21 results about "Discrete event system" patented technology

The application discloses a kind of supervision control strategy generation methods based on counterexample guide deep reinforcement learning, comprising: one, definition model;Two, supervision control strategy generation, the method with deep Q network as reinforcement learning subject, introduce online counterexample guide verification mechanism, using counterexample search dynamic correction control permission dictionary and optimizing reinforcement learning strategy, finally coupling convergent deep network parameters and whole state space dynamic permission dictionary, generate with global non-blocking characteristics coordinated supervision control strategy.This method can meet non-blocking and approach maximum allowable supervision strategy without explicitly constructing the global state space of controlled discrete event system, balance between computational complexity and strategy allowance, provide a new technical approach for non-blocking control of super large scale discrete event system.

The invention discloses a dual-time Petri network system activity control method based on time parameter adjustment. The method comprises the following steps: establishing sufficient and necessary conditions of activity violation caused by improper configuration of time parameters of a system; constructing a plurality of parameter adjustment options considering the adjustment cost, wherein the parameter adjustment options are used for modifying static time parameters of the system; two parameter adjustment strategies based on cost are provided, active violation existing in the system is recursively processed, that is, feasible time parameter configuration is iteratively synthesized and the overall adjustment cost is minimized by focusing on eliminating a specific active violation in each iteration step. The two strategies verify the validity of the generated solutions; the single-option adjustment strategy verifies the solutions corresponding to the single adjustment options one by one, and selects the feasible option with the minimum cost for iteration; according to the multi-option adjustment strategy, a parameter optimization problem corresponding to single activity violation is modeled into a linear programming model, and a feasible solution is solved to realize multi-parameter collaborative optimization. The invention provides a technical scheme of time parameter regulation and control based on a dual-time Petri network for a discrete event system with complex time constraint, and can effectively realize formalized verification and guarantee of system activity.

The invention relates to a method, implemented by a computer infrastructure, for controlling the sequential change in a resource of a discrete event system, said change being modelled by a state machine having a plurality of states and at least one transition for changing the current state of the resource from a first state to a second state on the occurrence of a predefined event, the method comprising the following steps: reading a first computer object representing the resource, said first computer object describing the current state of the resource and comprising a function that is intended to be executed automatically by the computer infrastructure in the event of a request to change the current state of the resource from the first state to the second state; executing the function associated with the requested state transition from the first state to the second state.

The invention provides a reliable fault diagnosis method for a random discrete event system and application thereof, and the method comprises the steps: firstly, defining a dynamic observation activation method for the random discrete event system; secondly, according to formalization-reliable dispersion diagnosability of the dynamic observation activation method, a local random-diagnostor is constructed for each local site according to the dynamic observation activation method; and finally, constructing a reliable-co-diagnostor according to the local random-diagnostor, verifying the reliable dispersive diagnosability of the random discrete event system according to the reliable-co-diagnostor, and performing reliable dispersive diagnosis of the random discrete event system under an observation activation method, reliable diagnosis is popularized from a discrete event system to a random discrete event system, and an observation activation method is introduced to realize dynamic switching of a sensor so as to optimize configuration, so that the robustness of the system under the scenes of sensor failure, network congestion and the like is remarkably improved.

The application discloses a parallel time sequence advancing method and electronic equipment suitable for discrete event system simulation, and comprises the following steps: starting a main program of simulation deduction, and updating an event queue list; according to time stamps of sequence events in the updated event queue list, calling resources corresponding to the sequence events on demand, and executing subprograms of the sequence events; after receiving a mutation state signal, generating a random event according to the mutation state signal, and setting a time stamp and a highest priority of the random event; according to the time stamp and the highest priority of the random event, adopting a triggered event parallel response method, and executing a subprogram of the random event; after executing the subprogram of the random event, continuing to execute the subprograms of the sequence events in the event queue list until the main program of simulation deduction is ended, and generating a simulation report. The application simultaneously satisfies a hybrid execution logic of script type prefabricated execution and event triggered generation and parallel response execution at any moment, and improves flexibility and randomness of a military simulation deduction system.

The present invention discloses a real-time system security verification method and system for a discrete event system. The method comprises the following steps: establishing a Time Labeled Petri Nets model of the discrete event system based on discrete event system information, wherein the discrete event system information includes events, labels, and time information; applying a real-time observation expression of the discrete event system and an expression of an initial secret state of the discrete event system to the Time Labeled Petri Nets model of the discrete event system to obtain real-time observations of the discrete event system and an initial secret state of the discrete event system; constructing an integer linear programming mathematical problem model based on constraint conditions for verifying real-time security of the discrete event system; introducing the real-time observations of the discrete event system and the initial secret state of the discrete event system into the integer linear programming model for solving and verifying the security of the integer linear programming model to obtain a verification result; and judging the security of the discrete event system based on the verification result.

The invention belongs to the technical field of information security, and relates to a smart home temperature control system opacity strengthening method based on a tag time Petri network. Establishing a label time Petri network model of the intelligent household temperature control system; constructing a partial correction state class diagram based on time sequence observation of which the current state is not transparent, forming a path constraint model consistent with observation logic, and identifying a path set inconsistent with observation time; screening a path which meets the opaqueness of the current state relative to the secret identifier set in the path set, and constructing a linear programming model to solve a minimum time sequence disturbance function value; and updating the original time sequence observation by using the perturbation function, and generating a new observation sequence meeting the opaqueness of the current state. According to the method, an attacker is effectively prevented from deducing the real state of the system through a time sequence, meanwhile, exhaustive search on a full-state space is avoided, the calculation complexity is reduced, and the applicability and expandability of the method in a complex discrete event system are improved.

This invention discloses a method for quantifying the current state opacity of discrete event systems, belonging to the technical field of current state opacity quantification for discrete event systems. The method involves constructing a resource automaton model and a resource intruder model based on a nondeterministic finite state automaton, and further constructing a resource game theory model on this basis. Game theory is then introduced to quantify the current state opacity of the discrete event system. This invention can achieve accurate quantification of the current opacity of discrete event systems, adapting to environments where system behavior has inherent uncertainty and faces proactive analysis by intelligent attackers. It can also maximize its own utility and meet the needs of refined evaluation of system privacy and security in practical applications.

This invention relates to a differential privacy enhancement method for a discrete event system in a smart building, comprising: obtaining the initial resource configuration of the smart building system; representing the initial resource configuration using a probabilistic automaton; and establishing a differential privacy mechanism for the smart building system; calculating the probability distribution of the smart building system's behavior under similar initial resource configurations using a differential privacy verifier; verifying whether the smart building system satisfies the differential privacy mechanism using the probability distribution; if it does not satisfy the differential privacy mechanism, calculating a replacement function for the smart building system; and using the replacement function to control the probabilistic automaton to replace the observation symbols of system events. This invention ensures that attackers cannot infer the current initial resource configuration information of the system through external observation.

The application belongs to the technical field of fault diagnosis of discrete event systems, and particularly relates to a research method of fault diagnosis of discrete event systems based on a lambda-free Petri net, which comprises the following steps: S1: constructing a labeled lambda-free Petri net model for a discrete event system; S2: judging whether a fault can be detected through an observation sequence with a limited length, that is, whether the system is diagnosable; S3: if the system is not diagnosable, then a verification net is constructed on the basis of the original Petri net, the reachable tree thereof is unfolded and pruned by using the system structure captured in the verification net, and labels that need to be relabeled are searched. The application can help to improve the efficiency and accuracy of fault diagnosis, and the Petri net model after removing empty transitions can reduce the complexity of system description, thereby simplifying the fault diagnosis process.

The invention discloses a discrete scheduling-oriented hierarchical timing Petri net deduction simulation and conflict resolution method. The method comprises the following steps of: realizing hierarchical modeling of a discrete task; specifically, a hierarchical timing Petri net model is composed of a place, transition, a flow relation, place time delay, transition time delay, an identifier and a mapping function, hierarchical modeling of discrete tasks is achieved, a subtask hierarchical timing Petri net and a meta-task hierarchical timing Petri net are included, the former shows operation logic of a composite task on a subtask level, and the other shows operation logic of the composite task on a meta-task level. The latter shows specific execution steps of the composite task at the meta-task level; an execution library in the sub-task level timing Petri net can be mapped into a meta-task timing sub Petri net in the meta-task level through a mapping function; the hierarchical timing Petri net model takes a discrete task scheduling result as input, realizes dynamic conflict resolution of the discrete task scheduling result in a deduction simulation process, and is particularly suitable for simulation of discrete event systems such as intelligent manufacturing tasks, intelligent logistics processes, industrial automation system cooperative control and the like.

The invention discloses a method for predicting a robust fault of a random discrete event system under observation loss, and the method comprises the following steps: constructing a random robust verifier of a random automaton of a manufacturing system, obtaining the state of each operation stage of the manufacturing system and the operation and fault of the manufacturing system, constructing an event set based on a monitoring sensor group of the manufacturing system, and predicting the fault of the random discrete event system. The random robust verifier synchronizes an observation permanent loss scene of the adaptive event set; collecting a boundary state set of a random robust verifier; and screening a boundary state and a reachable part of a state reached by another path event string matched with the event string projection of the boundary state, outputting a ring type of the reachable part, judging random robustness predictability, and outputting a fault prediction result. According to the method, the problem of event observation loss caused by sensor faults, signal transmission interference and the like in an actual scene can be effectively solved, stochastic discrete event system fault prediction can be accurately realized, the limitation of observation loss scenes is broken through, and stochastic discrete event system fault prediction requirements are met.

The application discloses a fault diagnosis method for a discrete event system based on events and partially observable states, and comprises the following steps: S1, acquiring a discrete event system to be diagnosed, and modeling the discrete event system into a deterministic finite state automaton, wherein observable behaviors of the discrete event system comprise an observable event set and an observable output set; S2, defining event-output pairs based on the automaton; S3, defining observable event-output pairs and observable event-output pair sequences composed of the observable event-output pairs based on the event-output pairs; S4, constructing a verifier automaton taking the observable event-output pairs as events, wherein states of the verifier automaton carry information about whether the discrete event system is faulty; and S5, judging whether the discrete event system is diagnosable. The application realizes effective diagnosis of the diagnosability of a system under the condition that both events and states are partially observable.

The application provides a position information hiding method based on random discrete event system active opacity, which comprises the following steps: modeling a position information hiding system as a random discrete event system, and constructing a k-step active opacity verifier V according to a mathematical model of the modeling G , further constructing a Markov chain M, calculating a probability of exposing a secret position after each position information hiding scheme is enforced, judging whether there is at least one position information hiding scheme corresponding to a probability less than a preset threshold, if yes, the mathematical model of the random discrete event system has random k-step active opacity, and the position information hiding is completed; otherwise, a new position information hiding scheme is generated; the application simultaneously presets multiple position information hiding schemes, introduces active control into the opacity research, verifies the k-step active opacity, improves the control ability of the opacity, widens the application range of the active opacity, and can effectively realize reliable hiding of the position information.

The invention belongs to the field of discrete event system control, intelligent manufacturing and reinforcement learning, and discloses a state feedback control strategy generation method and system of a time delay Petri network system in a non-deterministic environment, and the method comprises the steps: constructing a time delay Petri network model containing controllable / uncontrollable transition and minimum transmission delay constraint, defining a time extension state formed by the identification and the enable transition residual delay; a two-stage random judgment mechanism is introduced, two types of non-deterministic factors of control execution errors and uncontrollable event preemption are modeled, and the state transition probability is deduced; a control problem is formalized into a Markov decision process, and a reward function with time consumption as a negative reward and deadlock and an ultra-long path as strong punishment is designed; and adopting a table type Q learning algorithm based on dynamic learning rate scheduling, iteratively updating an action value function in interaction with a simulation environment, and exporting a state feedback control strategy. The method can be widely deployed in discrete event system control scenes such as flexible manufacturing, logistics scheduling and multi-robot cooperation.

The invention discloses a high-throughput-oriented period scheduling method, and belongs to the technical field of industrial production period scheduling. The method comprises the following steps: inputting production data, wherein the production data comprises operation area division information, equipment information and process flow information of process processing; constructing a technological process automaton model for each technological process based on a discrete event system supervision and control simulation platform, and generating non-deadlock candidate scheduling paths meeting technological requirements by taking operation areas, technological steps and equipment as scheduling path nodes; taking the candidate scheduling path with the shortest total processing time length of each production cycle as an optimal scheduling path; and dispatching information is distributed to each corresponding operation device in the operation area based on the optimal dispatching path, so that the processing operation of the processing object is executed based on the received dispatching information. According to the method, the equipment utilization rate can be maximized, the production period is shortened, and smooth connection of all process stages is ensured; and the production efficiency is ensured, and the resource utilization maximization is realized at the same time.

The invention discloses a construction method of an energy management system information estimator based on data driving. The method comprises the following steps: 1, defining a model; 2, constructing an information estimator; according to the technical scheme, the dependence of traditional supervision and control on an accurate model is broken through, state and income joint estimation is realized under partially considerable and model-unknown conditions, and a feasible technical scheme is provided for quantitative control of complex discrete event systems such as a high-performance energy management system. The method can support optimal supervision control strategy synthesis of energy benefit management in a model-free and partially considerable environment.

The application provides a kind of explainable fault diagnosis system and method of discrete event system, adopts the calculation mode of combining off-line construction fault diagnosis device and on-line fault diagnosis, while fusing field expert knowledge, according to the possible mode of system fault given by field expert, customizes limited linear time logic formula template, takes the historical operation log of system as sample, encodes fault diagnosis problem as satisfiability problem, obtains the explanation of each type of fault behavior of system: FLTL formula with the help of SAT solving technique.These FLTL formulas can form on-line fault diagnosis device on the one hand, and also provide the explanation and analysis of system fault, which can provide decision support for later system fault recovery and system improvement;Thus, the defect that existing DES fault diagnosis technology is difficult to provide explainable fault diagnosis is solved.

The invention belongs to the technical field of industrial manufacturing, and particularly relates to a tag time Petri net-based time-assigned discrete event system fault diagnosis method, which comprises the following steps of: S1, modeling a time-assigned discrete event system by using a tag time Petri net; s2, on the basis of a time-label sequence (TLS), a modified state class graph (MSCG) is constructed, and a transition sequence which is logically consistent with the TLS is found out; s3, proposing a method based on linear programming by utilizing time constraints related to a transition sequence consistent with the TLS logic in the observable MSCG so as to judge the transition sequence consistent with the TLS time; and S4, according to the transition sequence consistent with the TLS time, judging whether the system has a fault or not. The invention provides a tag time Petri network system fault diagnosis method based on a tag time Petri network, which solves the problems in the background technology, reduces the calculation complexity and is more suitable for a complex system.

The invention relates to the technical field of fuzzy discrete event systems, and provides a testability judgment method for a distributed constrained fuzzy discrete event system. The method comprises the following steps: giving a distributed constrained fuzzy discrete event system to be subjected to fuzzy testability judgment, wherein the distributed constrained fuzzy discrete event system is provided with a plurality of distributed sites; constructing a partial observator corresponding to each distributed site, and finding out all fuzzy observable event sequences of the distributed sites by using the partial observator; solving the certainty of the fuzzy state of the distributed constrained fuzzy discrete system from the initial state to the fuzzy observable event sequence, and solving the fuzzy testability of the fuzzy observable event sequence based on the certainty of the fuzzy state; and judging the fuzzy testability of the distributed constrained fuzzy discrete event system based on the certainty of the fuzzy state and the fuzzy testability of the fuzzy observable event sequence. By adopting the method, the fuzzy testability can be popularized from a constrained discrete event system to a distributed constrained discrete event system, and the application range of the fuzzy testability is widened.

The application provides a UAV communication deployment and scheduling method for on-the-spot adjustment tasks, comprising: constructing a discrete event system corresponding to each UAV based on a predefined event space, a state space, and a state transition rule corresponding to the event space and the state space; under the discrete event system, constructing a UAV redeployment optimization model under a preset constraint condition, with the goal of maximizing the system utility of a UAV cluster under a current redeployment task; solving the UAV redeployment optimization model to obtain an optimal redeployment strategy of the UAV cluster under the current redeployment task, and scheduling the UAVs in the UAV cluster to execute the current redeployment task based on the optimal redeployment strategy; the system utility is obtained based on the total link capacity, the communication rate variance, and the total energy consumption of the UAV cluster. The application improves the agility and flexibility of the response to emergencies, improves the stability of the communication service, and improves the reliability of the UAVs in executing long-time tasks or in complex and variable scenarios.