125 results about "Virtual leader" patented technology

The present disclosure provides a weakly-centralized frequency regulation control method of a charge station cluster based on virtual leader and a medium. Firstly, based on the control strategy of the virtual synchronous generator and the requirements of the electric vehicles and the charge stations, an architecture of the virtual synchronous generator of the electric vehicles and the charge stations is established. Secondly, based on the control strategy of the collaborative topology design of multiple charge stations, a virtual leader is determined and a weakly-centralized consistency algorithm is designed. Finally, a control strategy of the collaborative frequency regulation of the charge station cluster is proposed to achieve the weakly-centralized frequency regulation control of the charge station cluster.

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 an unmanned surface vessel cluster system finite time distributed formation method, which not only can ensure that an unmanned surface vessel system reaches an expected formation mode in finite time, but also can ensure that the system speed and the formation error always meet the time-varying constraint requirement in the whole operation period. The method comprises the following steps: establishing kinematics and dynamics models of the three-degree-of-freedom unmanned surface vessel; using a smooth function to approximate saturation constraints of the system, and combining with the fault model to establish a new system dynamic model limited by driver faults and saturation constraints; designing a virtual control law, also known as a kinematics guidance law; designing a parameterized channel rate of the virtual leader; designing a finite time distributed formation controller; and designing an uncertain compensation adaptive law. The method can design a time-varying formation mode and a time-varying constraint function according to the needs of a user, dynamically adjusts the formation form of multiple unmanned surface vessels, and guarantees that the speed and formation tracking errors are not deviated from a specified constraint set all the time.

The invention discloses a finite-time active-disturbance-rejection control method for a multi-unmanned-aerial-vehicle hanging transportation system. According to the finite-time active-disturbance-rejection control method, a finite-time super-spiral sliding-mode observer is used for carrying out observation compensation on load errors and lumped disturbance of the load errors, a finite-time sliding-mode controller is constructed, total tension for controlling load movement is determined, and an optimal tension distribution scheme is solved. External disturbance is introduced, a load is taken as a virtual leader, a leader following cluster model is constructed, a finite time reduced-order proportional differential observer and a finite time controller are designed, formation finite time control is carried out, and an expected trajectory of each unmanned aerial vehicle is determined; an actuator fault model and a virtual control quantity are introduced, an unmanned aerial vehicle dynamics model is constructed, and a lumped disturbance reconstruction state error system is introduced; and designing a finite-time reduced-order generalized parameter estimation observer and a finite-time nonsingular terminal integral sliding mode fault-tolerant controller, carrying out unmanned aerial vehicle position loop control and attitude loop control, and realizing finite-time active-disturbance-rejection control of the multi-unmanned aerial vehicle hanging transportation system.

The invention provides an air-ground unmanned cluster system cooperative formation control method driven by reinforcement learning. Establishing a dynamic model for the air-ground unmanned cluster system; a distributed predefined time observer is constructed to estimate the state of a virtual leader, and a state reference is provided for cooperative formation tracking control; and reconstructing a dynamic model of the augmented air-ground unmanned cluster system, and further constructing a control gain matrix. Segmented constant initial excitation is applied to the augmentation system, state data of early-stage operation of the augmentation system is collected and stored, then an initial stability control strategy is obtained by using a data driving method according to the early-stage operation data of the air-ground unmanned system, and finally, the stability of the air-ground unmanned system is improved based on an offline strategy reinforcement learning algorithm and the initial stability control strategy based on the data. And learning an optimal formation tracking controller to realize optimal formation tracking control of the air-ground unmanned system. According to the invention, under the condition that a system model is unknown, the optimal time-varying formation tracking control of the air-ground unmanned cluster system can be realized according to complex task requirements.

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.

A method and system for controlling collision avoidance formation of mobile robots subject to perturbations and communication limitations. [Solution] A formation system model of multiple mobile robots is constructed, the total perturbation is estimated, a reference trajectory of the first virtual leader in the formation of mobile robots is set, a corresponding desired formation is formed based on the set desired distance and desired angle between the robots, distance error and angle error during the formation are created, and the created distance error and angle error are limited so that they are always within the corresponding specified limits using specified performance control technology, and a perturbation suppression formation system controller is constructed using dynamic surface control technology according to the distance error, angle error and estimated total perturbation.

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 method is mainly applied to the technical field of intelligent robots. The invention discloses a robot group control method, system and device capable of walking randomly and a medium, and the method comprises the steps that a robot group is divided into a plurality of robot groups, and each robot group comprises a plurality of robots; determining a virtual leader in each robot group; aiming at each robot group, each robot moves by taking the virtual leader as a target; each robot group performs search action in a random walk mode; and when the robot group finds the target object in the search action, each robot in the robot group moves by taking the target object as a target so as to execute a hunting task aiming at the target object. According to the method and the device, the task of exploring and hunting multiple targets can be executed, and the task execution efficiency is improved.

The invention provides a finite time cooperative tracking control method based on an adaptive RBF neural network, and belongs to the technical field of networked multi-agent control strategies. Constructing a dynamic mathematical model of a high-order all-drive uncertain nonlinear multi-agent system comprising a virtual leader and a follower; according to a cooperative tracking control target and uncertain items in the system, constructing an error dynamic system comprising an adaptive RBF neural network estimation compensation item; designing a finite time integral sliding mode surface based on a high-order all-drive system theory; designing linearization parameters of a finite time integral sliding mode surface based on a pole assignment method according to system dynamic performance and finite time convergence requirements, and obtaining a finite time integral sliding mode controller; and designing a self-adaptive updating law of an upper bound of an RBF neural network weight and an approximate error, and substituting the network weight and the approximate error into a finite time integral sliding mode controller to realize cooperative tracking control of finite time.

The invention discloses a method for realizing formation trajectory tracking by a multi-agent system considering delay and packet loss, and belongs to the field of networked multi-agent formation control. The method is characterized by comprising the following steps: establishing mathematical models of virtual leaders and followers of the networked multi-agent system; performing trajectory planning on the virtual leader; the problems of target unreachable and local minimum are solved; designing a state observer according to outdated state information of the intelligent agent; designing a predictive control protocol by using an estimated value obtained by the observer; deriving a closed-loop error system according to the predictive control protocol, and obtaining conditions satisfied by a feedback gain matrix of the predictive control protocol; and substituting the feedback gain matrix into a predictive control protocol, and realizing leadership following formation trajectory tracking control by using the predictive control protocol. According to the invention, the influence of time delay and data loss in the network on the control system is overcome, so that the networked multi-agent system achieves the same control effect as a local control system.

The invention provides a predetermined time distributed optimal inclusion control method for an unmanned aerial vehicle cluster, and belongs to the technical field of collaborative decision of an unmanned cluster system. The method comprises the steps that unmanned aerial vehicles in an unmanned aerial vehicle cluster are divided into virtual leader unmanned aerial vehicles and follower unmanned aerial vehicles; according to the single integral linear model of the virtual leader unmanned aerial vehicle, generating a preset formation pattern through a preset time distributed optimization theory; constructing a nonlinear model of a follower unmanned aerial vehicle in the unmanned aerial vehicle cluster; and designing an inclusion control protocol of the follower unmanned aerial vehicle based on a distributed inclusion control algorithm according to the nonlinear model of the follower unmanned aerial vehicle, so that the follower unmanned aerial vehicle converges to a preset formation. Through a distributed optimal formation control algorithm and a distributed inclusion control algorithm, a virtual leader unmanned aerial vehicle formation generation strategy within a preset time is realized, follower unmanned aerial vehicles converge to a preset formation, and thus unmanned aerial vehicle cluster security cooperative control under a complex sea condition is completed.

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 provides a fully-distributed unmanned aerial vehicle robust formation control method based on minimum information amount, and the method comprises the following steps: employing a second-order system as a kinematic model of an unmanned aerial vehicle, and building a state space model of an unmanned aerial vehicle system; establishing a state space model of the virtual leader system to describe a global flight path vector of the unmanned aerial vehicle; describing a communication network of the unmanned aerial vehicle group by using a directed graph; designing an output-based adaptive distributed observer to estimate virtual leader system information required by each unmanned aerial vehicle; based on the output information of the observer, constructing an asymptotic internal model to process uncertain parameters in the virtual leader system; an asymptotic internal model is combined with a dynamic state feedback controller, an unmanned aerial vehicle robust formation flight controller is constructed, and the unmanned aerial vehicle robust formation flight controller and an output-based adaptive distributed observer jointly control robust formation flight of a full-distributed unmanned aerial vehicle group. And the robustness and the distributed performance of the formation flight of the unmanned aerial vehicles are improved.

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 multi-unmanned ship formation fault-tolerant control method with input / state quantification, and the method comprises the steps: obtaining the sea condition information of a surrounding environment and other surrounding ships, and building a trajectory control mathematical model of an under-actuated unmanned ship formation; a uniform quantizer is adopted to quantize control input and state variables in the control system; under the condition that virtual leader information is known, estimating quantization state information of each USV and uncertain items existing in the model by using an ESO technology; a hierarchical design method is adopted, a kinematics guidance law and a dynamics quantization tracking control law are designed, a linear model is introduced to describe a quantization process, and a designed controller does not need priori information of quantization parameters any more; and the stability of fault-tolerant control of the multi-unmanned ship formation with input / state quantification is proved by using an input-to-state stability theory.

The invention relates to the field of area coverage control methods, and discloses a multi-agent system channel type area coverage control method based on arc length, which comprises the following steps: S1, target area division: dividing a channel type target area into a plurality of sequential sub-areas based on an arc length division method; s2, designing a distributed controller of a virtual leader agent, wherein the distributed controller of the virtual leader agent ensures that the arc length of a coverage area of each group of agents is in direct proportion to the number of the group of agents; and S3, designing an individual intelligent agent distributed controller, and enabling the intelligent agent to realize sequential team coverage control on the area S by combining the individual intelligent agent distributed controller with a distributed controller of a virtual leader intelligent agent. The distributed controller designed by the invention enables the intelligent agent to adjust the coverage area of the intelligent agent in real time according to the change of the actual environment.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a UWB-based finite time unmanned aerial vehicle cooperative control method, which comprises the following steps: acquiring relative position data of an unmanned aerial vehicle; designing a virtual piloting target, and calculating the relative position expectation of each unmanned aerial vehicle at each moment; designing a finite time controller model; designing a trajectory tracking controller model; an unmanned aerial vehicle cooperative control system is divided into an outer ring and an inner ring for respective control. According to a task flight planning application data structure, it is guaranteed that a certain distance is kept during cooperation of multiple unmanned aerial vehicle formations, nonlinear control convergence of relative trajectory errors is achieved by designing a finite time controller, the unmanned aerial vehicles are controlled to be converged to be kept at the relative distance within set time, and the unmanned aerial vehicle formations are controlled to be coordinated. Therefore, formation operation in a complex scene is realized. According to the invention, the unmanned aerial vehicle can quickly reach a task target area and realize formation keeping or changing in finite time, and task development is supported.

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 an unmanned aerial vehicle formation obstacle avoidance control method based on a bird survival pressure simulating mechanism. The method comprises the following steps: step 1, constructing an unmanned aerial vehicle and virtual leader motion control model; 2, designing an unmanned aerial vehicle formation controller; 3, designing an obstacle avoidance controller based on a bird survival pressure mechanism; 4, designing an unmanned aerial vehicle formation obstacle avoidance controller; 5, designing a virtual leader controller; and 6, updating the states of the unmanned aerial vehicle and the virtual leader model. The method has the advantages that 1) the problem that the unmanned aerial vehicle cannot bypass an obstacle when directly facing the obstacle in a traditional artificial potential field method is solved; (2) a consistent formation method with a virtual leader is adopted, in practical application, a ground station can serve as the virtual leader, the relative position and formation between the unmanned aerial vehicles can be effectively kept, and rapid and stable switching of the formation can be achieved; and 3) on the premise of ensuring that the formation of the unmanned aerial vehicles is basically kept, efficient obstacle avoidance of the unmanned aerial vehicles in the formation state can be realized.

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 is suitable for the field of intelligent control, and provides an optimal time-varying lag formation control method for a high-order nonlinear multi-agent system, and the method comprises the steps: firstly, constructing a mathematical model and a virtual leader model of the high-order nonlinear multi-agent system with external interference and unknown system dynamics; secondly, designing an interference observer and a neural network recognizer to compensate the influence of external interference and unknown system dynamics on a single agent; then, an optimal time-varying lagging formation control strategy is designed by using a sliding mode control method and a reinforcement learning technology, and the controller not only can realize actual time-varying lagging formation of a multi-agent system, but also can minimize a performance index function; finally, the effectiveness of the proposed control scheme is verified through a multi-agent system composed of four unmanned ships.

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.

An iterative learning fault-tolerant consistency control method for a multi-flexible-mechanical-arm system comprises the following steps that S1, a directed communication topological structure is constructed, flexible mechanical arms serve as followers, and a virtual leader is established; a mathematical model of the multi-flexible mechanical arm system is established based on the Hamiltonian principle; s2, constructing a finite time observer for estimating the angular displacement and the angular velocity of the virtual leader for each follower of the multi-flexible mechanical arm system; s3, designing an iterative learning rule, a parameter adaptive rule and a control signal of the multi-flexible mechanical arm system based on the virtual leader state estimated by the finite time observer in combination with an actuator fault model and an event triggering rule based on sampling data; according to the control method, fault-tolerant consistency control design based on a sampling data event triggering mechanism is carried out in combination with an estimated value of a finite time observer, so that communication resources are saved, and meanwhile, consistency control of the system is realized.

The present invention relates to the technical field of collaborative formation control, and discloses a method for collaborative formation control of air-sea heterogeneous unmanned clusters based on sliding mode consistency. The method comprises constructing a kinematic model of an air-sea heterogeneous unmanned cluster including multiple types of intelligent agents, and constructing a leader-follower model according to a set virtual navigator; constructing an air-sea heterogeneous unmanned cluster formation tracking error model according to the leader-follower model; and establishing an air-sea heterogeneous unmanned cluster fixed-time formation control law based on sliding mode consistency according to the air-sea heterogeneous unmanned cluster formation tracking error model to perform fixed-time collaborative formation control. The present invention can improve the formation control efficiency and environmental adaptability of heterogeneous unmanned clusters.