11results about How to "Realize coordinated control" patented technology

This invention relates to the fields of machine learning and edge computing technology, specifically to a blockchain-based trusted distributed hybrid expert model edge computing system. The system includes a task publisher for publishing learning tasks, which may be training or inference tasks; a blockchain network for receiving learning tasks and evaluating expert weights to obtain sparse activation expert index results; a blockchain network for receiving learning task processing results from the edge layer and achieving consensus; a gating network deployed within the blockchain network; an edge layer for downloading the corresponding expert model from the storage layer based on the sparse activation expert index results to process the learning tasks and uploading the processing results to the blockchain network; and a storage layer for storing all expert networks, each with a CID. This invention significantly improves the defense capability of the distributed MoE network against malicious edge node data tampering attacks, thereby ensuring the learning performance of the MoE system.

The application discloses a method for analyzing the interaction of multiple grid-connected inverters based on matrix norm theory, and aims at the interaction between grid-connected inverters, takes a power distribution system containing two grid-connected inverters as an analysis object, establishes an equivalent grid-connected model containing two inverters based on the Norton theorem, derives a transfer function matrix of a control system, and quantitatively analyzes the relationship between the interaction between inverters and the system frequency, equivalent grid-connected inductance and controller combination mode based on the spectral norm and condition number of the transfer function matrix, so as to provide a reference for the coordinated control of the inverters. A simulation model is built in Matlab / Simulink for analysis. The application provides a simple and effective method for analyzing the interaction of inverters, and provides a theoretical method for the coordinated control of the inverters.

This application relates to the fields of power technology and energy storage technology, and in particular to a method, apparatus, equipment, and medium for scheduling a grid-connected distributed energy system. The system includes at least one edge energy node, a distribution bus, and an energy metering device. When any edge energy node enters the current cycle, the system acquires the net external power collected by the energy metering device and compares it with the target power to obtain a power deviation value. Based on the power deviation value and the energy state information of the edge energy node, droop control calculation is performed to obtain the current energy storage output power. Based on the current energy storage output power, power output is executed and the cycle repeats. This application establishes independent control of each edge energy node in the grid-connected distributed energy system through droop control calculation. It effectively achieves coordinated control of system-level power without the need for a central controller, improving the reliability, autonomy, adaptability, and real-time performance of the grid-connected distributed energy system control.

The application discloses a power grid frequency control method and device, equipment and storage medium, relates to the power grid frequency control technical field, and includes: obtaining an optimal energy storage configuration scheme, wherein the optimal energy storage configuration scheme is obtained by global optimization and solution based on a preset energy storage optimization configuration model; collecting power grid real-time operation data according to the optimal energy storage configuration scheme, extracting power grid operation characteristics, and generating a feedforward power compensation reference value based on the power grid operation characteristics; generating an adaptive optimal control instruction using a preset decision model based on the power grid operation characteristics and the feedforward power compensation reference value; checking and correcting the adaptive optimal control instruction based on a preset full-scenario safety constraint rule, and issuing the corrected executable control instruction to an execution unit to realize power grid frequency coordinated control. The application can realize full-scenario frequency stability support in normal state, disturbance and black start, and significantly improve the inertia level, disturbance resistance and fault recovery speed of high-proportion new energy power grids.

The invention relates to the technical field of intelligent park digital operation and maintenance, in particular to a multi-node collaborative intelligent park digital operation and maintenance system and a control method, and the method comprises the following steps: collecting multi-source operation data, and executing protocol conversion, time synchronization and local jitter removal processing at a gateway end; sending the processed collected data to a central access layer, carrying out authentication and flow limiting on the data, and writing the data into message middleware; mapping data accessed by the message-oriented middleware to a unified asset model and performing unit and semantic standardization; writing the time sequence data into a time sequence database, and writing the event and the audit information into an event and audit library; and performing missing interpolation, quality labeling and preliminary filtering on the data. According to the invention, through a hierarchical alarm and strategy scheduling mode, the accuracy of abnormity identification and the timeliness of operation and maintenance processing are improved, the frequency of manual intervention is reduced, and the stability and reliability of system operation and the overall efficiency of intelligent park digital operation and maintenance are improved.

The present application relates to the technical field of industrial nondestructive testing, in particular to a nondestructive testing robot welding seam automatic tracking system based on multi-modal sensing. It comprises a data acquisition module, a data preprocessing module, a data fusion module, a trajectory generation module and a motion control module. Point cloud data is obtained by a laser scanner, image information is obtained by an RGB-D camera, and attitude data is obtained by an inertial measurement unit. After denoising, downsampling and correction processing of multi-modal data, data fusion is realized by Kalman filtering, and continuous welding seam spatial trajectory points are output. The trajectory generation module generates end pose sequences through three-dimensional B-spline fitting and surface normal estimation, and adopts quaternion interpolation for attitude smoothing processing. The motion control module combines differential path keeping and hybrid position-force control to ensure that the robot accurately tracks along the welding seam centerline and maintains constant contact force, while having process correction function to improve the stability and reliability of the system in complex welding seam environment.

The present application provides a kind of immersion probe window self-cleaning method and device, belong to immersion probe technical field, the present application constructs acoustic pressure distribution prediction model using physical information neural network to optimize transducer installation position, adopts square wave signal generator to realize the time-sharing control of cleaning and detection, utilizes dynamic time warping algorithm to match the real-time transducer impedance change time sequence with cleaning success time sequence template library to adaptively determine the cleaning completion state, determines the detection equipment start time dynamically through vibration attenuation real-time monitoring module, and the cleaning intensity is closed-loop regulated by artificial intelligence light window pollution evaluation model and driving power adaptive adjustment function, solve the technical problems that cleaning completion state cannot be adaptively determined in the self-cleaning process of immersion probe window, leading to fixed cleaning time and unable to adapt to different pollution conditions.

The invention discloses a storage space humidity control method and equipment. The method comprises the steps that the environment humidity in a storage space is obtained, and the deviation between the environment humidity and the preset safety humidity is determined; determining a humidity load state based on a change trend of the environment humidity in a preset time range; automatically switching different humidity control operation stages according to a combination result of the humidity deviation and the humidity load state; and in the different humidity control operation stages, differential adjustment is carried out on the operation parameters of the humidity control equipment. By introducing a control strategy combining multi-parameter sensing, trend analysis and staged control, the problems that an existing humidity control system is lagged in response, frequently started and stopped, unstable in humidity control, high in energy consumption and the like are effectively solved. According to the scheme, the safe target humidity is adaptively set based on the grain type, trend analysis is carried out by utilizing the historical humidity data, and the change of the environment humidity is pre-judged in advance, so that the lagging adjustment risk caused by single-point threshold control is avoided.

The application relates to a constant pressure variable air volume control method and related device for a barrier level laboratory animal room, which comprises the following steps: obtaining a current time and an indoor ammonia concentration, and selecting a mode based on the current time and the indoor ammonia concentration; wherein the selectable modes include a daytime mode and a nighttime mode; adjusting and setting a theoretical pressure difference of each functional area based on the nighttime mode, and adjusting a ventilation rate of each functional area, wherein the theoretical pressure difference of each functional area is set according to a preset pressure control gradient; calculating a theoretical air supply rate and a theoretical exhaust rate of each functional area based on the theoretical pressure difference and a functional area use condition; and adjusting a stroke time of each air supply damper based on the theoretical air supply rate and the theoretical exhaust rate. The application can adjust the working power of the system according to the day-night change and the activity level of animals, greatly saves energy while ensuring the ventilation quality, and has the advantages of green environmental protection.

The present application belongs to the technical field of energy station regulation and control, and specifically discloses an energy station control system, method, device and medium. A hierarchical control module is used to obtain environment data and user instructions of each energy station, and generate an intelligent control scheme according to the environment data and user instructions; a communication module is used to obtain energy station data and the intelligent control scheme, and optimize the intelligent control scheme according to the energy station data, and then issue the optimized intelligent control scheme to each energy station; and a voltage stabilization module is used to obtain a voltage stability index and the intelligent control scheme, thereby controlling the voltage of each bidirectional converter. The hierarchical control module is used to optimize user instructions to generate an intelligent control scheme, and the communication module is used to optimize the intelligent control scheme again, so as to adapt to a multi-energy flow coupling environment, efficiently process complex data from different sources, and effectively improve the operation efficiency of the energy system. The voltage fluctuation caused by the hierarchical control module is effectively solved by setting the voltage stabilization module.

This application discloses a clutch disengagement control method and related apparatus. Based on the vehicle's operating conditions, a target disengagement speed threshold is obtained for the clutch to enter the disengagement control phase. This target disengagement speed threshold is determined based on the torque of a target object, which is a higher-priority object among multiple objects under operating conditions. These multiple objects include the engine and the clutch. If the speed of the target object is lower than the target disengagement speed threshold, the clutch is controlled to enter the disengagement control phase, which includes multiple disengagement sub-phases. During the disengagement control phase, based on the actual operating conditions of the engine and clutch, the clutch is controlled to enter the corresponding disengagement sub-phase, and coordinated control of the engine and clutch is performed during these sub-phases. This application achieves coordinated control of the clutch and engine, avoiding drivability issues, preventing stalling risks, and improving safety.