208 results about "Instruction distribution" patented technology

According to the instruction processing system, method and device provided by the invention, the instructions can be efficiently and smoothly distributed and run through the at least one processing module of the processor, and different instruction distribution logics are adopted based on different types of business processing instructions through two-stage instruction distribution, so that the service processing efficiency is improved. The business processing instructions are stored in the target storage area and then scheduled to the instruction execution module, so that quick distribution and hardware support of different types of business processing instructions are realized, the instruction distribution efficiency is greatly improved, complex calculation tasks can be flexibly and efficiently processed, instruction scheduling can be performed according to the priorities of the business processing instructions, and the service processing efficiency is improved. The key business operation is ensured to be responded and processed in time, and the overall performance and the operation efficiency of the database processor are effectively improved. The technical effect of flexibly and efficiently processing the database acceleration task is achieved.

The invention provides a switching station control method and system of a subway station. The system comprises a subsystem control unit, a main control unit, a communication module and a data caching module, the subsystem control unit transmits an equipment on-off state, a fault signal and an environment parameter to the main control unit in a hybrid networking mode, and a first cooperative control instruction set is generated in combination with a linkage rule base; a target priority is distributed for the operation instruction to obtain a second cooperative control instruction set, and the communication module adopts a multi-channel parallel distribution mechanism for pushing; in the process of executing the switching station operation, the data caching module stores running state data, identifies a time sequence mode by using a machine learning model, pre-judges a switching station linkage scene and loads a control strategy; and the main control unit detects the response delay of the subsystem control unit and generates a third cooperative control instruction set according to the control strategy so as to optimize the switching station control time sequence. According to the invention, intelligent cooperative control of multiple electromechanical devices can be realized.

The invention provides a processor memory access optimization implementation method and system with multi-channel concurrent instructions, and relates to the technical field of processor integrated circuits, and the method comprises the steps: obtaining a Load instruction and a Store instruction to be executed; distributing a plurality of memory access instructions to each memory access channel which is independently processed in parallel, wherein each memory access channel comprises a Load memory access channel and a Store memory access channel; an independent Load queue and an independent RAW check queue are arranged in the Load memory access channel, and an independent Store queue, an independent STD queue and an independent Store Buffer queue are arranged in the Store memory access channel; the Load instruction is sequentially subjected to an address generation stage, a TLB parallel query stage, an L1Cache access stage, a RAW check and data forward push stage and a data write-back stage in the Load memory access channel; according to the method, address and data separation processing is carried out on a Store instruction, an address part enters a Store queue, a data part enters an STD queue, then merging is carried out, multiple Store operations on the same Cache Line are merged into one-time writing, the merged data are written into a Store Buffer queue, and then the Store Buffer queue submits and caches in a unified mode.

The invention relates to the technical field of hydraulic engineering monitoring, and discloses a hydraulic engineering operation risk monitoring management system based on multi-sensor fusion. The system comprises a data acquisition module, a data fusion module, an early warning and instruction generation module, and an instruction distribution and verification and correction module. The data acquisition module acquires structural deformation, water flow pressure and environment temperature and humidity data in real time through multiple types of intelligent sensors; the data fusion module inputs the collected data into a dynamic weighted fusion model, and generates a comprehensive monitoring index in combination with a sensor confidence coefficient weight and a historical data deviation rate; the early warning and instruction generation module triggers multi-stage early warning and generates an equipment regulation and control instruction set according to the comprehensive monitoring index and a preset safety threshold value; the instruction distribution module distributes the instruction to an execution terminal through a distributed message queue; and the verification and correction module checks terminal feedback signals by using a back propagation verification mechanism, and corrects the confidence coefficient weight of the model.

The invention relates to the technical field of multi-agent cooperative control, and discloses a multi-agent cooperative operation control method and system based on a wireless deterministic network, and the system comprises a time synchronization calibration module which is used for collecting the initial timestamps and network transmission delay data of all agent nodes, setting synchronization protocol attributes for calibration, and transmitting the initial timestamps and the network transmission delay data to a wireless deterministic network; establishing a collaborative operation network model; the task instruction distribution module associates the job task demand with the agent capability data, and generates a collaborative job instruction set through task decomposition; the path conflict detection module initializes parameters based on a network model and optimizes a path to obtain a collaborative optimization path; the collaborative state sensing module obtains real-time state data and analyzes and determines control strategy parameters; and the control parameter optimization module performs simulation verification and feeds back optimization parameters. According to the system, the precision, efficiency and reliability of multi-agent collaborative operation are improved, and the system is suitable for various complex operation scenes.

The invention provides a parallel optimization method and system for a GPGPU (General Purpose Graphics Processing Unit) instruction execution stage, and the method comprises the steps: splitting an input instruction into a plurality of sub-instructions which can be independently scheduled based on an instruction type, operand dependency analysis and a hardware resource real-time state, and generating a dependency table to record the input and output association of the sub-instructions; acquiring real-time load data of the calculation unit, the storage unit and the communication unit, and distributing the sub-instructions to the calculation unit, the storage unit or the communication unit by adopting a priority dynamic adjustment algorithm and combining instruction key path analysis; according to the dependency relationship of the sub-instructions and the availability of hardware resources, the execution sequence of the sub-instructions is adjusted to maximize the degree of parallelism; and analyzing the dependency relationship among the sub-instructions in real time to maximize the degree of parallelism to dynamically adjust a parallel execution strategy so as to realize serial execution of dependent instructions and parallel execution of non-dependent instructions. According to the method, the complexity of instruction compiling is reduced, the efficiency of instruction compiling is improved, and meanwhile extra consumed time is reduced.

The invention discloses an adjustable resource unified data external characteristic modeling, regulation and control method and system oriented to various transaction scenes. The method comprises the following steps: collecting real-time data of an internal adjustable resource of a virtual power plant; the climbing time, the duration, the response capacity and the responsible frequency are quantized and defined as a group of external characteristic parameters, an adjustable resource data external characteristic model is constructed, adjustable resources are classified according to the external characteristic parameters of the model, and an adjustable resource characteristic library is established; in combination with the response characteristic and the load state of each adjustable resource, generating an optimal regulation and control strategy meeting the regulation and control requirements, and allocating a corresponding regulation and control instruction to each adjustable resource; each adjustable resource adjusts power output according to the regulation and control instruction, and meanwhile, the calling cost of each adjustable resource is calculated; in combination with the real-time state and the adjustment cost minimization target, the regulation sequence and proportion are optimized; according to the method, the economy and flexibility of the virtual power plant in multi-scene regulation can be effectively improved, and meanwhile, the accuracy of power grid frequency modulation response and the system stability are enhanced.

The embodiment of the invention provides a synchronization method, a synchronization device, electronic equipment and a storage medium. The synchronization method comprises the following steps: aiming at a thread bundle comprising a plurality of threads, distributing a synchronization channel for a first instruction; the first instruction and the second instruction are synchronized based on the synchronization channels, a dependency relationship exists between the first instruction and the second instruction, the thread bundle corresponds to a plurality of synchronization channel groups, each synchronization channel group comprises at least one synchronization channel, and different synchronization channel groups correspond to different types of instructions. The synchronization method uses a synchronization channel mechanism based on an instruction type to realize synchronization of instructions in the thread bundle, effectively realizes decoupling of synchronization channels used by different types of instructions, and expands the number of synchronization channels, thereby improving the processing capability of the thread bundle for a workload, and improving the processing efficiency of the thread bundle. And challenges brought by continuously increasing workloads in the thread bundle can be effectively handled.

The invention relates to the technical field of information, and discloses a digital right near-field real-time cancel-after-verification system based on edge computing, which comprises a space-time coding module used for generating a unique cancel-after-verification identifier according to the geographic position and time of a user, and transmitting the identifier to a dynamic weight module; a dynamic weight module which is connected with the space-time coding module, generates a right and interest distribution strategy based on a federated learning model and an optimization algorithm, and outputs the optimized strategy to a block chain fragmentation module; the block chain fragment module is connected with the dynamic weight module, dynamically divides a consensus network according to the real-time cancel-after-verification density, executes distributed verification in fragments and generates a cancel-after-verification authorization instruction; and the cancel-after-verification execution module is used for distributing cancel-after-verification tasks according to the authorization instruction and synchronously updating the multi-node inventory state. By adopting the technical scheme of gridding coordinate mapping, time window division and nonlinear hash of the space-time coding module, the technical effect that the verification identifier is unpredictable and uniquely bound is achieved.

The invention relates to the technical field of power system dispatching, in particular to a distributed storage system for source-network-load-storage collaborative dispatching, which comprises a distributed data acquisition module, a regional collaborative sensing module, a distributed energy storage evaluation module, a dispatching instruction generation module and a dispatching instruction distribution module, wherein the distributed data acquisition module is used for acquiring real-time operation data of source, network, load and storage nodes in parallel; the regional collaborative sensing module is used for calculating a real-time power deviation value; the distributed energy storage evaluation module is used for generating an energy storage adjustment instruction set; and the scheduling instruction generation module is used for generating a final refined scheduling instruction. According to the invention, through constructing a cooperative scheduling mechanism of the source network load storage full chain, accurate identification of power deviation and optimal distribution of energy storage resources are realized, and scheduling response efficiency and operation stability of the system are significantly improved.

The invention relates to the technical field of industrial control, and discloses an industrial communication protocol adaptation method and system based on OpenHarmony. The method comprises the following steps: performing distributed soft bus deployment on a plurality of industrial devices in an industrial control network to obtain a distributed device connection architecture; carrying out multi-protocol adapter loading on the industrial automation runtime service of the distributed equipment connection architecture to obtain a multi-protocol runtime service instance; performing communication protocol identification and configuration on the plurality of industrial devices according to the multi-protocol runtime service instance to obtain standardized device data; and establishing a data transmission channel according to the standardized device data, and performing global state synchronization and cooperative control instruction distribution on the plurality of industrial devices to generate a distributed cooperative control network. The deployment and maintenance work of the industrial control system is simplified, the accuracy and consistency of system configuration are improved, the risk of manual configuration errors is reduced, and the development cost and maintenance complexity of industrial application are reduced.

Aspects of the disclosed technology include computer-implemented systems and methods for adapting machine-learned models using high-quality synthetic data that is tailored to elicit improved instruction-following abilities for particular target instruction distributions and models. A model adaptation system can obtain instruction metadata indicative of at least one use case and at least one skill associated with a particular computing task to be performed by a target machine-learned model. The system can generate a metadata-conditioned synthetic instruction by prompting a generative model system including one or more machine-learned generative models with the instruction metadata as one or more constraints. The system can generate a model response by prompting the generative model system with the metadata-conditioned synthetic instruction. The system can modify a target sequence processing model based at least in part on a data pair including the metadata-conditioned synthetic instruction and the model response.

The invention relates to the technical field of call center control, and discloses an unmanned vehicle formation control and obstacle avoidance reconstruction system based on complex road conditions. The system call data acquisition module is used for acquiring multi-source interaction data in real time; the dynamic feature extraction module is used for performing semantic intention hierarchical analysis on the voice stream text conversion data, performing event fragment segmentation on the user behavior time sequence data, and generating an operation track feature vector; the scene clustering engine module is used for performing space-time alignment on the semantic intention hierarchical analysis result and the event fragment segmentation result to generate a multi-dimensional scene clustering tag; the strategy matching core module is used for retrieving an interaction strategy set matched with the current scene from a distributed strategy library according to the multi-dimensional scene clustering label and generating a dynamic control instruction sequence; and the instruction distribution execution module is used for distributing the dynamic control instruction sequences to corresponding seat terminals and voice routing equipment after sorting the dynamic control instruction sequences according to priorities.

The invention relates to a neural network accelerator, in particular to an instruction flow control system applied to the neural network accelerator, which comprises a first-stage instruction flow control unit, a second-stage instruction flow control unit, a third-stage instruction flow control unit, a fourth-stage instruction flow control unit and a fourth-stage instruction flow control unit, and is characterized in that the first-stage instruction flow control unit is responsible for prefetching, decoding, executing and distributing instructions of the neural network accelerator and responding to pause influence of debugging events and synchronization events on instruction distribution; the second-level instruction flow control unit is located in each execution unit, extracts execution parameters from the second-level execution instructions distributed by the first-level instruction flow control unit, is responsible for translating and maintaining the instruction execution dependency relationship among the execution units, and ensures that the execution units execute the instructions in sequence according to the instruction execution dependency relationship among the execution units; according to the technical scheme, the defect that in the prior art, it is difficult to efficiently execute instructions with the execution dependency relationship between the execution units can be effectively overcome.

The invention relates to the technical field of industrial internet, in particular to a control system and method for stirrer production. Comprising an edge data preprocessing unit, a flexible production instruction distribution unit and a working condition diagnosis and protection control unit. By constructing an integrated control parameter mapping model, an industrial operation signal is converted into a collaborative sensing digital primitive; the production task is compiled into an intelligent production execution process cluster based on a resource scheduling algorithm, and equipment is driven to execute differentiated production; and performing situation assessment on the digital primitives by using the anomaly detection model, and generating a regulation and control instruction to execute process logic recombination and safety protection. According to the invention, the problems of low production information integration level and tight data in each link of a production control system are solved, and flexible scheduling and active security defense in the production process are realized.

The invention relates to the technical field of quantum computer control, and belongs to a quantum equipment instruction distribution system and method based on multi-thread parallel routing, the system comprises an upper computer, an instruction board, an instruction routing board and an equipment end, and the instruction distribution method comprises the following steps: S1, inputting a program instruction and a control instruction through the upper computer, the data is issued to the instruction board through the local bus interface; s2, multi-thread parallel execution of the program instruction is achieved in an instruction board FPGA chip, a control instruction is generated and output to a routing board through a high-speed radio frequency interface, and the control instruction comprises a target address code; s3, dynamically selecting an output port by the instruction routing board according to the target address code generated in S2, and distributing the instruction to specified equipment; and S4, each device in the device end receives the instruction through the SSMA sequence interface and executes the instruction. According to the invention, efficient synchronous control of quantum equipment is realized through multi-thread parallel execution and a dynamic routing mechanism.

The invention relates to the technical field of data monitoring, in particular to a workshop operation state real-time monitoring, management and control method and system, and the method comprises the steps: carrying out the real-time collection of multi-source heterogeneous data of each process execution unit through a plurality of data collection terminals, and carrying out the standardization processing of the collected multi-source heterogeneous data; based on the standardized multi-source heterogeneous data, extracting multi-dimensional features corresponding to each process execution unit, associating the multi-dimensional features with plan standard features, inputting the associated features into a state judgment model, and outputting a comprehensive state identifier; if it is judged that the comprehensive state identifier triggers a state abnormal event, comparing the state abnormal event with a preset decision rule base, and outputting corresponding decision action information; and packaging the decision action information into a corresponding management and control instruction, and transmitting the management and control instruction to the corresponding process execution unit for execution through an instruction distribution interface, thereby realizing comprehensive, accurate, real-time and intelligent management and control of the workshop operation state.

The invention discloses an eVTOL aircraft ground control device based on a multi-link adaptation and response mechanism, and belongs to the technical field of eVTOL aircraft communication and control. The device comprises an instruction distribution module, a multi-link management module, a frame construction module and an error control module. The instruction distribution module is responsible for cooperating with eVTOL aircraft information to send a corresponding flight control instruction according to an actual condition; the multi-link management module evaluates a plurality of communication links (including a main link, a standby link and an emergency link) in real time and is used for sending different instructions; the frame construction module constructs an extended interactive data frame based on the MAVLink protocol, and the data frame comprises a plurality of control fields for control; the device also has an error control mechanism, and a closed-loop control system is completed through the mechanism. Through the method, the instruction reliability of the ground control station in a complex communication environment and the stability of an eVTOL aircraft system can be effectively improved.

The embodiment of the invention provides a data processing device, a processor and a data processing method. The data processing apparatus includes an instruction distribution unit, an instruction information recording unit, an instruction processing unit, and a write-back control unit, the instruction distribution unit being configured to split a vector instruction into a plurality of microinstructions, and to distribute the plurality of microinstructions to the instruction processing unit; the instruction information recording unit is configured to record instruction state information corresponding to a plurality of microinstructions respectively; the instruction processing unit is configured to receive a plurality of micro-instructions, process each of the plurality of micro-instructions to obtain a corresponding execution result, and feed back a processing progress to the instruction information recording unit; and the write-back control unit is configured to select at least one to-be-written-back microinstruction from the instruction information recording unit to perform write-back operation based on the instruction state information, and the write-back operation is used for writing an execution result of the to-be-written-back microinstruction back to the register. The device can realize out-of-order write-back of the instruction and improve the execution efficiency of the instruction.

The invention discloses a memory access device, a processor and a memory access method, and belongs to the technical field of computers. The memory access device comprises a scheduling module which is configured to distribute memory access instructions in an instruction queue to a plurality of assembly lines of the memory access device; the first cache module is configured to cache the first mapping relation; the control module is configured to query the page table and update the second mapping relation in the second cache module according to the memory access instruction of the virtual machine monitor if the memory access instruction currently processed by the plurality of assembly lines does not hit the first mapping relation and the memory access instruction is the memory access instruction of the virtual machine monitor; and the second cache module is configured to cache the second mapping relation. On the basis of not increasing the complexity of hardware design, the resource utilization rate in the execution process of the memory access instruction of the virtual machine monitor can be improved.

The embodiment of the invention provides an instruction distribution device and method, a processor and electronic equipment. The instruction distribution device comprises a write selection module, a plurality of micro instruction queues and a read distribution module. The write selection module is configured to write microinstructions into a plurality of microinstruction queues; the plurality of microinstruction queues are configured to cache written microinstructions; and the read distribution module is configured to read the microinstructions from the plurality of microinstruction queues, obtain a target microinstruction group to be distributed at this time based on the read microinstructions, and execute a distribution operation. The instruction distribution device improves the bandwidth of instruction distribution by setting a plurality of microinstruction queues and a scheduling method of the plurality of microinstruction queues, thereby promoting the improvement of the performance of a processor.

The invention relates to the technical field of chips, and provides a tensor memory accelerator and a tensor memory acceleration method.The tensor memory accelerator comprises an instruction distribution unit and a plurality of tensor memory acceleration engines capable of conducting parallel processing; wherein the instruction distribution unit is used for distributing a tensor memory acceleration instruction to idle engines in a plurality of tensor memory acceleration engines for execution, each tensor memory acceleration engine is provided with a descriptor storage unit for storing descriptors, and each tensor memory acceleration engine is used for storing the descriptors according to multiplexing identification information in the tensor memory acceleration instruction. And multiplexing the descriptors from the corresponding descriptor storage units or obtaining new descriptors from the external memory. According to the invention, each tensor memory acceleration engine can selectively multiplex descriptors from the local or obtain new descriptors from the outside, so that instruction-level parallel processing and effective multiplexing of descriptor information are realized.

The invention discloses a self-coupling PID (proportion integration differentiation) flight control method of a rudder-controlled transverse-row type rotor unmanned aerial vehicle based on dynamic multi-dimensional heterogeneous fuzzy logic, and belongs to the technical field of flight control of rudder-controlled transverse-row type rotor unmanned aerial vehicles. A flight control system architecture of the self-coupling PID flight control method is composed of three core modules: (1) a dynamic multi-dimensional fuzzy logic coupling PID controller (DMHFL-SCPID); (2) control instruction distribution; and (3) a six-degree-of-freedom dynamical model of the rudder-controlled transverse rotorcraft. According to the control algorithm, input and output dynamic parameters of a system are analyzed in real time, and four-dimensional flight control quantities (roll, pitch, yaw and height instructions) are generated. A control distribution strategy based on the aerodynamic characteristics of the rotor converts the instructions into actuating quantity of an actuating mechanism, and flight attitude adjustment is realized by changing aerodynamic load distribution of a rotor system, so that the unmanned aerial vehicle is guided to realize accurate tracking along a predetermined flight path.

The embodiment of the invention discloses a production change control method and device for mixed line production and a medium, and relates to the technical field of production control, and the method comprises the steps: collecting real-time production index data corresponding to a current production product in a current production line in real time under the triggering of a production change instruction issued by a production management system, obtaining a target process parameter set corresponding to the target product change product; according to the real-time production index data and the production change instruction, a production change state vector containing a production change stage label is determined, and the production change stage label comprises a production change preparation stage, a production change pre-adjustment stage and an execution stage; and based on the production change state vector and the target process parameter set, through a preset reinforcement learning agent, determining a time sequence production change action sequence, converting the time sequence production change action sequence into an equipment control instruction for instruction distribution, and realizing production change control. The sequential production change action sequence comprises a pre-adjustment action instruction, a parallel scheduling instruction and a parameter loading instruction.

The invention relates to the technical field of mobile communication and Internet of Things, and discloses a heterogeneous network space multi-level mobile Internet of Things cloud system based on artificial intelligence, which comprises a data acquisition module for acquiring real-time state data of a mobile Internet of Things terminal and generating a standardized network-service joint situation vector; the endogenous interference sensing module is used for generating a network interference association diagram based on the vector; the service-network dynamic decoupling module is used for reversely reconstructing terminal service characteristics according to the association diagram and decoupling a key network state sequence; the business intention abstraction module constructs a heterogeneous network cooperation state target according to the sequence; the collaborative scheduling strategy generation module is used for generating a multi-dimensional collaborative scheduling instruction by using a collaborative decision model; the network resource self-growing module is used for performing state sequence evolution after the rehearsal instruction and constructing a compensation network plane; and the instruction distribution and verification module is used for executing the instruction of the fusion compensation logic and updating the association diagram. According to the method, the problems of heterogeneous network interference and scheduling lag of the mobile Internet of Things are effectively solved.

The invention discloses an AI-based multi-device cooperative control method in an Internet of Things environment. By constructing a'perception-decision-control-feedback-self-adaption 'full-closed-loop architecture, terminal components such as an intelligent equipment group and a sensor group of an equipment layer, a multi-source data acquisition and enhancement preprocessing module of a perception layer, a dynamic equipment capability graph of an AI decision layer, an incremental AI decision model and other core units are integrated; and a cross-protocol instruction distribution and closed-loop feedback module of the control layer realizes deep processing of multi-source heterogeneous data, real-time perception of equipment capability, dynamic adjustment of task priority and autonomous optimization of a coordination strategy, thoroughly solves the technical problems of rigid coordination logic, response lag and unreasonable resource allocation of a traditional method, and improves the reliability of the system. And the intelligent level and the operation efficiency of the Internet of Things system are greatly improved.

The invention discloses a configurable cascade circuit for efficient in-memory processing, which comprises an integrated state machine module, a cascade instruction distributor unit, a configuration register unit, a configurable cascade calculation engine and an on-chip storage unit, and forms a complete in-memory calculation processing chain. The state machine dynamically adjusts the circuit operation state; the cascade instruction distributor unit decomposes a cascade instruction into discrete operation blocks and loads the discrete operation blocks into a plurality of registers in the configuration register unit; the decoder unit generates a control word containing the serial number of the in-memory computing unit and the channel configuration parameters of the in-memory computing unit; and the configurable cascade computing engine enables the corresponding in-memory computing unit according to the control word, and after the in-memory computing unit is driven to complete a specified computing task, intermediate cache data is written into the on-chip storage unit in real time by adopting a double-BRAM dynamic cache strategy. And circularly controlling the iteration work of the calculation unit in the memory until the cascade termination signal triggers and outputs a final calculation result. According to the invention, a calculation-caching-transmission integrated assembly line is constructed.

The embodiment of the invention provides an allocation method, electronic equipment and a storage medium. The distribution method is executed by a compiler and comprises the steps that according to the position of a first type of instruction in an intermediate representation corresponding to a program to be compiled, a second type of instruction corresponding to the first type of instruction is grouped, and a dependency relationship exists between the first type of instruction and the second type of instruction; according to the grouping result, a hardware synchronization channel is distributed for the second type of instructions, and the hardware synchronization channel is configured to achieve synchronization of the first type of instructions and the second type of instructions. On the premise that hardware synchronization channel resources are limited, the method effectively reduces synchronization channel conflicts and extra waiting among different instructions through a reasonable grouping and distribution strategy in cooperation with hardware instructions, improves hardware concurrency, reduces dependence on hardware synchronization capability, and thus reduces hardware design complexity.

The invention relates to the technical field of wireless communication synchronization and gate valve action collaboration, in particular to a multichannel audio master-slave sound role intelligent conversion system and method.A master control unit broadcasts a time calibration packet to synchronize unit clocks, and an automatic calibration protocol is executed to generate an inherent processing delay baseline value; the subordinate gate valve unit records an instruction receiving and action completion timestamp through a delay detection module, calculates actual delay containing wireless transmission and local processing delay, and packages the actual delay into a structured feedback data packet for real-time feedback; a dynamic adjustment module of the main control unit filters noise through a weighted moving average algorithm, and calculates individual compensation delay parameters in combination with the dynamic buffer compensation amount of the environment interference monitoring module and delay trend prediction of an adaptive learning engine; and when abnormity occurs, historical data is called for replacement and self-inspection is triggered, an instruction distribution time sequence is adjusted according to compensation parameters, a gate valve action execution confirmation module verifies the displacement precision, and the fluid control precision and stability are improved.

The invention discloses a VR scene control method and system, and belongs to the technical field of VR scene control, and the method specifically comprises the steps: deploying a global time controller, generating a continuously increasing global timestamp at a fixed frequency, and transmitting the global timestamp to a scene rendering, audio processing and touch driving module; the scene interaction monitoring unit continuously collects user body movement and virtual object movement state data, analyzes interaction event types and characteristic parameters and then binds the interaction event types and the characteristic parameters with a current global timestamp to form an interaction information packet with the timestamp; a multi-modal feedback instruction generation unit receives the information packet, and generates three types of instructions carrying the same global timestamp based on the interaction event type, the characteristic parameters and the bound global timestamp; the feedback instruction distribution unit forwards the three types of instructions to corresponding modules at corresponding moments according to global timestamps carried by the instructions; and after executing feedback, each module records delay and sends the delay to the global time controller, so that the actual execution moments of three types of instructions in the next round are consistent.