185 results about "Task control" patented technology

In one implementation, a device may identify a type of task and its context indicated by a prompt sent by a user for input to a language model. The device may authorize the prompt for input to the language model based on the type of task and its context. The device may make a determination as to whether a response of the language model to the prompt is authorized to be returned to the user based on the response, the type of task, and its context. The device may prevent the response from being returned to the user when the determination indicates that the response is not authorized to be returned.

The invention relates to the technical field of cloud control, in particular to a cloud-based steam cabinet control system, which comprises a humidity sampling processing module, a steam state judgment module, a task stage identification module, a control instruction reconstruction module and a scheduling execution response module. According to the method, the accuracy of steam management is improved through staged recognition of the steam release state, a matching mechanism is formed in combination with the task timestamp and the staged state, the real-time adaptation capacity in the task execution process is enhanced, a dynamic comparison and queue rearrangement mode is adopted in the task instruction updating link, and the task execution efficiency is improved. Synchronous cooperation of a control instruction and a current task state is achieved, targeted optimization of the task control instruction and dynamic adjustment of a control process are achieved through a multi-dimensional state analysis and time sequence mapping means, the feedback response efficiency, task scheduling flexibility and steam release accuracy in the equipment operation process are effectively improved, and the system performance is improved. Therefore, the adaptive capacity and the control precision of the steam cabinet control in various operation states are enhanced.

The invention discloses a real time operating system (RTOS) multi-task priority scheduling and real-time control method based on advanced RISC machines (ARM), and relates to the technical field of embedded computing and control. Comprising the following steps: S1, time slice management setting: dividing CPU time according to a preset time period to obtain time slices; s2, performing task scheduling: setting each task according to a task control block, and performing context switching and priority arbitration through an OSScheduler () function; and S3, performing exception response: performing forced interruption and exception recovery operation through a set multi-stage exception classification mechanism. Through a three-level decision model and a partition response mechanism, it can be ensured that a high-priority task can be responded in time within strict time constraints, the hard real-time requirement is met, meanwhile, CPU time is divided through a fixed time slice, a counter is updated through timer interruption, and therefore the time deviation of task execution can be reduced, and the task execution efficiency is improved. And the certainty of the system is improved.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The invention discloses a kernel task execution method, electronic equipment, a readable storage medium and a program product, and relates to the technical field of computers. The method comprises the following steps: creating at least three layers of nested mapping table structures; the first layer of mapping table stores a task identifier and a nesting relationship between the task identifier and a lower layer, and the other layers of mapping tables store control rules and corresponding nesting relationships. Target task control rule information extracted from the resource strategy file is divided into task execution control rules with the corresponding number, the task execution control rules are correspondingly stored in mapping tables of corresponding layers, and the task execution control rules serve as task execution control rule storage tables to be issued to a kernel mode; and the kernel mode performs layer-by-layer control on kernel task operation according to the task execution control rule storage table. According to the method and the device, the problem that the container scene cannot store the service requirement of the access control rule due to the fact that the eBPF Map cannot be nested in multiple layers in the related technology can be solved, and container access control can be realized in the container scene.

The invention provides a controller parameter optimization method and a task control method based on reinforcement learning, and relates to the technical field of control, and the method comprises the steps: inputting the parameters of a PID controller of a current task into a DDPG model, obtaining the parameters of a PID controller of a next task, inputting the parameters of the PID controller of the next task into the PID controller to obtain a control quantity; determining an evaluation result of the control of the PID controller based on the control quantity as a reward; taking the state, action and reward of the current time step and the state of the next time step as sample data and storing the sample data into an experience pool; and training the DDPG model based on the experience pool, and determining the target parameter output by the trained DDPG model as the optimal parameter of the PID controller. In the application stage, only the PID controller needs to output the target control quantity based on the optimal parameters, the participation of a DDPG model is not needed, and the light weight of the whole control model is realized.

The invention provides a computing chip, a computing device, a data processing method, a storage medium and a program product. The computing chip comprises one or more computing modules and is used for executing computing tasks; the command processor is used for issuing a first calculation task to the one or more calculation modules; the data transmission module is used for carrying out data transmission with an external computing chip in a remote memory direct access mode; the transmission control module comprises a task queue creating module used for receiving the control command and adding the first calculation task to a first task queue created by the task queue creating module according to the control command; the task scheduling module is used for responding to the fact that the one or more computing modules execute the first computing task, controlling the data transmission module to communicate with an external computing chip, and transmitting a computing result corresponding to the first computing task to the external computing chip in a remote memory direct access mode.

A method for controlling a robotic manipulator according to a task comprises accepting a feedback signal including a sequence of multi-modal observations of a state of execution of the task. The multi-modal observations are processed with a neural network having a self-attention module with a hierarchically conditioned output to produce a skill of the robotic manipulator and an action conditioned on the skill. The neural network is trained in a supervised manner with demonstration data to produce a sequence of skills and a corresponding sequence of actions for the actuators of the robotic manipulator to perform the task. The method further comprises determining one or more control commands for the one or more actuators based on the produced action and submitting the one or more control commands to the one or more actuators causing a change of the state of execution of the task.

The invention relates to a matrix accelerator sharing a chip system memory and an operation method of the matrix accelerator. The matrix accelerator comprises a system memory module, a task management module, a data access module and a matrix operation module. According to the matrix accelerator, the chip system memory is directly shared through the dual-port SRAM, so that the matrix accelerator can be suitable for a navigation baseband chip with small size and low power consumption, meanwhile, when the matrix accelerator does not work, the shared memory can still be used as the chip system memory, and idle waste of memory resources is avoided. Through the task queue, a plurality of operation tasks and corresponding task control instructions can be loaded into the matrix accelerator at one time, and an interrupt signal is generated after all the operation tasks are completed to complete interaction between the CPU and the matrix accelerator, so that the efficiency of the CPU is improved to the maximum extent, and the performance of a chip system is remarkably improved.

The invention relates to an unmanned aerial vehicle cluster task dynamic recombination system and method. The system comprises a task control program, a module engine, a program API interface, a task upgrading program, an ROS2 data distribution service and a plurality of task modules. The task control program controls the starting, stopping and running state monitoring function of each module, the module engine is responsible for managing the starting, stopping and running states of the modules, the program API interface is responsible for receiving an external task upgrading request or task configuration request, the task upgrading program receives a platform external request, and the module engine is responsible for managing the starting, stopping and running states of the modules. The upgrade package information is sent to a program API interface of the task control program, the task module is a specific task processing unit, and the ROS2 data distribution service is used for realizing data interaction among the task modules. The problem that an unmanned aerial vehicle cluster system lacks the capability of performing dynamic adjustment according to actual conditions in the task execution process is solved, the flexibility, expandability and task execution efficiency of the system are remarkably improved, and effective application in a complex task environment is achieved.

The invention provides a task scheduling method for realizing equipment on an electric energy meter verification assembly line, which comprises the following steps of: determining equipment and tasks participating in scheduling according to a verification working link of an electric energy meter, and determining the workload, priority and completion time of each task; acquiring state information data of each device, after preprocessing the state information data into feature data of each device, importing the feature data into the trained multifunctional prediction model, and predicting the load capacity and fault risk of each device; calculating the load capacity of each device according to the load capacity and the fault risk of each device, and calculating the load demand of each task in combination with the workload, the priority and the completion time of each task; and constructing a target function, and solving an optimal solution to obtain a task scheduling queue in combination with the load demand of each task so as to perform intelligent scheduling task control on each device. By implementing the method, the task scheduling efficiency and accuracy are improved, the generation efficiency of the electric energy meter verification assembly line is also improved, and the verification period is shortened.

The present invention discloses an enterprise human resources comprehensive management platform, which relates to the field of data management technology and includes: a resource management system determination module for determining a resource management system; a management logic chain determination module for determining a management logic chain; a task management strategy determination module for determining a task management strategy; a sensitive management mode setting module for setting a sensitive management mode for sensitive data classes; a sensitive management strategy determination module for determining a sensitive management strategy; and a pre-management task control module for executing and controlling pre-management tasks. The platform solves the technical problems of the existing enterprise human resources management, such as the difficulty in coping with complex and changing enterprise management needs, the lack of integration of multiple enterprise application systems, and the risks of sensitive data management, which lead to the inaccuracy and security of enterprise human resources management. The platform intelligently realizes the comprehensive integration and efficient use of human resources information, achieving the technical effect of improving the accuracy and security of enterprise management.

The invention discloses a multi-robot synchronous control method and system, and relates to the technical field of robot control, and the method comprises the steps: uploading a directional task to a task management center, carrying out the task interpretation and role marshalling planning through a task engine, determining an execution unit cluster, and building a task communication system based on the execution unit cluster through a 5G private network. Gathering at a task side end and deploying a dynamic management component; and based on the task communication system and the dynamic management component, the execution unit cluster is taken over, and driving control and tracking supervision are carried out by robot coding, so that the technical problems of relatively limited efficiency, flexibility and expandability of robot cluster task control and scheduling in a complex environment in the prior art are solved. And efficient, flexible and extensible task management and scheduling can be realized in a complex environment.

A computing device displays a graphical user interface (GUI) comprising a navigator interface component. The navigator interface component comprises an interactive graphical representation of an asset. The device, responsive to detecting a predefined event, generates an alert. The device updates the navigator interface component to indicate the alert in association with the asset in the interactive graphical representation. The device receives a selection of the asset via the interactive graphical representation. The device displays, in the GUI, a second interactive graphical representation specific to the asset. The second interactive graphical representation of the asset comprises a task control element for controlling tasks specific to management of the asset. The device receives, using the task control element: a task for resolving the alert; and an association with the task and the asset. The device updates the navigator interface component to indicate the association with the task and the asset.

The invention belongs to the technical field of robot control, and discloses a foot-arm multi-task control method and system based on time-varying terminal cost, and the method comprises the steps: generating a whole-body reference trajectory of a robot offline, and pre-calculating a time-varying terminal cost matrix sequence based on the reference trajectory; based on the time-varying terminal cost matrix sequence, constructing and solving a nonlinear model predictive control optimization problem to obtain an optimization sequence of a system state and control input; and the optimization sequence serves as a reference instruction and is input into a layered whole-body controller for multi-task priority optimization, and a joint control instruction is generated and output to a robot execution mechanism. According to the method, the problem of short vision of a traditional NMPC in a long-time task is effectively relieved, and the operation precision of the robot is remarkably improved.

The invention discloses a composite AGV feeding and discharging control method and device, electronic equipment and a readable storage medium, and relates to the technical field of composite AGVs, and the method comprises the steps: responding to a current feeding and discharging task, controlling the composite AGV to move to a task area, recognizing a calibration point, and obtaining a current calibration point location; comparing the current calibration point location with an initial calibration point location to obtain point location deviation information; combining the point position deviation information to a task target point position based on a coordinate transformation matrix to obtain a current target point position; and executing the loading and unloading task based on the current target point location. The method and the device have the effect of improving the tail end execution positioning accuracy of the composite AGV.

The invention relates to the technical field of computers, in particular to an interaction method, electronic equipment, a readable medium and a program product. According to the method, thumbnail windows respectively corresponding to one or more task windows displayed on a screen are intensively displayed in an area, and the area can be named as a task control area hereinafter. On the basis, the foldable equipment can recognize the window operated by the user and the target area or the target position to which the window is dragged according to the operation, which is applied by the user in the task control area and indicates to move the display position of the window, of the thumbnail window. Therefore, according to the interaction scheme provided by the invention, the screen is prevented from being damaged by the sliding operation on the screen of the user, the efficiency of adjusting the position of each window displayed on the screen by the user can be improved, and the use experience of the user is further improved.

This application relates to the field of automatic feeding technology, and provides a distributed control method and system for feeding motor rotor laminations. The method includes: setting up programmable logic controllers (PLCs) at multiple feeding nodes, each controller connected to a synchronous Buck topology circuit; reading and parsing the feeding task script, identifying the collaborative feeding nodes and their task control precision from multiple feeding nodes; sending a precision synchronization command to a coordination terminal based on the task control precision to obtain a corresponding fluctuation limiting signal; and the coordination terminal performing distributed collaborative control on the output of the synchronous Buck circuit connected to the collaborative feeding nodes based on the fluctuation limiting signal to complete the execution of the feeding task script. This application solves the technical problems of inconsistent actions and large precision fluctuations caused by independent control of each feeding node in the traditional motor rotor lamination feeding process, achieving the technical effect of highly consistent actions of each feeding node and controllable feeding precision through distributed synchronous control and high-precision DC bus clamping.

A controller for controlling robotic manipulator according to a task is provided. The controller is to collect data relating to a state and an object property of an object, and execute a state adapter model to produce a state correction to state of the object having the object property different from a unitary property of a unitary object. The controller is to execute a control policy using the state correction to produce an action for the unitary object, and execute an action adapter model to produce an action correction to the action produced by the control policy. The state correction and action correction are produced based on difference between object property and unitary property. The control policy is to map a state of the unitary object to the action of the robotic manipulator to manipulate the unitary object according to the task.

The invention discloses a mine underground unmanned equipment intelligent control method and system, and relates to the technical field of intelligent mine equipment automatic control. Comprising the steps of constructing a regulation and control logic map according to a mining roadway center line; the method comprises the following steps: disassembling a long-flow operation task into a plurality of independent subtask units, and training an independent end-to-end task control model; when each task is started, a task navigation map is generated based on the regulation and control logic map, the executed task and the current position; and the front-end equipment triggers the corresponding sub-task control model based on the task navigation graph, the sensing information and the position information, and completes autonomous control of the current operation task through the real-time sensing information in the sub-task stage. Through operation area division, operation task decomposition, action model decoupling, reinforcement learning training, regulation and control of a logic map and an event-driven regulation and control mechanism, stable, reliable and efficient control of unmanned equipment operation under a coarse positioning condition is realized, and the method has good robustness, expandability and generalization.

The application discloses a kind of based on SM2 algorithm and SM4 algorithm's password processing method and system, belong to computer information security technical field, comprising: the enhanced task control block including service index number and data amount is constructed;Based on historical performance data calculation processing coefficient, utilize double threshold hysteresis comparator decision serial or parallel mode, avoid mode frequent switching;Parallel mode is through load balancing weight function for subtask allocation IP core;Hardware synchronization control unit maintains three index tables being processing, blocking and having been processed, realizes the automatic blocking and wake-up of associated job package, and with service index number as address accesses key and intermediate state;Adopt interrupt aggregation and double buffering batch processing result;Based on sliding window adaptive calibration double threshold and dynamically adjusting weight coefficient.The application effectively reduces interrupt overhead, eliminates scheduling ping-pong effect, realizes hardware level job synchronization, improves load balancing and image encryption structure fidelity.

The application relates to the technical field of grab machine control, and discloses a grab machine control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring current track information and current area information of each working area, acquiring working task information and current grab machine information, wherein the grab machine information comprises a grab machine state and a grab machine type; determining a task type of a task to be executed based on the working task information; determining a target grab machine from the grab machines whose current grab machine state is a preset grab machine state and whose current grab machine type corresponds to the task type; wherein the grab machine is used for grabbing and transporting materials; assigning a task to the target grab machine according to the current track information, the current area information and the working task information, obtaining a target task of the target grab machine, and controlling the target grab machine to execute the target task. The method provides a more practical, more accurate and more efficient grab machine control method.

The application discloses a task list engineering quantity segmentation control method and system based on WBS and a pricing list, relates to the technical field of engineering progress management, and comprises the following steps: an engineering project is decomposed into minimum task control units layer by layer through a WBS structure, and basic cost measurement is carried out on each unit based on a pricing list; scheduling constraints and overflow costs among units are generated, and costs are dynamically adjusted in real time through real-time input of engineering progress data; further, a prediction and an optimal scheme are generated based on actual data of completed engineering, and a project profit state and risks are comprehensively judged; through multidimensional evaluation and a sliding optimization algorithm, an optimal segmentation node is automatically identified, and segmentation control and scheme fine adjustment are realized. The method improves the fine management of engineering costs, risk early warning and dynamic optimization capability, and provides technical support for efficient, controllable and sustainable profit of complex engineering projects.

The invention provides an instantiation task execution method and device and electronic equipment, and the method comprises the steps: generating a plurality of instantiation tasks corresponding to a target game event according to a current game state; determining a target service code needing to be executed by the current frame; determining a target instantiation task needing to be executed by the current frame; the target instantiation task and the target service code are controlled to be executed in the current frame, the remaining time of the current frame after the target instantiation task or the target service code is executed is determined based on the timer until the remaining time meets a preset condition, and the current frame is controlled to be ended. According to the mode, through the pre-configured timer, the remaining time of the current frame after the current task or code is executed is calculated in real time in each frame of the game, and whether the current frame is ended or not is determined according to the remaining time, so that the problem of game picture jamming caused by executing excessive instantiation tasks is avoided, and the user experience is improved. The problem that system resources are wasted due to the fact that few instantiation tasks are executed is solved, and meanwhile the execution efficiency of the instantiation tasks is improved.

The embodiment of the invention discloses a task processing method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the following steps: acquiring transfer source position information; controlling the unmanned aerial vehicle task processing equipment to the sky corresponding to the transfer source position information; sending transfer task control information to control the first task processing equipment to send a to-be-processed task information set; generating a popularity task information sequence based on the to-be-processed task information set; performing executable detection processing on each piece of popularity task information to obtain executable detection information; generating an executable hot task information set and a non-executable hot task information set based on each piece of executable detection information; tasks corresponding to the executable popularity task information are executed in sequence; and controlling each unmanned aerial vehicle task processing device except the unmanned aerial vehicle task processing device to perform cooperative processing on each task corresponding to the non-executable popularity task information set. According to the embodiment, the delay of task processing is reduced.

The present invention relates to a method for implementing multi-task scheduling and load balancing based on Spring Boot. This method is implemented through the collaboration of an edge task plug-in module, a central task scheduling module, Nacos, and a database cluster. Based on the Spring Boot framework, any application developed based on Spring Boot can integrate the edge task plug-in module to implement message interaction with the central task scheduling module. This enables the dispatch of task control messages and the reporting of task status messages. This reduces the development and subsequent maintenance workload for developers. Through multi-task load balancing scheduling, automatic module offline upon failure, and automatic module online upon expansion, the method addresses issues such as low resource utilization, long response time, high load, and lack of flexibility (inability to dynamically adjust and lack of fault tolerance) in single applications. The method is applicable to various software systems requiring multi-task scheduling and load balancing.

Embodiments of the present application provide a self-moving device control method, an electronic device and a storage medium, and relate to the technical field of artificial intelligence. The method comprises: displaying a target scene map, a custom area creation icon and a task triggering panel in a task control interface, the target scene map being used to reflect a target scene in which a target self-moving device works; in response to a triggering operation of the custom area creation icon by a user, creating a custom area on the target scene map; in response to a selection operation of the custom area and a target area in the target scene map by the user, displaying a working area of the target self-moving device in the target scene map, the working area being a mixed area of the custom area and the target area; and controlling the target self-moving device to execute a target task in the working area according to the target task triggered by the user through the task triggering panel. The present application has high work efficiency, can meet the individual needs of users and has good user experience.

The present disclosure relates to the field of computers and automatic control, and particularly to a method, device, electronic device, and storage medium for controlling packaging tasks. The method includes: determining N batches of spools that can be packaged from the balancing room at preset time intervals, as well as the storage duration and storage quantity of each batch of spools that can be packaged in the balancing room; where N≥2 and is an integer; obtaining a predetermined packaging sequence for the N batches of spools that can be packaged based on the storage duration and storage quantity of each batch of spools that can be packaged in the balancing room; and performing an automatic packaging task for the N batches of spools that can be packaged according to the predetermined packaging sequence. By adopting the solution of the present disclosure, a large number of manual participation processes in the existing technology during the packaging task of spool products can be replaced by an automated packaging process, thereby greatly reducing the time for manual intervention and decision-making and improving the execution efficiency of the spool packaging task.

The invention discloses a task management system and a task management method suitable for a swarm unmanned aerial vehicle system, and in the task management system, hardware cross-linking, remote control instruction transmission and remote measurement information transmission are carried out between a command control subsystem and a flight control subsystem; the flight control subsystem is connected with the task control subsystem, and task control and management information for the swarm unmanned aerial vehicle system is processed through the task control subsystem, so that modification of the unmanned aerial vehicle from a single unmanned aerial vehicle to multiple unmanned aerial vehicles is realized by additionally arranging the task control subsystem; the task control subsystem and the task load subsystem are crosslinked, and the task control subsystem is used for transmitting a remote control instruction and a telemetering return of the task load subsystem and receiving task image information from the task load subsystem; the command and control subsystem and the task load subsystem are crosslinked, and the task load subsystem transmits task image information to the command and control subsystem, so that the ground station can display the task image information in real time. According to the technical scheme provided by the invention, the problem that the existing flight management system of the unmanned aerial vehicle is difficult to realize information interaction, instruction control, cooperative task execution and autonomous task planning among multiple unmanned aerial vehicles in a swarm unmanned aerial vehicle system is solved.