38 results about "Coverage control" patented technology

The invention relates to the technical field of communication, and discloses a sea area wireless network coverage method and device and a computer readable storage medium, and the method comprises the steps: obtaining the historical link performance, real-time marine environment data and business load information of a target sea area; constructing a sea surface electromagnetic wave propagation attenuation dynamic prediction model based on a gated circulation unit; and in combination with the prediction result and the service demand, jointly optimizing the base station transmitting power, the antenna beam pointing angle and the subcarrier resource allocation, and issuing a regulation and control instruction. The system comprises a data acquisition module, a propagation modeling module, a resource scheduling module and an instruction execution module. According to the invention, through deep fusion of marine environment physical field perception and wireless communication system control, a dynamic coverage regulation and control mechanism driven by a sea condition is established; the provided sea surface electromagnetic wave propagation attenuation dynamic prediction model can pre-judge the signal attenuation trend under the complex sea condition in advance, so that network resource scheduling has perspectiveness.

The invention discloses a Unicycle multi-agent dynamic coverage control method based on safety reinforcement learning, and the method comprises the steps: firstly, carrying out the modeling of a Unicycle agent, an anisotropic sensor, and a multi-agent system dynamic coverage control task; then, designing corresponding constraining force according to safety requirements such as input limitation and obstacle and collision avoidance of Unicycle so as to design a safety protection mechanism, and correcting a control instruction of the intelligent agent when the intelligent agent is about to do unsafe action so as to ensure the safety of the intelligent agent in a dynamic coverage process; and finally, training the dynamic coverage control security decision model in cooperation with a multi-agent deep reinforcement learning algorithm, improving the adaptive capacity of the dynamic coverage control security decision model to a variable environment based on an observation coding mode of state compression, and executing the dynamic coverage control security decision model to complete Unicycle multi-agent dynamic coverage control.

The invention discloses a multi-unmanned aerial vehicle cooperative search and coverage optimization method based on an improved Lloyd algorithm, and is suitable for a target search task in a dynamic environment. Firstly, target distribution is perceived and estimated in real time by using a probability hypothesis density filter, and a target probability map is dynamically updated, so that the response capability and search precision of a system to target state change are improved; secondly, a multi-graph fusion mechanism is adopted, a target probability map, an uncertainty map and a search pheromone map are subjected to dynamic weighted integration, priority sharing and updating of key area information are achieved, and the cooperation efficiency and the communication resource utilization rate among multiple unmanned aerial vehicles are improved; and finally, based on an improved Lloyd algorithm, introducing a multi-step prediction mechanism and a direction-guided centroid updating strategy, optimizing search path generation, and preventing the path from being converged to a low-value region. Through the method of the invention, the system can realize adaptive and efficient search and coverage control in a complex dynamic environment, and stability, real-time performance and overall robustness of task execution of multiple unmanned aerial vehicles are significantly improved.

The invention discloses an Internet of Things terminal remote control method based on low earth orbit satellite communication, and belongs to the technical field of low earth orbit satellite communication. By establishing a coverage control relationship between the Internet of Things terminal and the low-orbit satellite link, generating a distribution control behavior set and recording connection delay, scattered communication behaviors can be converted into traceable associated data, and matching analysis of the terminal and the link is facilitated; a data matrix is constructed and normalized based on time delay, a feature contour is extracted after the data matrix is converted into a data portrait, and identification of multi-terminal common-frequency behaviors is simplified by utilizing spatial relevance of image features so as to quickly solve the problem of common-frequency interference concealment; and identifying a common-frequency behavior through contour overlapping, and quantifying a link importance score to optimize terminal link selection. According to the method, the problems that traditional low-orbit satellite link allocation is static and common-frequency interference is difficult to control are solved, the link resource utilization rate and the terminal communication reliability are improved, and the method is suitable for remote control of wide-area Internet of Things scenes such as oceans and deserts.

The application relates to integrated chip testing technology and discloses a test method for an SOC system, which comprises the following steps: deploying a test scene on an SOC system and generating a first test case corresponding to the test scene, wherein the test scene comprises at least one of a verification IP, a virtual machine compiler and an FPGA platform compiler; determining a test function according to a test requirement and generating a second test case corresponding to the test function according to the first test case, wherein the test function comprises at least one of a connection line detection, a timing detection, simulation information control, simulation waveform control, coverage control and DUT code control; and executing all the second test cases on the SOC system to obtain a test result. The application further discloses a test device for the SOC system, a computer device and a computer readable storage medium. The application aims to improve the test efficiency of the SOC system.

The invention discloses an intelligent vehicle system based on single Beidou multi-source data acquisition, which belongs to the technical field of non-electrical variable control or adjustment systems and comprises six series modules, namely a multi-source data acquisition module, a space-time alignment module, a multi-source fusion module, a scene adaptive sensing and path generation module, a motion control and execution module and an emergency obstacle avoidance and safety control module. According to the system, multi-source data space-time alignment is realized by taking single Beidou GNSS time service data as a unified reference, credibility evaluation is performed on a single Beidou positioning state, a fusion weight is dynamically adjusted, an adaptive driving path is generated in combination with positioning credibility, closed-loop feedback is formed by motion control, and an emergency obstacle avoidance module can cover a control instruction at the highest priority. By the adoption of the system, self-adaptive fusion of multi-source sensing information is achieved only depending on a single Beidou positioning signal, the sensing control continuity of the system is guaranteed, Beidou positioning participates in operation decision, and the operation stability and safety of an intelligent vehicle in a complex environment are improved.

The application discloses a kind of multi-layer game reinforcement learning methods for intelligent group area coverage control, comprising: each intelligent agent in intelligent group is mapped as game player, and the task target of intelligent agent is combined to construct revenue evaluation mechanism, and form group game model;Based on the physical capability constraint of intelligent agent, construct perception model and communication model, design coverage efficiency, running safety, energy efficiency and communication collaboration evaluation index, and integrate as the vector revenue function of intelligent agent;TD3 model is used as the game player role of intelligent agent, and the association of reinforcement learning and group game is established;Multi-layer semi-distributed game reinforcement learning framework is constructed, and environment interaction is carried out, to solve the intelligent group area coverage control strategy satisfying Pareto Nash equilibrium.The application realizes the balance of individual and collective benefits, improves the calculation efficiency through semi-distributed iterative algorithm, and adapts to the solution demand of large-scale complex system.

The application relates to the technical field of multi-agent cooperative coverage control, and discloses a multi-agent cooperative control method, device and equipment and a storage medium, the method comprising the following steps: constructing a first / second type supervision area according to initial / primary position coordinates of the first / second type agent; constructing a common supervision area according to the first type supervision area and the second type supervision area, and determining optimal / advantage target positions of the first / second type agent according to all area points in the common supervision area; updating the first / second type supervision area when the first / second type agent moves towards the optimal / advantage target position; returning to the step of constructing the common supervision area according to the first type supervision area and the second type supervision area according to the updated first / second type supervision area until a coverage loss value corresponding to the common supervision area meets a preset optimal coverage loss value. The application aims to improve the coverage capability of heterogeneous agent cooperative control.

In order to reduce power consumption, an access node may turn off transmissions from one or more rows or columns of antennas in a mMIMO array. To help prevent the beam from overshooting (i.e., going beyond) an intended area of coverage when the access node turns off transmission by one or more rows, the access node also increases the electrical down tilt of the beam (i.e., angle of depression) to help contain the beam within its intended area of coverage. To help prevent problems with SSB beam selection and / or beam switching, when the access node turns off transmission by one or more columns, the access node reduces the number of SSB beams that are transmitted while sweeping SSBs over the sector thereby reducing the overlap of the (now) wider SSB beams.

A dental triage and clinical risk assessment system (100), the system (100) comprising: a first user device (102) configured to receive patient-related dental information for remote dental assessment; a first user interface (104) within the first user device (102) that is configured to guide the patient's interaction by presenting structured symptom questionnaires, image acquisition instructions, and status notifications; a communication network (110) that is connected to the first user device (102) and configured to securely transmit patient-related dental information and control signals; a processing unit (112) connected to the first user device (102) via the communication network (110) and configured to perform automated dental triage and clinical risk assessment through coordinated data analysis decision logic and routing operations, wherein the processing unit (112) comprises: a data acquisition module (114) configured to receive patient-related dental information from the first user device (102); a data preprocessing module (116) configured to validate, normalize and structure the received dental information for analytical processing; a triage intelligence module (124) configured to analyze the structured dental information to generate a quantified urgency score and risk classification level using combined analytical logic; a decision support module (130) configured to assign the urgency score and risk classification level to a recommended dental care pathway; a nursing navigation module (134) configured to generate routing instructions corresponding to emergency referrals, scheduled consultations, teleconsultations or automated guidance; a learning and analysis module (144) configured to update internal analytical parameters based on confirmed clinical results; a storage unit (154) connected to the processing unit (112) and configured to store patient data, analytical results, priority points, routing decisions and result feedback for continuous system operation; a second user device (158), connected to the processing unit (112) via the communication network (110) and configured to receive triage outputs and recommendations for care pathways; and a second user interface (160) in the second user device (158), configured to display risk indicators, urgency points, patient data summaries and override controls for interaction with the clinician.

The invention discloses a multi-agent exploration and coverage control method based on state-based potential gaming and near-end strategy optimization, and belongs to the technical field of automatic control. According to the method, aiming at the problems of low task cooperation efficiency and difficulty in strategy convergence of multiple agents in an unknown or dynamic environment, exploration and coverage tasks are modeled as a generalized state-based potential game, a global potential function and an individual utility function are defined, and a state space, an observation space, an action space, a state transfer function and a reward function are constructed. Under a centralized training and distributed execution framework, a near-end strategy optimization algorithm based on potential game increment constraint is designed, a reward shaping mechanism and an epsilon-annealing posterior constraint mechanism are introduced, and efficient updating and stable convergence of the strategy are guided. Through two-dimensional discrete grid simulation scene training, the system can significantly improve the exploration efficiency and the coverage effect under the conditions of limited communication and local perception. The method can be widely applied to emergency disaster relief, environment monitoring and unmanned cluster tasks.

The application provides a high-pole lamp lighting intelligent control system and method, which comprises an intelligent lighting control cloud box and a lighting control management system, and the intelligent lighting control cloud box is in wireless communication connection with the lighting control management system. The application can realize intelligent monitoring control and fine management of high-pole lamp lighting by operating a lighting management platform, a mobile phone APP and the intelligent lighting control cloud box to send instructions for separately controlling, batch controlling and plan controlling the on-site lamps, and also can control the on-site lamps by time period and area. Meanwhile, the application can realize functions such as a map function, equipment inspection, lighting control, power over-reading, gateway inspection, equipment time correction, electricity price clock, batch parameter adjustment, energy efficiency management, alarm and the like, and traffic flow monitoring, safety monitoring, light intensity and coverage control functions based on image recognition and neural network technology, which has important significance for improving lighting efficiency, reducing energy consumption and realizing intelligent management of urban traffic.

The invention provides a vehicle control method, system and device based on reinforcement learning and a medium. The method comprises the steps that vehicle state information and reference track information of a target vehicle at the current moment are acquired; performing rolling optimization solution through a model prediction control algorithm to obtain a control sequence of a coverage control time domain corresponding to the current moment; constructing a strategy network for inputting the reinforcement learning state vector into a pre-trained flexible action-evaluation network to obtain a front wheel steering angle correction amount at the current moment; and carrying out superposition processing on the first-item front-wheel rotation angle increment, the front-wheel rotation angle correction and the front-wheel rotation angle control quantity at the previous moment in the control sequence to generate the front-wheel rotation angle control quantity at the current moment. According to the method, the controller does not completely depend on a fixed vehicle dynamics model any more, so that the technical problem that the performance is reduced or even unstable due to the fact that the model is inaccurate in an existing algorithm is effectively solved, and high-precision trajectory tracking can still be kept under the complex and changeable real driving working condition.

The invention discloses a cross-community point settlement and reserve fund coverage control method and device based on double account books and a state channel, equipment and a storage medium. According to the method, point cross-domain liquidation and rapid settlement among different community nodes are realized by establishing a multi-account-book cooperation mechanism; a state channel technology is adopted to optimize transaction time delay and storage overhead; dynamically adjusting a reserve fund proportion according to the risk parameters so as to realize safe hosting and real-time liquidation of integral assets; and the authenticity and traceability of the data are ensured through the encryption and traceability module. The method can improve the operation efficiency and risk prevention and control capability of a community point system, and is suitable for multi-scene application of smart communities, commercial alliances and the like.

The application discloses a stratosphere airship cluster area covering control method based on a clustering artificial potential field method, relates to the automatic control technical field, and comprises the following steps: establishing a stratosphere airship ground covering channel model, and distributing covering targets; obtaining expected covering deployment center positions of each cluster unit based on a clustering method; establishing a dynamic artificial potential field to obtain expected positions of the stratosphere airship cluster; establishing a stratosphere airship dynamics model, and designing a stratosphere airship dynamic tracking controller to track the expected positions of the stratosphere airship cluster. Therefore, the above method can realize adaptive dynamic covering of the stratosphere airship cluster to ground targets, reduces the influence of environmental wind on the stratosphere airship cluster covering task, establishes a dynamic artificial potential field unified framework, greatly reduces the complexity of the task, and effectively realizes tracking of the expected positions of the stratosphere airship cluster by designing the stratosphere airship dynamic tracking controller.

The invention discloses a reconfigurable intelligent surface enhanced coverage control method, device and equipment for a virtual power plant and a medium, which are used for solving the technical problem that the reconfigurable intelligent surface enhanced coverage control effect of the virtual power plant is poor. Comprising the following steps: collecting state information of each node in a virtual power plant, and generating a scheduling weight and a partition number of each node; calculating an estimated communication benefit value of each node, and generating a service assignment variable in combination with the scheduling weight; constructing a partition allocation scheme according to the service assignment variable and the number of partitions, and dividing the reflection unit to a plurality of sub-panels; calculating phases of the incident signal and the emergent signal of each reflection unit, and generating a reflection matrix; determining an emission vector according to the reflection path channel and the scheduling weight of each reconfigurable intelligent surface after adjustment of the reflection matrix; performing time slot resource allocation on each reconfigurable intelligent surface according to the service assignment variable and preset geographic sector mapping; and performing data transmission according to the transmission vector and the time slot resource allocation scheme.

The invention relates to the technical field of intelligent control, in particular to a compressor unit working noise control system based on data analysis. The compressor unit working noise control system based on data analysis comprises a sound pressure segmentation demarcation module, a frequency band change extraction module, a sound energy concentration drifting module, a target frequency band locking module and an absorption execution triggering module. According to the method, fine division of a sound pressure trend in operation is realized by constructing a sound pressure change boundary, a frequency abrupt change region is extracted, a drift path with concentrated sound energy is captured, a target frequency position is screened according to frequency change direction consistency and time continuity, and a focusing frequency is further accurately corresponding to a control frequency band; the shielded area is adjusted in a linkage mode to achieve directional intervention and coverage control over a key noise propagation path, the frequency locking precision, the energy focusing stability, the dynamic response sensitivity and the synergistic effect efficiency of sound absorption shielding are improved, and therefore an active noise control system based on the characteristic evolution trend is established.

The invention belongs to the technical field of robot control and distributed autonomous systems, and particularly relates to an autonomous robot coverage control system based on multi-Jetson collaboration, which is realized based on an ROS2 robot operating system and a multi-Jetson embedded computing platform, and comprises the following steps: multi-sensor data acquisition; carrying out pose fusion and positioning; performing pose processing and neighbor recognition; neighbor detection and event judgment; performing data synchronization and cyclic scheduling; dynamically adjusting the sensing radius; carrying out actuarial calculation and weighted centroid calculation on the Voronoi region; control law calculation and saturation constraint; issuing a target point and executing a path; asynchronous and energy-saving control is realized; wherein the ten stages are independently executed on a local ROS2 node of each Jetson trolley, the whole system operates in an asynchronous distributed mode, and autonomous coverage control can be achieved without a central control node. According to the invention, the problems of complex synchronization, high energy consumption, communication dependence and the like in the existing multi-robot distributed coverage control can be solved.

Cover for covering an opening in a housing of a control unit, wherein the cover (30) is made of a metallic material, has a bottom section (32) and an edge section (34), wherein the edge section (34) extends obliquely from the bottom section (32) and has a number of tabs (36), wherein a bending area (38) is provided in the edge section (34) and a groove (40) is formed in this bending area, in the area of ​​which a wall thickness of the tabs (36) of the edge section (34) is reduced.

The embodiment of the invention provides a robot safety decision-making system and method based on uncertainty perception, and is applied to the technical field of robot control and artificial intelligence crossing. The method comprises an intelligent sensing module, a safety monitoring module and an execution module, the intelligent sensing module runs on a first computing platform, is internally provided with an uncertainty sensing neural network, processes a robot environment sensing task and outputs a system state, a sensing recognition result and a corresponding uncertainty score; the security monitoring module runs on a physically independent second computing platform, receives the data through a security communication interface, determines a security level by fusing a local physical sensor data decision and outputs a security control instruction; a main actuator controller and a safety actuator interface in the execution module receive a control instruction and a safety instruction respectively, and the safety actuator interface has the highest control priority and can cover the control instruction. According to the method, early warning can be performed in time and preventive measures can be taken when the deep learning model perceives that the deep learning model is unreliable.

The application discloses a 5G base station indoor coverage control method and system, relates to the field of 5G base station indoor coverage control, and is used for effectively controlling system energy consumption while ensuring key service communication performance, and comprises the following steps: acquiring a wireless signal measurement report of a user terminal in a base station coverage area and a probe signal echo characteristic of a base station itself; the probe signal echo characteristic comprises an echo time delay and strength; fusing the wireless signal measurement report and the probe signal echo characteristic, constructing and updating a real-time radio frequency environment map; comparing the real-time radio frequency environment map with a benchmark map, identifying physical environment changes and inferring obstacle characteristics; adjusting a beamforming direction and transmission power according to the physical environment changes and the obstacle characteristics; identifying key services, improving the priority of the communication quality of the key services when the beamforming direction and the transmission power are adjusted, and simultaneously coordinating and suppressing interference to adjacent areas.

The invention discloses a 5G base station indoor coverage control method and a 5G base station indoor coverage control system, which relate to the field of 5G base station indoor coverage control, are used for effectively controlling system energy consumption while ensuring key service communication performance, and comprise the following steps: acquiring a wireless signal measurement report of a user terminal in a base station coverage area and a detection signal echo characteristic emitted by a base station, the echo characteristics of the detection signal comprise echo time delay and intensity; a wireless signal measurement report and a detection signal echo characteristic are fused, and a real-time radio frequency environment map is constructed and updated; comparing the real-time radio frequency environment map with the reference map, identifying physical environment change and deducing obstacle characteristics; adjusting the beam forming direction and the transmitting power according to the physical environment change and the obstacle characteristics; the key service is identified, and when the beam forming direction and the transmitting power are adjusted, the priority of the communication quality of the key service is improved, and the interference to the adjacent area is coordinated and suppressed.

The application discloses a low-orbit satellite communication-based remote control method for Internet of Things terminals, and belongs to the technical field of low-orbit satellite communication. By establishing a coverage control relationship between an Internet of Things terminal and a low-orbit satellite link, a set of distribution control behaviors is generated, and a connection delay is recorded, so that scattered communication behaviors can be converted into traceable associated data, and matching analysis of the terminal and the link is facilitated; a data matrix is constructed based on the delay and normalized, a feature profile is extracted after the data matrix is converted into a data portrait, the spatial correlation of the image features is utilized to simplify the identification of multi-terminal co-frequency behaviors, and the co-frequency interference concealment problem is quickly solved; the co-frequency behaviors are identified through profile overlap, and the link importance score is quantified to optimize the selection of the terminal link. The application solves the problems of static distribution of traditional low-orbit satellite links and difficult control of co-frequency interference, improves the link resource utilization rate and the terminal communication reliability, and is suitable for remote control in wide-area Internet of Things scenes such as oceans and deserts.

The invention provides a whole-staff non-inductive positioning method and system for a large-range construction site in order to solve the problems that in the prior art, limitation still exists in the aspects of precision, response speed and coverage control, and high-precision, large-range and low-intervention positioning requirements in a complex construction site environment are difficult to meet. The method comprises the steps of building an electromagnetic shielding space, obtaining IMSI information of a mobile phone and achieving position tracking by combining a base station and a phased array radar cooperation mechanism. According to the invention, reliable acquisition of the IMSI of the mobile phone is realized by constructing the electromagnetic shielding space, and a brand new large-range, high-precision and non-sensitive personnel positioning scheme is provided by combining a cooperative working mechanism of the wireless communication base station and the phased array radar.

This invention discloses a synchronization method for a semi-Markov jumping neural network with measurement loss, belonging to the field of synchronization control technology for semi-Markov jumping neural networks. This invention can guarantee the mean-square global asymptotic stability of the error system when external disturbances are zero, and meet a preset disturbance attenuation level when external disturbances exist. The controller in this invention explicitly includes a non-fragile term structure, covering the control gain to realize error / uncertainty, avoiding the risk of "nominal design feasibility but implementation failure." This invention employs a dynamic event triggering mechanism to avoid Zeno risk at the mechanism level through "minimum trigger interval," and avoids performance degradation caused by long-term lack of updates through "maximum interval forced update." Dynamic variables achieve adaptive trigger thresholds, thereby reducing unnecessary transmissions while meeting performance requirements.

The invention relates to a multi-agent coverage control method and system based on a graph neural network, and the method comprises the following steps: S1, receiving local observation information collected by an unmanned plane agent i in an environment, extracting a spatial feature vector through employing a convolutional neural network, and taking the spatial feature vector as the local feature representation of the agent i; s2, constructing a multi-agent communication topology based on the local feature representation of the agent i, aggregating neighbor node features by adopting a graph neural network, and generating a feature representation fused with global cooperation information; s3, a multi-layer perceptron is adopted to map the feature representation fused with the global cooperation information into a speed control instruction, and an intelligent agent i is driven to move and cover in the environment; and S4, the steps S1 to S4 are repeated and iterated until the multi-agent coverage control process is completed. Compared with the prior art, the method has the advantages of enhancing robustness and adaptability to complex and noise environments and the like.

This invention relates to the field of intelligent control, specifically to an intelligent control method and system for green grain storage environment based on the Internet of Things (IoT). It includes: acquiring data; determining the dew point temperature of the outside air and constructing long-term potential moisture-affected prediction characteristics; constructing short-term actual moisture-affected response characteristics; determining the moisture-affected trigger intensity; calculating the number of effective diffusion areas within the grain storage facility where moisture initiation occurs; generating local control demand and global control demand; comparing the local and global control demand, determining control instructions based on the comparison results, and controlling the grain storage environment according to the control instructions. This invention can implement targeted and precise control to reduce energy consumption when the risk of moisture-affected conditions is concentrated in a localized area, and can promptly switch to global coverage control to ensure grain storage safety when the risk spreads to multiple areas.

The application discloses a projector multi-zone cooperative heat dissipation control method based on scene sensing and disturbance compensation, comprising the following steps: S1, collecting the mainboard SoC temperature, the light source module temperature, the power module temperature, the environment temperature, the signal source type, the running load, the frame average brightness and the brightness change rate in the same control cycle. The projector multi-zone cooperative heat dissipation control method and system based on scene sensing and disturbance compensation, by fusing the temperature, the signal source, the running load and the picture brightness change data in the same control cycle, form the heat dissipation control logic composed of the reference rotating speed, the scene rotating speed offset, the disturbance compensation rotating speed, the main auxiliary fan slave cooperation and the safety coverage control, so that the projector can dynamically adjust the main fan and auxiliary fan rotating speed according to different use scenes, different core heat zone states and different transient heat disturbance states.

The invention relates to the technical field of signal control, and discloses an RFID tag antenna signal coverage control method and system, and the method comprises the steps: obtaining tag distribution density data and environment interference data; constructing a label spatial distribution diagram through kernel density estimation and quadtree spatial indexes; identifying the boundary of the abnormal region by adopting hierarchical scanning and acquiring coordinates; inputting the abnormal area data into a power optimization model to generate a power distribution matrix; calibrating a node power state through backscatter communication to obtain an adjustment amplitude; allocating communication time slots by using a time slot ALOHA protocol, and performing data verification in combination with a neighbor discovery algorithm to obtain a power coordination result; and finally, generating a final resource scheduling scheme through weighted polling and a Nash equilibrium algorithm. According to the method, accurate label signal coverage control and resource optimization allocation are realized.

The invention discloses a network attack-oriented cluster hierarchical dynamic coverage control method. The method comprises the following steps: constructing a system mathematical model based on an unmanned aerial vehicle cluster system network; the whole process is divided into a robust construction stage and a dynamic coverage stage, in the robust construction stage, a group of unmanned aerial vehicles in initial random distribution construct a communication topological graph meeting robust conditions, and in the dynamic coverage stage, a robust cluster formed in the previous stage is controlled to move, so that the robustness of the unmanned aerial vehicles is improved. The robust attribute of the cluster formation is maintained while dynamic coverage is considered, and the targets of dynamic coverage, collision avoidance, obstacle avoidance and robust maintenance are achieved at the same time in the task process. The method can effectively ensure that the cluster can still effectively eliminate the interference of malicious nodes in a network environment in which malicious network attacks possibly exist, so that the state values of normal nodes are quickly consistent, the dynamic region coverage task is efficiently completed, and the research and practical application of the existing method in the cluster cooperative control field are expanded.