1078 results about "Consensus" patented technology

The invention relates to the technical field of data processing, provides a multi-node carbon emission intelligent contract verification method based on a block chain, and aims to solve the problems that data verification in an existing carbon asset transaction system is non-transparent, high in trust cost and difficult to adapt to policy changes. Distributed storage and dynamic verification of data are realized by constructing a hierarchical block chain architecture, the data are collected by using edge computing nodes, and third-party verification data are obtained through an oracle machine node cluster. The dynamic rule engine monitors data changes in real time, triggers a multi-stage verification process, and improves the data accuracy. And meanwhile, an improved Byzantine fault-tolerant mechanism is adopted to reach a consensus, and the system has the functions of strategy dynamic updating and security enhancement, so that the flexibility and security of the system are improved. According to the method, multi-party consensus and real-time verification of the carbon emission data are realized, trust cost of cooperation among enterprises is reduced, and healthy development of a carbon emission permit trading market is promoted.

A distributed indexing and resolution architecture is disclosed for decentralized systems requiring modular, trust-scoped mutation control and dynamic alias governance. The system comprises a plurality of index entries arranged in a parent-child hierarchy, each associated with a structured alias and governed by one or more anchor nodes. Anchors perform localized resolution, mutation validation, and restructuring operations under deterministic policy constraints, enabling semantic scope enforcement and entropy-sensitive adaptation without requiring global consensus or centralized control. The architecture supports scoped alias traversal, asynchronous mutation proposals, and elastic anchor registration based on system state metrics. The indexing substrate may be integrated into heterogeneous infrastructures, including systems comprising distributed software agents, semantic execution platforms, or pseudonymous identity frameworks. Anchors coordinate within defined trust domains to ensure lineage continuity, dynamic rekeying, and semantic integrity across independently governed segments of a decentralized namespace.

The invention discloses an industry return on investment real-time acquisition method based on multi-source heterogeneous data, and relates to the technical field of data analysis and processing, and the method comprises the following steps: normalizing a multi-source timestamp and retaining metadata information based on a UTC reference, an adjustable gain and a power exponent; in the streaming processing, reordering of out-of-order data and marking of expired data are realized by setting a buffer queue and a watermark threshold value; when null value fields or cross-source conflicts are detected, interpolation and conflict processing are carried out, and complete data subjected to consistency correction are output; then, an external high-precision reference or a cross-correlation function is used for further fine tuning the timestamp at a millisecond level, and if the adjustment amplitude exceeds a safety boundary, the timestamp is marked as suspicious; and finally, the corrected data is distributed to multiple nodes according to a fragment mapping strategy, and fault-tolerant consensus and difference repair are triggered under fault duration judgment, so that high-precision time sequence alignment and high availability in a massive concurrent scene are kept, data loss or precision attenuation caused by time sequence inconsistency and node faults is avoided, and the method can be widely applied to high-frequency analysis.

An improved system implements Fitness Gradient Consensus including hash distance and bucket consensus variations within a digital blockchain by calculating the highest fitness value competing blocks to resolve conflicts and allocate the rewards associated with building new blocks. The consensus system applies conflict resolution formulas to incentivize block-building nodes to share blocks generated, as it completes construction, to improve chances of a reward, resulting in enhanced speed and security of blockchain.The hash distance consensus utilizes a hash distance scalar value as part of its fitness metric, and the bucket consensus assigns tokens to buckets and calculates an aggregate value of the assigned tokens. A trust-but-verify variant increases transactional throughput and reduces linearity and computational constraints.The system also utilizes novel record types, such as token genesis, transfer, transaction, trade order, settlement, proposition, determination, and pattern linkage records to facilitate the automation of financial, commercial and legal processes.

The invention relates to the technical field of blockchain network security monitoring, and particularly discloses a blockchain-based network security monitoring method and system, the system collects transaction data, block data and intelligent contract execution results from a plurality of blockchain nodes, the analysis technology calculates the abnormal degree of each time window, the change rate of data inconsistency is quantified, and the data security monitoring accuracy is improved. If a relatively high data inconsistent change rate is detected, further comparing consensus results of the nodes, calculating consensus verification differences of the nodes, identifying the nodes deviating from normal consensus behaviors, constructing a machine learning model of a support vector machine, evaluating the safety states of the nodes, and according to a result output by the model, determining the inconsistent change rate of the nodes. The safety states of the nodes are divided into normal, slight abnormality and serious abnormality, for the nodes marked as slight abnormality, the system analyzes the abnormality trend and deviation of the nodes through a time sequence, automatically marks high-priority concerned nodes and generates a review task list to remind an operator to intervene.

The invention discloses a large-model-driven automatic knowledge graph construction method based on a confidence feedback mechanism, and aims to improve the structural accuracy and semantic consistency in a structured triple generation process, and perform structural constraint guidance by using a few-sample prompt mechanism and a cross validation mechanism of a heterogeneous large model. And the control capability of the large language model on the triple format is enhanced, so that format offset and semantic redundancy in the generation process are reduced. And meanwhile, a multi-dimensional confidence evaluation system is constructed, model consensus judgment, semantic rationality analysis and knowledge consistency verification are fused, and refined quantification and screening of triple quality are realized. According to the method, a confidence backtracking feedback strategy is introduced, a generation-verification-optimization closed-loop process is constructed, the expression and correction capability of the system on a complex knowledge structure is enhanced, the dependence on an external API is effectively reduced, the consumption of computing resources is reduced, and the operation efficiency of the system and the feasibility of engineering deployment are remarkably improved.

The invention discloses a vehicle-mounted controller firmware upgrading method, which relates to the technical field of intelligent networked automobiles, and comprises the following steps of: accurately describing a dependency relationship between versions by introducing a directed acyclic graph, providing a clear topological sorting basis for an upgrading process, and improving the upgrading efficiency. The system function conflict and disorder caused by disordered upgrading sequence are fundamentally avoided; a distributed consensus protocol is utilized to ensure that each controller achieves state coordination before upgrading, so that the overall robustness of a multi-controller cluster is effectively improved when the multi-controller cluster faces network delay or individual node abnormity, and upgrading failure or version bifurcation caused by the fact that part of nodes are not ready is avoided; through the combination of the group-level binding token and the atomic switching mechanism, the controller group with a strong function dependency relationship can be ensured to be effective and updated as a unified transaction unit, and the safety and reliability of cross-domain function linkage are remarkably enhanced.

The invention discloses a practical Byzantine fault-tolerant consensus method, device and equipment for commodity transaction in a block chain, a medium and a product, and relates to the field of block chains. The method comprises the following steps: initializing alliance chain network nodes, and dividing the alliance chain network nodes into a double-layer network structure comprising a main network layer and a secondary network layer; grouping in a secondary network layer according to the nearest neighbor communication time delay of the nodes; after each round of consensus is finished, reputation score calculation is carried out on the nodes based on attribute scores of mechanisms to which the nodes belong and dynamic behaviors of the nodes in the commodity transaction process, the node with the highest reputation score is periodically selected from each group to serve as a main node in the group, and other nodes in the group serve as common nodes; local consensus is carried out on the main node and the common node in each group in the respective group; and adding the main nodes in each group to a main network layer to participate in global consensus. According to the invention, the overall consensus efficiency and stability of the network can be improved, and stable and efficient transaction of commodities on the block chain is ensured.

The invention discloses a block chain transaction parallel execution method based on pre-execution conflict detection, and belongs to the field of block chains. The method specifically comprises the steps that a node receives a transaction sent by a user, and a verification node carries out pre-execution operation on the received transaction in idle time waiting for proposal of a main node; judging whether the transaction packaged by the elected main node is a pre-execution transaction, and if so, generating a transaction conflict graph according to the read-write set of each transaction; an independent set is solved repeatedly, and the main node performs optimistic parallel execution to obtain a transaction dependency graph and packages the transaction dependency graph into a proposal block; otherwise, the main node performs optimistic parallel execution on the transactions which are not pre-executed, constructs a directed acyclic transaction dependency graph, and packages the directed acyclic transaction dependency graph to generate proposal blocks; and finally, each verification node sequentially executes corresponding transactions according to the transaction dependency graph and performs comparison verification on an execution result and an execution result of the main node, and when the results are consistent, the proposal block is successfully linked, and the consensus of the round is completed. The optimistic parallel execution efficiency is improved.

The invention relates to the technical field of distributed storage verification, and discloses a storage information verification system based on a consensus mechanism. The system comprises a consensus network communication module, a storage feature analysis module, a verification decision core module, a time sequence prediction module, a decision compensation module and a verification execution engine module. The consensus network communication module is connected with a distributed storage node and receives a storage verification request; the storage feature analysis module extracts multi-dimensional feature vectors of the target data to form a feature descriptor set; the verification decision core module is combined with an embedded consensus verification space and dynamic confidence coefficient constraint condition operation to output an initial verification decision scheme; the time sequence prediction module divides a time window and generates a prediction feature descriptor set; the decision compensation module carries out deviation compensation according to the result to obtain an optimization scheme; and the verification execution engine module sends an instruction to trigger the distributed nodes to execute verification operation. A dynamic verification system constructed by the system adapts to dynamic characteristics and heterogeneous environments of distributed storage.

Various aspects of the disclosure relate to automated testing for application programming interfaces (APIs). A dynamic API validation computing system leverages a generative AI model to dynamically generate a multitude of data sets and rules for use during API validation activities. A federated byzantine agreement mechanism performs the validation of each API using the generated test cases and test data. A generator engine incorporates a generative AI model that may be trained on a large corpus of API metadata and / or data characteristics to predict data patterns and / or validation rules for each of the APIs under test. The generator engine may also predict a structure and format of requests based on the training model inputs. Multiple Test cases for an API created through use of the generative AI model may be distributed and executed on different testing nodes that reach a consensus about whether each API has passed or failed.

Disclosed are a blockchain sharding method and system based on a convolutional neural network-long short-term memory (CNN-LSTM) prediction model. The method includes: using a double-layer chain system architecture, namely a vehicle layer and an edge layer; and using a delegated byzantine fault tolerance (DBFT) as a consensus protocol of a network at the vehicle layer and using proof of authority (POA) as a consensus protocol at the edge layer. Load balancing of the blockchain sharding system is optimized through a CNN-LSTM prediction model. A transaction status of the entire sharding network in a next period is predicted. Hot accounts are effectively allocated through a designed account allocation algorithm. The blockchain sharding method can maintain load balancing of shards, reduce cross-shard transactions, and implement effective utilization of resources. Malicious behavior of nodes is restricted. Security of the network is ensured.

The invention discloses a multi-mechanism attribute-based encryption algorithm based on creditworthiness consensus and zero-knowledge proof, and relates to the field of blockchains. On the basis of traditional attribute-based encryption, creditworthiness evaluation is introduced, a decentralized trust model is established for evaluating and selecting trusted nodes, and the reliability of the algorithm is improved. According to the method and the system, the data can be shared and accessed in a credible environment, zero-knowledge proof is used for verifying the correctness and integrity of the data, specific data values or other sensitive information are not leaked, and the reliability of the data is improved by combining credibility consensus and the zero-knowledge proof technology. And an innovative and efficient solution is provided for data security sharing in a multi-mechanism environment.

The invention relates to a distributed storage and synchronization system based on a block chain, and belongs to the technical field of distributed file storage. The system comprises a node management module, a data fragmentation and distributed storage module, a consensus mechanism module, a data synchronization module, a cross-chain interaction module, a client interaction module and a decentralized node network. By optimizing a consensus mechanism and introducing a fragmentation technology and a cross-chain technology, the problems of expansibility and consistency of an existing system are solved, and interoperability between different block chain networks is realized. The system has high expandability and flexibility, supports access of various block chain network protocols and intelligent contract standards, and is easy to popularize and apply.

The invention belongs to the technical field of alliance chain consensus, and discloses an alliance chain consensus improvement method and system based on contribution degree and grouping, and a CG-PBFT algorithm aims at optimizing the performance and efficiency of a block chain network. According to the algorithm, the consensus set is grouped, so that the communication complexity among the nodes is reduced, the nodes in the group are easier to cooperate, and the throughput and efficiency of the network are improved. In order to solve the problems of performance imbalance, safety and resource consumption of a PBFT algorithm, a consensus mechanism based on contribution degree is introduced into CG-PBFT, and a node with the highest contribution degree is selected as a master node through management of a master node election stage. The node contribution degree is a measurement method for measuring the overall contribution of the nodes to the network, and the node data contribution degree and the online resource consumption are mainly considered. The CG-PBFT algorithm is combined with the PoC contribution degree algorithm and the PBFT algorithm, the consensus consistency and the final consistency of the nodes are ensured, and meanwhile, the risk that an attacker tampers the consensus is reduced by reasonably grouping the consensus nodes.

The present invention relates to the technical field of blockchains, and in particular to a blockchain-based multi-partition asynchronous parallel consensus method. The method comprises: constructing a multi-partition asynchronous parallel consensus blockchain system comprising a plurality of partitions and a plurality of guide nodes; for each partition, each ordinary node publishes and broadcasts transaction information in the partition to which it belongs, and each ordinary node collects and stores the transaction information published in the partition to which it belongs; each partition creates a partition block by executing an intra-partition consensus algorithm, and uses a main node to upload the partition block to a guide node; and each guide node sorts the collected partition blocks, and selects one partition block therefrom to execute an inter-partition consensus algorithm. The present invention enables the synchronous intra-partition consensus initiation and execution provided for in existing sharded blockchain systems to now be performed asynchronously, thus improving system parallelism, transaction information processing throughput, and cross-shard communication processing efficiency.

The invention discloses a switch load balancing method based on fuzzy logic control, and the method comprises the following steps: S1, monitoring a network state in real time through quantum sensing equipment, and obtaining related parameters; s2, transmitting the parameters to a fuzzy logic controller for processing; s3, generating a load distribution strategy according to a predefined rule; s4, transmitting the preliminary strategy to each switch node in the block chain network, and recording related data; s5, verifying the data by using a distributed consensus mechanism of the block chain; s6, dynamically evaluating a node trust value based on an enhanced fuzzy trust model, and selecting nodes meeting requirements to participate in a load balancing game decision; s7, carrying out cooperative calculation on the selected nodes by utilizing a game theory cooperation mechanism, and generating a globally optimized load distribution strategy; and S8, optimizing a load distribution strategy through a quantum genetic algorithm, and performing automatic execution through an intelligent contract. According to the method, the advantages of fuzzy logic, the block chain and quantum computing are combined, and the intelligence and safety of load balancing are improved.

The invention discloses a decentralized multi-agent information interaction method and system, and the method comprises the steps: generating a subtask carrying a unique identifier and metadata based on mixed dimension task decomposition, and embedding a global utility function; sub-task-agent mapping is dynamically adjusted through Kafka and Flink, and a utility function weight coefficient is broadcasted; the sub-agent determines an executor through contract network protocol bidding, and performs execution permission arbitration on key resources in combination with a token bucket algorithm; metadata are transmitted by adopting a Gossip protocol, and intermediate data are transmitted by P2P direct connection (abnormal degradation to Kafka); key metadata are synchronized through lightweight Raft consensus, and non-key metadata are merged by adopting CRDT; and after a final result is written in through Kafka, duplicate removal, sorting and aggregation are carried out through Flink, and key states are synchronized through Gossip. According to the method, the problem of message disorder under a hybrid protocol is solved; and high-reliability message transmission and state synchronization are realized by combining the strong consistency bottom of Kafka and the conflict resolution of lightweight Raft and CRDT.

The invention discloses a block chain fragment security expansion method of a trusted state synchronization chain, which realizes state consistency verification between fragments by constructing a Layer1 state synchronization chain, and adopts an unbiased random leader rotation mechanism based on a preorder block signature and an efficient two-stage submission protocol. Three rounds of communication of traditional BFT consensus are compressed into two rounds of parallel processing under a state fragmentation architecture, and a dynamic fragmentation recombination strategy and a state difference synchronization technology are combined, so that the core problems of throughput bottleneck, cross-fragmentation transaction atomicity, attack risk prediction by a leader, reduction of recombination efficiency and the like in a block chain fragmentation system are systematically solved; the parallel transaction processing is realized, the consensus time delay is reduced by 30%, the cross-fragment transaction verification efficiency is improved by 60%, the system throughput is linearly expanded along with the fragment number, and the system security is enhanced through a pledge economic model and a malicious node detection mechanism.

Disclosed in the present application is a blockchain-based distributed ensemble learning method. On the basis of a designed three-layer blockchain structure, which consists of a mini block, an ensemble block and a key block, by means of a consensus protocol, a miner in a network is enabled to train a base model on a training set after performing sampling with replacement, and aggregates models from other miners; and finally, information of the base model and information of an ensemble model are recorded in a blockchain, such that the whole process of model training, model ensemble and model evaluation is fused into a blockchain consensus, and the whole ensemble learning process is automatically executed in a blockchain network. In this way, the present application can increase the utilization rate of the computing power in a blockchain network by means of a proof-of-useful-work mechanism based on machine learning, and a center node is prevented from being introduced during a model aggregation process, thereby maximizing the degree of decentralization of a blockchain.

The invention discloses a virtual power plant operation management and control method based on a block chain, original power data are compressed into Hash fingerprints to be chained through a collaborative architecture of an edge computing layer and an AI pre-decision module, the block chain network load is effectively reduced, and a dynamic elastic PBFT consensus mechanism adjusts the scale of verification nodes in real time based on transaction types, so that the efficiency is improved. And compared with a traditional fixed node consensus mechanism, the network communication overhead is reduced. And a hash value asynchronous pre-verification technology is adopted, so that the interaction rate of the multi-dimensional power data is improved, and the efficiency is improved compared with that of a conventional data uplink mode. Through the decoupling design of the intelligent contract execution flow and the consensus verification flow and in combination with the pre-decision data cache queue, the resource scheduling instruction issuing time delay is reduced. The block chain transaction throughput is improved and is effectively improved compared with a standard alliance chain architecture, and the technical problems that the consensus mechanism processing transaction speed of an existing block chain is limited and the high-frequency real-time data interaction requirement of a virtual power plant is difficult to meet are successfully solved.

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

The invention belongs to the technical field of cross-data island consensus, and particularly relates to a cross-data island consensus verification method and system based on credibility scoring. According to the invention, by dynamically evaluating the trust degree of each data island and combining network state fluctuation, real-time verification and abnormal early warning of a consensus result are realized, the stability and safety of cross-data island cooperation are effectively improved, the data consistency is ensured, the data risk caused by network fluctuation is reduced, the self-adaptive capability of the system is enhanced, and the method is suitable for large-scale popularization and application. In the consensus process, historical interaction events and a current cooperation state of a data island are considered, efficient alignment of cross-island features is achieved through a gradient exchange mechanism, a standardized consensus data view is generated, in addition, self-adaptive adjustment of a consensus verification rule is ensured by pre-deploying a trusted execution environment, and the consensus verification efficiency is improved. And the consensus accuracy and efficiency are further improved.

The invention relates to a multi-robot system global flexible preset performance control method under an unknown state and a DoS attack, and belongs to the technical field of multi-robot system control. Aiming at the problems in the prior art that the communication topology is unstable due to attack, the initial error constraint is strict, and the input saturation conflicts with the performance, the following scheme is provided: dynamically reconstructing the attacked communication topology based on a bipartite consensus layering algorithm; designing a global error constraint mechanism fusing the scale function and the tunnel type performance function; constructing a balance control input and performance boundary of the input saturation self-adaptive auxiliary system; and estimating an unknown state and compensating an observation error by adopting a state observer. The method has the technical effects that the DoS attack resistance of the system is enhanced, the global preset performance control of any initial error is realized, the contradiction between input saturation and tracking performance is dynamically coordinated, and the multi-robot collaborative operation under the unbalanced topology is supported.

The invention discloses a distributed extensible deterministic transaction execution method for a fragment permission chain system, which is characterized in that distributed multi-version tentative deterministic concurrency control and batch transaction submission mechanism strategies are adopted to realize multi-node extensible deterministic transaction concurrency execution under a conflict load. According to the distributed multi-version tentative deterministic concurrency control, a batch of transactions in a block are sorted in advance in a consensus manner, and a globally unique and automatically increasing transaction sequence number is allocated, so that a result of concurrent execution of the transactions is equal to a result of serial execution according to the transaction sequence number; according to the batch transaction submission mechanism strategy, submission of a plurality of cross-piece transactions is combined and processed by adopting batch processing, and network overhead required by submission is uniformly shared. Compared with the prior art, the method has the advantages that multi-node expandability under conflict loads is realized in a distributed scene, strict certainty of an execution scheme is guaranteed, the overall performance and transaction processing performance of the system are improved, and the method has a good application prospect.

The invention discloses a block chain-based consensus authentication method and device, electronic equipment and a program product, and relates to the technical field of block chains, and the method comprises the steps: generating a pre-preparation message based on a financial transaction request initiated by a client through a main node, and broadcasting the pre-preparation message to all consensus nodes, part of preparation messages returned by consensus nodes are received through a main node, signatures in the part of preparation messages are aggregated into batch signatures under the condition that the validity verification of the messages is passed, submission information is generated based on the batch signatures, and the submission information is broadcasted to all the consensus nodes. And counting the number of the consensus nodes which pass verification of the aggregated batch signatures, and completing the consensus authentication process of the current batch transaction under the condition that the number of the consensus nodes reaches a preset node number threshold value. According to the method and the device, the technical problems of low consensus efficiency and complex verification process when the alliance chain adopts a batch processing signature mechanism to perform batch processing in a high-concurrency transaction processing scene in the related technology are solved.

Connection units 200A, 200B connect to a data distribution platform and form a consensus on a contract including an asset and a policy shared among users. Execution units 230A, 230B start a secure isolated execution environment isolated by using an image of an execution environment including a policy execution program that operates according to the contract, and receive and process data according to the contract in the isolated execution environment. At least one of the isolated execution environment, the image of an execution environment, the contract inputted to the isolated execution environment, the data received in the isolated execution environment, and the processing result in the isolated execution environment is remotely attested.

Systems and methods for controlling resource utilization for a consensus-based distributed group of replicas are provided. A leader node can receive a write request originating from a tenant and comprising instructions to write to data of replicas of a range. The leader node stores a leader replica, follower nodes each store a follower replica, and the leader node is configured to coordinate a consensus protocol for executing the instructions. The leader node and the follower nodes each correspond to at least one of a plurality of token pools. Sizes of the token pools are determined based on receiving the write request. The write request is evaluated based on the sizes of the token pools by determining a size of the write request and generating a log entry for the write request. The write request is executed using the log entry by writing to the data of the replicas.

An improved system implements Fitness Gradient Consensus including hash distance and bucket consensus variations within a digital blockchain by calculating the highest fitness value competing blocks to resolve conflicts and allocate the rewards associated with building new blocks. The consensus system applies conflict resolution formulas to incentivize block-building nodes to share blocks generated, as it completes construction, to improve chances of a reward, resulting in enhanced speed and security of blockchain.The hash distance consensus utilizes a hash distance scalar value as part of its fitness metric, and the bucket consensus assigns tokens to buckets and calculates an aggregate value of the assigned tokens. A trust-but-verify variant increases transactional throughput and reduces linearity and computational constraints.The system also utilizes novel record types, such as token genesis, transfer, transaction, trade order, settlement, proposition, determination, and pattern linkage records to facilitate the automation of financial, commercial and legal processes.

The invention discloses a manufacturing task autonomous negotiation and execution method based on a large language model agent, and the method comprises the steps: constructing a production scheduling agent, an equipment management agent, a material distribution agent and a quality control agent, analyzing a natural language task instruction through the production scheduling agent, and decomposing the natural language task instruction into subtasks; each agent calculates a utility value based on the load rate, the resource matching degree, the estimated completion time and the historical success rate, and performs structured negotiation to achieve a task allocation consensus; a prediction-check-rollback architecture is adopted to generate an action instruction sequence, the sequence is compiled into a time Petri network transition sequence, and reachability verification is carried out based on hard security constraints; production environment data is collected in real time to trigger anomaly detection and re-negotiation, and a formalized security verification and causal anti-factual reasoning parameter updating mechanism is introduced. According to the method, unstructured instruction understanding, autonomous task planning, multi-agent collaborative decision and closed-loop optimization are realized, and the problems of real-time performance, safety and interpretability of a large language model in manufacturing control are solved.