7 results about "Hybrid automaton" patented technology

The invention relates to the technical field of solvent extraction separation and process automation control, in particular to an extraction separation system for medicinal material extraction, which comprises a controlled object interface layer, an industrial internet of things acquisition unit and an edge execution and monitoring unit. Data such as solvent ratio is collected, and the on-line detection assembly outputs a first component indication and a second component indication of the crude extract and the purity of the recovered solvent. The cloud twinborn optimization platform comprises an extraction-recovery coupled hybrid automaton digital twinborn model library (comprising a counter-current extraction stage, a replacement flushing stage and stage switching guard conditions) and identifiability judgment, online identification, mixed integer double-layer optimization, anti-fact admission and reachability verification modules, and generates a strategy evidence packet; and the edge side verification is executed and is monitored in a consistent invariant manner, and the preset security policy is rolled back abnormally. According to the method, a strategy is generated through cloud twin identification optimization, and an evidence packet is issued to edge gating execution after verification; and the abnormal rollback security policy is monitored consistently.

This invention relates to the field of new energy storage power station operation and management technology, and discloses a data-driven collaborative operation and management system for new energy storage power stations. The system includes: a system modeling and state perception module that uses a stochastic hybrid automaton to model the cloud-edge collaborative system of the energy storage power station in an integrated manner. This module characterizes the continuous dynamics and random disturbances of the equipment's physical evolution and constructs a stochastic transfer model of discrete events in cloud-edge interaction. Combined with the system state definition of multiple operating modes and switching conditions, it acquires the real-time state and completes state estimation. An information value decision-making and primary triggering module determines the state based on the state estimation results and local information sets. This data-driven collaborative operation and management system for new energy storage power stations addresses the core defects of existing technologies, such as poor adaptability to complex operating conditions, weak module collaboration, and an imbalance between safety and value. It avoids ineffective communication and energy waste, ultimately achieving a dynamic balance between the safety of the energy storage power station and its economical operation, significantly improving the system's operational reliability and overall benefits.

The invention provides a method and device for evaluating the local inertia supporting capacity of a new energy delivery type AC / DC power system, and relates to the technical field of power system operation and control, and the method comprises the steps: building a parameterized differential-algebraic equation model; deriving an inertia distribution matrix of the power system by using a generalized energy framework, and calculating a local inertia supporting capability index of each network node based on the inertia distribution matrix; determining the network region of which the index value is lower than a preset index threshold value as an inertia weak region, and predicting the dynamic evolution trend of the inertia weak region based on a hybrid automaton model to obtain a prediction result; and establishing a mapping relation between the inertia supporting capability of the inertia weak area and the commutation failure risk of the high-voltage direct-current converter station, and evaluating the stability margin of the system. According to the method provided by the invention, the problem that the inertia space-time heterogeneity cannot be identified and evaluated by a traditional method can be solved, and accurate identification and risk evaluation of a region with weak local inertia supporting capability can be realized.

The invention provides an urban anti-terrorism system modeling and verification method based on DoDAF-DSM, and relates to the field of military simulation modeling. The method comprises the following steps: constructing a system for urban anti-terrorist combat based on a DoDAF framework, and standardizing and describing the purpose, capability, architecture and flow of the anti-terrorist combat. An urban anti-terrorist combat meta-model is defined through a DSM specific domain modeling method, and standardized packaging and rapid reuse of concept knowledge are achieved. And converting the urban anti-terrorist combat model into a simulatable hybrid automaton model through a meta-model mapping rule, and performing simulation solution on the hybrid automaton model to realize logic simulation verification. And performing dynamic simulation verification on behavior logic correctness and information interaction consistency of the combat activity model and the state conversion model. According to the method, the urban anti-terrorism complex combat system can be efficiently and accurately expressed, a model-driven simulation verification technology provides a new way for model correctness inspection, and a new guidance basis is provided for future urban anti-terrorism system top-level design.

This invention relates to the field of public safety resilience assessment technology, and discloses a method, terminal, and medium for cascading failure simulation of elderly care facilities based on hybrid automata. The method divides the infrastructure of elderly care institutions into multiple subsystem components and establishes a unified interface naming system for each subsystem component. It uses open hybrid automata to uniformly model each subsystem component, obtaining corresponding hybrid automata models, forming an overall cross-system coupled model. Under a preset disaster scenario, a multi-timescale adaptive synchronization algorithm based on event density is used to perform discrete-continuous co-simulation of the cross-system coupled model, outputting time-series trajectory data. Based on the time-series trajectory data, a cascading vulnerability directed graph is constructed, and the key failure chains leading to the interruption of core services are identified. This invention can provide quantitative decision support for elderly care institutions to locate weak points and carry out precise reinforcement.

The invention discloses an agricultural robot multi-task collaborative operation system based on air-ground linkage, and the system comprises a data collection module which is used for collecting multi-source state data; the data preprocessing module is used for generating standardized multi-source state data; the hybrid automaton modeling module is used for establishing an improved hybrid automaton model; the operation stage judgment module is used for generating a multi-task operation stage state sequence; the cooperative node extraction module is used for forming a participating node set; the cooperative connection structure generation module is used for generating a minimum cooperative connection structure; the cooperation relation determination module is used for determining a cooperation path, a cooperation sequence and a cooperation relation; and the cooperative execution control module is used for controlling execution of multi-task cooperative operation. By introducing the improved hybrid automaton model, efficient cooperation and flexible linkage operation of the aerial operation unit and the ground agricultural robot in the multi-task operation process is achieved.

The invention relates to the technical field of constructional engineering, and discloses a digital modeling-based ultra-large-area factory building rapid construction process, which comprises the following steps of: constructing a digital model system of a construction object; constructing a construction state diagram and generating all feasible construction scheduling paths; establishing a multi-target optimal control model, solving a continuous control track of the multi-target optimal control model, and calculating a corresponding target function value; performing normalization evaluation on the target function value, and selecting an optimal construction path based on a preset weight strategy; exporting the scheduling information and the control data of the optimal construction path as a construction control instruction file; and collecting field state data, and dynamically updating the state of the multi-target optimal control model according to the collected data. Through the hybrid automaton model, the problem of separation of scheduling and physical control in a traditional method is solved; linkage balance of construction period, energy consumption and carbon emission is realized; the construction disturbance is effectively dealt with; a normalized evaluation and variable weight mechanism is adopted, so that path selection can be dynamically adapted to targets in different stages.