based on denial of service attack and a storage medium, and the method comprises the steps: obtaining a neighbor estimation state of each following agent based on a state estimator and neighbor state information of each following agent; a reference state of each following agent is obtained based on a distributed hybrid event trigger observer, a neighbor estimation state of each following agent, a denial of service attack detection result and reference information of a virtual leader, and the distributed hybrid event trigger observer is constructed based on a denial of service attack model; based on the controller of each following agent and the reference state, obtaining an optimal control strategy of each following agent; and executing the respective optimal control strategy by using the actuator of each following agent, so that each following agent follows the virtual leader to keep formation. Therefore, the safe formation tracking performance with the optimal robustness of the heterogeneous multi-agent system is ensured under the DoS attack.

The invention discloses a multi-unmanned aerial vehicle cooperative obstacle avoidance control method based on a pigeon flock hierarchical leading intelligent mechanism, and the method comprises the steps: 1, building a virtual leader and follower unmanned aerial vehicle model, and building an unmanned aerial vehicle group communication topology; 2, initializing the position, speed, attitude and other state information of the unmanned aerial vehicle, initializing the obstacle position distribution and threat radius in the environment, and initializing the detection area of the unmanned aerial vehicle; and the like are totally eight steps. According to the method, an intelligent decision-making process that a high level guides a low level to perform collision avoidance when a pigeon flock faces natural enemy predation is used for reference, the anti-collision decision-making authority of a virtual leader and a following level unmanned aerial vehicle is stipulated, a leader obstacle avoidance and trajectory tracking switching controller is designed, a collision avoidance control protocol based on a logarithmic potential field gradient is established, and a collision avoidance control system is established. The invention provides a pigeon-flock-level-decision-imitating master-slave cooperative obstacle avoidance control method developed for a four-rotor unmanned aerial vehicle cluster in an obstacle distribution environment, and the method is adaptive to random obstacle distribution.

The invention relates to a robust predefined time path following formation control method for unmanned aerial vehicles. The method comprises the following steps: acquiring a target path curve of a moving object, and determining a target course angle rate of the moving object based on the target path curve, a preset course angle function, a first lumped interference parameter and a preset time performance function; based on the total error of the projection arc length, the expected forward movement speed and the second lumped interference parameter, the target forward movement speed of the moving object is determined, and the total error of the projection arc length comprises a first projection arc length error between the moving object and an adjacent target and a second projection arc length error between the moving object and a preset virtual leader target; and adjusting the moving object based on a preset kinematic model, the target course angular rate and the target forward moving speed, so that the moving object moves based on the target path curve. By adopting the method, the control precision of the unmanned aerial vehicle in the driving process can be improved.

The invention relates to a multi-unmanned aerial vehicle distributed fault-tolerant formation control method and system based on a potential game, belongs to the technical field of unmanned aerial vehicle control, and is used for solving the distributed formation control problem of a multi-quadrotor unmanned aerial vehicle virtual leader-follower system under the conditions of model uncertainty, actuator fault and external disturbance. According to the method, a distributed leader estimator is designed to obtain leader expectation information, a preset performance function is introduced in preset time to constrain position and attitude tracking errors, and a linear parameterized regression matrix and a multi-parameter adaptive law are constructed to realize unified compensation of uncertainty and faults. And the formation robustness is guaranteed by combining a potential game and a dynamic average consistency strategy. According to the invention, it is ensured that the tracking error converges to the preset range within the preset time, and the fault-tolerant capability and stability of the formation system are improved.

The application discloses a method for adaptive secure consensus control of a multi-agent spatio-temporal dynamic system with unknown boundary nonlinearity under hybrid attacks, comprising the following steps: constructing a multi-agent spatio-temporal dynamic system model with unknown boundary nonlinearity and a virtual leader model; establishing a hybrid network attack model containing deception attacks and denial of service (Dos) attacks, and using an adaptive radial basis neural network to approximate the unknown boundary nonlinearity function; defining a consensus error signal to obtain a consensus state error system; designing a composite adaptive neural network secure boundary consensus control scheme, constructing a Lyapunov function for the error system, and obtaining a sufficient condition for the error system to realize mean square secure consensus control. The application effectively solves the problem that the traditional method is difficult to simultaneously cope with complex network attacks and unknown boundary nonlinear disturbances, and significantly improves the security and robustness of the system.

The invention discloses a multi-cluster four-rotor unmanned aerial vehicle cooperative control method, system, device and medium, and relates to the technical field of sliding mode control, and the method comprises the steps: dividing unmanned aerial vehicles in a multi-cluster four-rotor unmanned aerial vehicle formation into leaders and followers; tracking the virtual leader by using an actual leader to obtain a tracking error, establishing a terminal sliding mode surface according to a dynamic adjustment value of the tracking error, and obtaining control input during convergence; adjusting the state of the follower by using a neighbor state, tracking a sub-cluster leader, and carrying out comprehensive control input according to the state of the follower and a tracking result; the state difference between the follower and the leader is used as a tracking error, a global fast terminal sliding mode surface is constructed according to the tracking error, global control input is obtained by offsetting disturbance for comprehensive control input, and all states are converged to the sliding mode surface within limited time. According to the method, a sliding mode surface structure is redesigned, a nonlinear term about a tracking error dynamic adjustment value is introduced, and it is guaranteed that the system state is rapidly converged within limited time.

This invention proposes an adaptive virtual impedance droop control method, system, device, and medium, relating to the field of droop control. The method includes: calculating the standardized reactive power of each local node and neighboring node based on the equivalent output impedance and reactive power droop coefficient; generating a correction amount for the virtual impedance based on the accelerated consensus algorithm and the standardized reactive power of each local node and neighboring node; adjusting the virtual impedance in the distributed grid topology according to the correction amount of the virtual impedance to obtain the adjusted dynamic virtual impedance; calculating the virtual impedance voltage drop based on the adjusted dynamic virtual impedance; calculating the feedforward compensation voltage reference value; calculating the common compensation amount of the preset virtual leader node and the local compensation amount of each local node and neighboring node to obtain the total voltage compensation command; adjusting the feedforward compensation voltage reference value according to the total voltage compensation command to obtain a voltage stabilization scheme, using the dynamic virtual impedance as the power distribution scheme.

The invention provides an unmanned aerial vehicle cluster formation method, system and device and a storage medium, and aims to solve the problems that formation configuration is carried out again due to different numbers of unmanned aerial vehicle cluster formation flights, the relevance with path points is poor, and formation transformation needs to be realized depending on limitation of a relative angle in formation and the like. The method comprises the following steps: determining a formation pattern required to be realized by an unmanned aerial vehicle cluster according to a formation pattern request of an unmanned aerial vehicle cluster formation task; a formation pattern number corresponding to the formation pattern is set, formation pattern parameters corresponding to the formation pattern number are configured, and the formation pattern parameters comprise position parameters of a real leader or a virtual leader; based on the number of the unmanned aerial vehicles, the formation number of each unmanned aerial vehicle is configured; and based on the position parameters of the real leader or the virtual leader and the formation number of each unmanned aerial vehicle, determining the relative position information of each unmanned aerial vehicle relative to the real leader or the virtual leader under the formation.

The application provides a kind of multi-agent system control method under the condition of having saturation constraint and time delay, it is related to intelligent control technical field, comprising: establishing multi-agent system model, wherein, virtual leader is established between leader and follower agent, follower communicates with virtual leader, virtual leader communicates with leader, on this basis, controller is designed based on saturation constraint and communication time delay, error system between follower agent and leader is constructed, consistency condition is established, and the leader-following consistency of multi-agent system is controlled.The application is aimed at the problem that the dimensions of leader and follower in the model are different, a virtual leader is established between leader and follower agent, and the communication between actual leader and follower is completed.In addition, in view of the actual situation that the inherent properties of agent are limited, the control protocol is adjusted based on saturation constraint information and communication time delay, so that the leader-following consistency of the system is realized.

The application provides a finite time distributed formation method of unmanned surface vehicle cluster system, which can not only guarantee that the unmanned surface vehicle system reaches the expected formation mode in finite time, but also ensure that the system speed and formation error always meet the time-varying constraint requirements during the whole operation period, and the method comprises the following steps: establishing a three-degree-of-freedom unmanned surface vehicle kinematics and dynamics model; approximating the saturation constraint of the system by using a smooth function, and combining a fault model to establish a new system dynamics model subjected to driver faults and saturation constraints; designing a virtual control law, also known as a kinematics guide law; designing a parameterized lane speed of a virtual leader; designing a finite time distributed formation controller; and designing an uncertain compensation adaptive law. According to the needs of the user, the time-varying formation mode and the time-varying constraint function can be designed, the formation form of the multiple unmanned surface vehicles is dynamically adjusted, and meanwhile, it is ensured that the speed and formation tracking error always do not deviate from the specified constraint set.

The invention discloses an adaptive inclusive formation control method for a heterogeneous singular multi-agent system, comprising: first constructing a heterogeneous singular multi-agent system and describing its inclusive formation control; then designing an adaptive state feedback formation controller and an adaptive dynamic output formation controller; then converting the inclusive formation control problem into an infinite norm constraint problem by designing the state transformation of a closed-loop system under the action of the adaptive state feedback formation controller; then combining pulse-free analysis and stability analysis to obtain the inclusive formation control method for the heterogeneous singular multi-agent system under the action of the adaptive state feedback formation controller; finally, according to the state transformation of the closed-loop system under the action of the adaptive dynamic output formation controller, the inclusive formation control method for the heterogeneous singular multi-agent system is obtained; the present invention realizes the inclusive formation control of the heterogeneous singular multi-agent system and can quickly estimate the virtual leader matrix information.

This disclosure provides a reinforcement learning-driven cooperative formation control method for an air-to-ground unmanned swarm system. A dynamic model of the air-to-ground unmanned swarm system is established; a distributed predefined time observer is constructed to estimate the virtual leader state, providing a state reference for cooperative formation tracking control; the dynamic model of the augmented air-to-ground unmanned swarm system is reconstructed, and a control gain matrix is ​​then constructed. Piecewise constant initial stimuli are applied to the augmented system, and its early operational state data is collected and stored. Then, based on the early operational data of the air-to-ground unmanned system, an initial stable control strategy is obtained using a data-driven method. Finally, based on an offline policy reinforcement learning algorithm and a data-based initial stable control strategy, the optimal formation tracking controller is learned, achieving optimal formation tracking control of the air-to-ground unmanned system. This invention can achieve optimal time-varying formation tracking control of an air-to-ground unmanned swarm system according to complex task requirements, even when the system model is unknown.

The present application relates to the technical field of unmanned aerial vehicle control, in particular to a control algorithm for cooperative inspection of unmanned aerial vehicle cluster, the present application is designed by innovative non-central architecture and double-neighbor system, when the node communication loss or failure of unmanned aerial vehicle cluster is up to 30%, it can still maintain more than 92% of task completion rate, fault tolerance is significantly better than prior art; its core only relies on three simple behavior rules, the requirement of single machine computing power and communication bandwidth is very low, it can adapt to low-cost civilian unmanned aerial vehicle platform, so that the cost of large-scale deployment is reduced by about 40%. Combined with dynamic weight adjustment mechanism and virtual leader guidance, the system can not only autonomously avoid dynamic obstacles in complex urban areas, but also accurately follow the preset inspection route, realizing the unity of flexibility and accuracy; and supports multi-hop Ad-hoc communication, maintains stable connection in the area without ground network; fault automatic switching, single machine exit does not affect the overall task; combined with fixed airport, it can realize 7*24 hours normal unmanned inspection.

The invention relates to the field of artificial intelligence, and provides a control method for bipartite consistency of a multi-agent system based on a virtual leader, a control device for bipartite consistency of the multi-agent system based on the virtual leader, electronic equipment and a computer readable storage medium. The method comprises the following steps: setting a virtual leader; constructing a fixed time containment feedback control protocol of each agent; constructing a bipartite consistency error of each agent according to a fixed time containment feedback control protocol; and according to the bipartite consistency error, determining the convergence time upper bound of the multi-agent system for realizing the bipartite consistency within the fixed time based on the fixed time containment feedback control protocol. According to the method and the device, the technical effects of ensuring the convergence speed and the communication robustness of the system and saving communication resources can be realized.

The present application relates to unmanned vehicle group cooperative control technical field, specifically relates to a kind of unmanned car group LSTM-MPC cooperative formation control method for complex environment in open country, including S1 training LSTM neural network prediction model, S2 realizes the cooperative formation control of virtual leader method based on LSTM-MPC algorithm, S3 is coordinated by virtual leader method, and the control planning of virtual leader car and real following car, the present application adopts LSTM data-driven model, replaces traditional physical model, solves the low state prediction accuracy and trajectory deviation problem caused by model mismatch, reduces the calculation complexity, improves real-time response speed, meets the efficient demand of large-scale vehicle group cooperation.Combined with virtual leader architecture and rolling cycle mechanism, the dynamic self-adaptive adjustment of target trajectory is realized, the instability of formation and cooperative response lag caused by sudden situation such as topographic mutation are avoided, the consistency of mapping is guaranteed, and the defects in the prior art, such as strong model dependence, poor field adaptability, insufficient real-time performance and weak formation cooperative ability, are overcome.

The application discloses a formation control method and device for realizing multi-target tasks by cooperation of a UAV cluster. The formation control method comprises the following steps: acquiring initial information of multiple target tasks and basic information of a UAV cluster for executing the multiple target tasks; obtaining cluster grouping data of the UAV cluster when executing the multiple target tasks according to the initial information; obtaining task allocation data of each cluster group according to the cluster grouping data and the initial information; obtaining a reference path of each UAV cluster according to the task allocation data, the cluster grouping data and the initial information; setting a virtual leader based on the reference path, and obtaining expected position and speed data of each UAV for different target tasks according to the reference path and the virtual leader; and obtaining a formation shape of each UAV after reaching a corresponding expected position at a corresponding expected speed according to the basic information of the UAV cluster, the expected position and speed data of each UAV.

The invention discloses a distributed commercial load cluster information security convergence system oriented to denial of service network attack. The system obtains a temperature track of a virtual leader air conditioner when a follower air conditioner is subjected to DoS attack through a preset track evolution model of the virtual leader air conditioner; and a distributed tracking control law of each follower air conditioner is constructed through an auxiliary sliding mode function, the distributed tracking control law is combined with a thermodynamic model, the temperature trajectory of the follower air conditioner is controlled, and the temperature trajectory of the virtual leader air conditioner when the follower air conditioner is subjected to DoS attack is tracked. The method can ensure that the air conditioner load cluster can stably track the temperature track of the virtual leader air conditioner.

The application discloses a multi-unmanned system formation control method based on specified time convergence, and belongs to the field of unmanned system control. The application solves the problem that multi-unmanned systems cannot converge to a common target state at a specified time under arbitrary initial states and dynamically changing environments. The method comprises the following steps: step one, establishing a multi-unmanned system kinematics model containing position, velocity and control input information; step two, regarding each unmanned system as a follower, taking the tracking error of each follower relative to a target position and the tracking error of each follower relative to a target velocity as state variables in a multi-unmanned system formation model of actual followers-virtual leaders, and then designing a formation controller according to the state variables and a reference differential convergence function; and step three, designing a final formation controller of the multi-unmanned system with disturbance based on a sliding mode control and the formation controller designed in step two. The method can be applied to multi-unmanned system formation control.

The application discloses a kind of dual unmanned aerial vehicle anti-interference cooperative hoisting control method, system, equipment and medium, comprising: obtaining the actual state information of dual unmanned aerial vehicle and the desired state information of virtual leader;According to desired state information, the desired position information of dual unmanned aerial vehicle is calculated according to pre-set dual-machine cooperative decoupling control rule;With desired position information as input, based on the extended state observer and nonlinear anti-interference controller constructed in advance, the control input information of each unmanned aerial vehicle is output, so that the power system controls dual unmanned aerial vehicle anti-interference cooperative hoisting load according to control input information.The application introduces virtual leader, solves the problem of sling tension imbalance caused by independent trajectory planning;Based on dual-machine cooperative decoupling control rule, the problem of unmeasurable load pose caused by flexible sling is solved, and the extended state observer and nonlinear anti-interference controller are used to realize real-time estimation and active compensation for compound disturbance such as wind disturbance and sudden load.

The application discloses a kind of cluster unmanned plane fixed time quick adaptive fault-tolerant cooperative control method, first, design a kind of elasticity distributed fixed time observer based on topology switching signal, for accurately estimating virtual leader state and weakening the influence of denial-of-service attack.Second, by combining power integrator technology with topology switching signal, for follower unmanned plane affected by unknown actuator fault, construct fixed time adaptive fault-tolerant cooperative control protocol, so that the cluster unmanned plane system can still realize trajectory tracking in fixed time under the condition of actuator fault and denial-of-service attack coexistence.Finally, by radial basis function neural network, online approximation of composite nonlinear disturbance is realized, more accurate cooperative control is realized.The application can be applied to cluster unmanned plane formation fault-tolerant cooperative control under actuator fault and denial-of-service attack.