2569 results about "Target control" patented technology

The invention discloses an electromechanical equipment distributed control system based on the Internet of Things, which belongs to the technical field of distributed control, and specifically comprises the following steps: splitting a control task into task units, registration dependencies, data entries and task levels at an edge gateway, and generating a candidate scheduling range according to registration items; a calibration heartbeat with a reference segment is issued, and a driving node executes and returns a measurement record in an idle window for calibrating hardware fingerprints and link overhead and dynamically updating matching parameters; when computing power saturation is triggered, splitting a low-level task unit into suspensible fragments, setting a de-duplication execution identifier, opening a state interface, and completing migration check; selecting a target control node and a transmission path according to a calibration result, issuing fragment and state interface information, driving a target node to continue fragments according to an execution template, and guiding a source node to release occupied resources in sequence; and checking and comparing the execution result, and when the rule is triggered, recovering to the previous stable state according to the mapping rollback table.

The invention relates to a vehicle control method and device, computer equipment and a storage medium. The method comprises the steps of obtaining target crosswind information of crosswind acting on a vehicle according to driving information of the vehicle, weather information of a scene where the vehicle is located and scene image information; determining a target yaw velocity of the vehicle according to the vehicle state information of the vehicle; determining a first angular velocity difference value between the target yaw velocity and an actual yaw velocity obtained through a sensor of the vehicle, and determining driving condition information of the vehicle according to the first angular velocity difference value; and target control information of the vehicle is obtained by using the first angular velocity difference value and / or the target crosswind information according to the driving working condition information of the vehicle. By adopting the method, the driving stability of the vehicle in the crosswind environment can be improved.

The invention relates to the technical field of software testing, and discloses an automatic test script generation method and system, a storage medium and electronic device.The method comprises the steps that test case information and tested environment information are received, and structured case representation is generated; enhancing the structured use case representation based on a preset knowledge base; generating a plurality of positioning candidates for the target control in the testing step, and establishing a priority relationship among the positioning candidates; generating an executable automatic test script; running the script, and when execution failure is detected, automatically adjusting a positioning strategy, a waiting strategy or a business process based on a failure type, and executing again; and feeding back the successfully executed script information to the knowledge base, and updating the content and priority of the knowledge base. Through organic combination of knowledge base enhancement, multi-candidate positioning and a self-healing mechanism, the technical problems that an existing automatic test script is high in maintenance cost, poor in stability and lack of domain knowledge are solved.

The invention discloses a server heat dissipation module control optimization method and system based on analogue simulation, and relates to the technical field of multi-physics field coupling modeling, and the method comprises the steps: constructing a multi-physics field simulation twin space, carrying out the heat flow simulation to obtain a heat dissipation simulation data set, collecting the real-time operation parameters of a server, mapping the real-time operation parameters to the space, and carrying out the heat dissipation simulation data set; the heat dissipation simulation data set is combined to deduce and obtain the heat dissipation temperature change trend, heat dissipation requirements are analyzed and determined according to the trend, a feedback data set is obtained through multi-target control and parameter adjustment, the space is corrected through the feedback data set, and a strategy is made to optimize heat dissipation module control. The technical problems that existing server heat dissipation control lacks twinborn simulation, accurate mapping and dynamic data processing support of the server heat flow state are difficult, complex changes of heat flow cannot be adapted, and consequently the heat dissipation regulation and control precision is insufficient are solved, accurate pre-judgment and dynamic regulation and control of the heat dissipation trend of the server are achieved, and the service life of the server is prolonged. And the control accuracy and adaptability of the heat dissipation module of the server are improved.

A method for automated control code generation and verification includes: receiving a natural language command, the natural language command being configured to instruct the large language model to output a code text that meets control requirements corresponding to the natural language command; performing matching retrieval on a vector database according to the natural language command to obtain a sample code snippet; obtaining API structured information corresponding to the sample code snippet from a knowledge graph database; generating an initial control code according to the sample code snippet and the API structured information; and performing a multi-level virtual operation verification on the initial control code in a software motion control system, and generating a target control code according to multi-level verification results confirmed multiple times by the user and the initial control code.

The embodiment of the invention provides an air conditioner control method and device and a storage medium, the method is used for conducting cooperative control on multiple air conditioner systems deployed in different buildings of a target park, and the method comprises the steps that people flow trend prediction data of the target park in the future time period is obtained, the people flow trend prediction data represents migration and / or distribution conditions of people among different buildings; based on the people flow trend prediction data, target loads of the multiple air conditioning systems are determined; based on the respective target loads of the multiple air conditioning systems, the multiple air conditioning systems serve as a whole, combined planning is conducted on the operation parameters of the multiple air conditioning systems, and a target control strategy used for conducting cooperative control on the multiple air conditioning systems is obtained; and on the basis of the target control strategy, control operation is executed on the multiple air conditioning systems.

The invention provides an unmanned aerial vehicle cluster dynamic hunting method for a complex three-dimensional scene. The method comprises the steps that the state of an escaper unmanned aerial vehicle, the state of each hunting unmanned aerial vehicle and the environment state are obtained respectively; sub-targets are generated around the escaper unmanned aerial vehicle through a Fibonacci ball algorithm, and the sub-targets are dynamically adjusted; based on the dynamically adjusted sub-targets and the state of each trapper unmanned aerial vehicle, optimal sub-target distribution is carried out on each trapper unmanned aerial vehicle through an improved market auction algorithm, wherein the improved market auction algorithm considers path cost and angle cost in a cost function; constructing a dynamic target control obstacle constraint based on the environment state, the state of the escaper unmanned aerial vehicle and the state of each trapper unmanned aerial vehicle; an escaper position change factor and a self-adaptive attenuation rate are introduced into the dynamic target control obstacle constraint; and constructing a distributed MPC optimization problem based on optimal sub-target distribution and a dynamic target control barrier function to perform trajectory optimization and motion control. According to the invention, the efficiency and the safety are ensured at the same time.

The invention discloses a dynamic anti-swing control method of a grab ship unloader, a storage medium and computer equipment, and the method comprises the following steps: acquiring real-time operation state information of the grab ship unloader during operation through a multi-source sensor mounted on the grab ship unloader; a target feedback gain matrix corresponding to the grab ship unloader is determined through a gain scheduling table according to the real-time steel wire rope length and the real-time load in the real-time operation state information, and the gain scheduling table comprises an optimal feedback gain matrix corresponding to the combination of various steel wire rope degrees and loads; determining a target control law based on the target feedback gain matrix, and determining a target control signal of the grab ship unloader according to the target control law and the real-time operation state information; and driving the grab ship unloader to move according to the target control signal. Dynamic anti-swing can be achieved, and the operation precision and efficiency are improved.

The invention relates to the technical field of laser control, in particular to an intelligent control method and system of an MOPA laser. The method comprises the following steps: constructing a target training data set and a one-dimensional convolutional neural network model; training a one-dimensional convolutional neural network model based on the target training data set in combination with a target loss function and a back propagation algorithm to obtain a target model; acquiring current operation parameters of the MOPA laser; inputting the current operation parameters into a target model, and outputting target regulation and control parameters by the target model; the target regulation and control parameters comprise the working current of a pumping module in the MOPA laser and the working temperature of a doped fiber; based on the target regulation and control parameters, the working current of a pumping module in the MOPA laser and the working temperature of a doped optical fiber are adjusted, the working temperature of the doped optical fiber comprises a plurality of different target temperatures, and each target temperature corresponds to a different position on the doped optical fiber. In this way, the problems caused by the nonlinear effect generated under high-power pumping can be reduced.

The invention provides an addressing method for a strategy control network element, an application side network element and a control plane network element, and the method comprises the steps: obtaining a device address of a strategy binding network element retrieval database network element based on the local static data configuration information of the application side network element; retrieving a device address of a database network element according to the policy binding network element, and sending the control plane network element query message to a corresponding target policy binding network element retrieval database network element, so as to query an address of a target control plane network element in the target policy binding network element retrieval database network element according to the control plane network element query information; according to the address of the target control plane network element, sending the policy control network element address query request to the target control plane network element; and receiving a query result corresponding to the policy control network element address query request sent by the target control plane network element. According to the invention, the problem that the application side network element cannot acquire the IP address of the policy control network element according to the user IP address information is avoided.

The invention provides a dosing control method, system and equipment for a sewage treatment process and a medium, and the method comprises the following steps: obtaining multi-source heterogeneous data, and processing the multi-source heterogeneous data to construct a high-dimensional state vector; inputting the high-dimensional state vector into a drug demand dynamic prediction model to obtain a predicted concentration sequence; obtaining a target control instruction according to the current high-dimensional state vector and the predicted concentration sequence; the target control instruction is issued to a controller of the target dosing pump, and dosing control is carried out through the controller; the method solves the industrial problems of response lag, excessive or insufficient addition, incapability of coping with sudden change of water quality, high operation cost and the like existing in the traditional artificial experience control or simple PID (Proportion Integration Differentiation) control. According to the method, under the rigid constraint of absolutely ensuring that the effluent quality is stable and reaches the standard, the medicament consumption can be reduced to the greatest extent, the operation cost is reduced, the secondary pollution is avoided, and the automation and intelligence level of the operation of the whole sewage treatment system is improved.

The invention relates to the field of robot control, and discloses an autonomous transfer robot control method, device, equipment and medium in an anti-explosion environment, and the method comprises the steps: collecting the multi-modal environment data of a target anti-explosion environment, carrying out the data correction of the multi-modal environment data, obtaining the multi-modal correction data, and storing the multi-modal correction data in a database; layered redundancy fusion positioning is carried out on the autonomous transfer robot by using the multi-modal correction data to obtain a real-time pose of the autonomous transfer robot, multi-source obstacle detection is carried out on a target anti-explosion environment by using the multi-modal correction data, a dynamic obstacle map is generated, and the real-time pose of the autonomous transfer robot is obtained. And constructing a structured semantic map of the target explosion-proof environment according to the multi-modal correction data and the dynamic obstacle map, and performing path planning and motion control on the autonomous transfer robot according to the real-time pose and the structured semantic map to obtain a target control result. According to the invention, the positioning and navigation stability of the autonomous transfer robot in explosion-proof dangerous environments such as smoke, dust, weak light and strong reflection is improved.

The application discloses a multimodal interaction method, device, controller, system, automobile and storage medium. The method comprises the following steps: determining a current interaction dialogue according to a current interaction voice at an interaction time; determining a current scene image and current scene data corresponding to a current interaction interface corresponding to the interaction time; adopting a multimodal recognition model to perform multimodal recognition on the current interaction dialogue, the current scene image and the current scene data, and determining a target control instruction; and executing the target control instruction to complete a human-computer interaction operation. The method can guarantee the output efficiency and accuracy of the target control instruction, reduce the complexity of customizing templates, rules and associations and other complex control logics in the development process, and improve the adaptability and generalization ability of voice interaction.

The invention relates to the technical field of electronics, and discloses a boost circuit control method and device, computer equipment and a storage medium, and the method comprises the steps: detecting a state change event in a boost circuit; calculating a voltage difference value between the front-end voltage value and the rear-end voltage value in the booster circuit, and determining a corresponding target control strategy based on the state change event and the voltage difference value, the target control strategy at least comprises a step of determining a corresponding target voltage value and a feed-forward current value based on vehicle driving parameters and working condition parameters of a load motor so as to execute voltage regulation, or a step of determining a corresponding feed-forward duty ratio based on a rear end voltage value of a booster circuit so as to execute voltage regulation; and executing corresponding control operation on the booster circuit according to the target control strategy. The problems that in the prior art, due to the fact that a control strategy of a booster circuit is fixed, and a state change event and voltage difference value dynamic adjustment are not combined, voltage adjustment response lags behind, and stability is insufficient are solved.

The invention discloses a control method and equipment of a glue spraying system and a storage medium, and relates to the technical field of automatic spraying, the method comprises the following steps: obtaining a distance parameter from a nozzle to the surface of a workpiece at the cut-off position of the nth time step and spraying area image data of the nth time step, and generating a workpiece curvature feature and a spraying state feature; the spraying state characteristics, the workpiece curvature characteristics and the material type of the area corresponding to the (n + 1) th time step are substituted into a compensation algorithm, and difference parameter values are generated; and generating and executing a target control parameter of the (n + 1) th time step according to the difference parameter value and the initial control parameter. According to the method, the change of the surface of the workpiece is monitored in real time, the spraying parameters are automatically adjusted according to the change, the technical problem that the thickness of a coating is not uniform is solved, and the spraying quality and efficiency are improved.

The invention discloses a fire point detection device applied to a satellite, and belongs to the technical field of space remote sensing. The method comprises the steps that first detection equipment and second detection equipment are installed on a satellite; the first detection device is in communication connection with a control computer of a satellite, and the second detection device is in communication connection with a data management computer of the satellite; the first detection equipment has a first field angle and a first resolution ratio and is used for determining the position of a fire point and sending the position of the fire point to the control computer, so that the control computer determines a maneuvering target based on the position of the fire point and sends the maneuvering target to the data management computer; the data management computer is used for controlling the working state of the second detection equipment based on the maneuvering target; the second detection equipment has a second field angle and a second resolution ratio and is used for imaging the fire point under the control of the data management computer; wherein the first field angle is larger than the second field angle, and the first resolution ratio is lower than the second resolution ratio. According to the invention, through a cooperation mechanism of the first detection device and the second detection device, rapid discovery and accurate detailed investigation of global fire points by a satellite are realized, and the observation efficiency and the resource utilization rate are significantly improved.

The invention discloses an intelligent control method and system for a constant-temperature incubator based on deep learning. The method comprises the following steps: acquiring an equipment state vector in real time; analyzing the equipment state vector by using an improved model, and predicting an environmental parameter demand trend in a culture process to obtain a prediction result; modeling a control strategy into an MDP Markov decision process through a DRL deep reinforcement learning framework according to the prediction result, and dynamically optimizing power distribution of a heater, a refrigerator, a humidifier and a fan by taking minimization of energy consumption and temperature fluctuation as objective functions to obtain an initial control strategy; and adjusting the power of the actuator according to the initial control strategy by using a fuzzy PID algorithm, monitoring sensor data in real time through an isolated forest model, and adjusting the initial control strategy when abnormality is detected to obtain a target control strategy. The environment demand change is pre-judged in advance, and the hysteresis problem of traditional control is solved.

The invention relates to the technical field of gas path control, and particularly discloses a gas path control method and system, an intelligent terminal and a storage medium, a PID control algorithm is used for calculating a pressure control quantity according to a current error so as to gradually enable the system to reach a stable state close to a target control value, and dynamic gain compensation and machine learning feed-forward compensation are introduced so as to achieve a stable state close to the target control value. Nonlinear compensation is carried out on disturbance caused by environment temperature changes, and rapid response is carried out based on the speed of temperature changes so as to make up for the lag problem in the dynamic change process.

The invention discloses a car following control method and a related product. According to the scheme, multi-source data are acquired, and the multi-source data are fused to obtain a fusion result; based on the fusion result, performing multi-modal trajectory prediction on the driving behavior of the preceding vehicle to obtain a prediction result of the driving behavior of the preceding vehicle; the multi-modal trajectory prediction comprises longitudinal motion prediction and transverse motion prediction; quantifying a car following risk by using a multi-dimensional risk index to obtain a risk level; constructing a multi-target cost function based on the fusion result, the front vehicle driving behavior prediction result and a control vector, and solving the multi-target cost function by using a preset constraint condition to obtain an initial control parameter of the vehicle; and on the basis of the risk level, initial control parameters of the vehicle are adjusted, and target control parameters of the vehicle are obtained. Compared with the problem of response lag in adaptive cruise control in the prior art, the adaptive cruise control method has obvious advantages.

The invention discloses a distributed energy storage control method and system for a smart power grid. The method comprises the following steps: S1, collecting and preprocessing operation parameters; s2, local features are extracted and compressed, and a power grid feature set is constructed; s3, performing frequency domain separation on the power grid feature set, and performing decoupling reconstruction; s4, constructing a dual-channel control vector, and forming a mixed instruction matrix; s5, inputting the mixed instruction matrix into a sliding window adversarial mapping unit, constructing a state transition tensor through historical control records, and executing dynamic mapping suppression; s6, determining a target control behavior of the current time slice, outputting and synchronously executing charging and discharging instructions, and recording feedback data; and S7, network parameters and mask weights are updated according to feedback data, and a continuous control closed loop is formed. Accurate decoupling and cooperative control of high-frequency disturbance and low-frequency trend of the power grid can be realized, and response speed, control precision and energy utilization efficiency of energy storage scheduling are remarkably improved.

The invention relates to the technical field of signal processing, in particular to a high-speed unmanned aerial vehicle structure servo elastic coupling vibration suppression control method, system and device, a medium and a program product. Obtaining a target control loop causing resonance; spectral analysis is carried out, and double-center frequencies causing resonance are obtained; a cascade wave trap with double center frequencies is designed; and the servo elastic coupling vibration of the unmanned aerial vehicle structure is suppressed. According to the method, the problems of difficulty in structure modification, narrow notch frequency range and large low-pass filtering delay of an existing structure servo elastic coupling resonance solving method are solved, the performance of a control system cannot be reduced, and the flight safety is ensured.

The invention provides a collision avoidance learning control method applied to an unmanned system cluster, which can be applied to the technical field of artificial intelligence. The collision avoidance learning control method comprises the following steps: determining respective state vectors of a plurality of unmanned systems according to respective real-time positions of the plurality of unmanned systems in an unmanned system cluster; inputting the communication weight among the plurality of unmanned systems, the state vector of each unmanned system and the expected formation vector of each following unmanned system relative to the piloting unmanned system into an error dynamic model to obtain respective formation errors of the plurality of unmanned systems; for each unmanned system, inputting the formation error into an evaluation neural network to obtain a prediction control parameter; determining a comprehensive obstacle function value based on the respective real-time positions of the plurality of unmanned systems and the real-time position of the obstacle; and correcting the prediction control parameter based on the comprehensive obstacle function value to obtain a target control parameter so as to control the unmanned system cluster to perform formation motion by using the target control parameter.

A coordinated optimization method for VSC-HVDC Frequency Synchronization Control and primary frequency regulation of hydropower includes: obtaining optimal PI parameters of the VSC-HVDC Frequency Synchronization controller from a first layer output of a dual-layer optimization model for coordinated parameters of VSC-HVDC Frequency Synchronization and primary frequency regulation; and obtaining a target PID control parameters from a second layer output of the dual-layer optimization model. The coordinated optimization method further includes adjusting the optimal PI parameters of the synchronization controller based on the target selection range and updating the PID control parameters of the primary frequency regulation system of hydropower based on the target PID control parameters. This approach aims to address the challenge of balancing the frequency response speed between the VSC-HVDC synchronization system and the primary frequency regulation system of hydropower.

The invention discloses a brain-controlled rehabilitation equipment-oriented control strategy generation method, device and equipment and a storage medium, and relates to the technical field of signal processing, and the method comprises the following steps: acquiring a multi-channel electroencephalogram signal, and preprocessing the multi-channel electroencephalogram signal to obtain a target electroencephalogram signal comprising a steady-state visual evoked potential signal and a motor imagery signal, the target electroencephalogram signal corresponds to a preset action category; decoding the steady-state visual evoked potential signal by adopting filter group task related component analysis to obtain a correlation score vector; decoding the motor imagery signal by adopting a Mangban dynamic routing space-time network model to obtain a classification score vector; performing posterior probability distribution conversion and weighted fusion on the correlation score vector and the classification score vector to obtain fusion probability distribution; and generating a target control strategy according to the action category corresponding to the highest probability value in the fusion probability distribution. The control strategy obtained by the invention can consider both intention recognition precision and rehabilitation nerve activation effect.

The invention relates to the field of edge computing, in particular to a primary and secondary fusion complete ring main unit energy efficiency optimization system based on cloud edge collaboration. The system comprises an edge device deployment and data acquisition module used for collecting operation electric parameters and device states and generating a service calling request; the service calling module is used for screening target control parameters under security constraints based on the energy efficiency optimization service package; the data synchronization module unloads the data to a cloud platform through a message queue protocol; the cloud service arrangement module aggregates the data updating service package and issues the data updating service package to the edge; and the real-time control module converts the parameters into instructions to drive equipment to act. A cloud training and edge reasoning collaborative architecture is adopted, the problems that local control lacks adaptivity, edge resources are limited and full-cloud control communication time delay exists are solved, and real-time energy efficiency optimization is achieved.

The present application relates to the technical field of network management and relates to an all-optical networking device control method, system and apparatus, and a communication device, a storage medium and a computer program product. The method comprises: in response to determining, on the basis of a first release message of a target device and a second release message of a master device, that the target device satisfies a preset legitimacy condition, determining location information of the target device in the network hierarchy of all-optical networking, wherein the first release message is acquired on the basis of a sub-level interface in a communication bus, and the second release message is acquired on the basis of a master-level interface in the communication bus; and on the basis of the communication bus and the location information of the target device in the network hierarchy of all-optical networking, sending a target control policy to the target device.

The invention provides a vehicle drifting control method, device and equipment, a computer readable storage medium and a computer program product. The method comprises the steps that based on target state information and actual state information of a vehicle, a first slip rate component and a second slip rate component are obtained, the first slip rate component is used for slip angle stability control, and the second slip rate component is used for yaw velocity control; determining a left rear wheel slip rate target and a right rear wheel slip rate target based on a basic slip rate target, the first slip rate component and the second slip rate component; and rotating speed calculation is conducted based on the actual state information, the left rear wheel slip rate target and the right rear wheel slip rate target, and the vehicle is controlled based on the obtained left rear wheel rotating speed target and the obtained right rear wheel rotating speed target. According to the invention, a driver can maintain stable drifting of the vehicle only by operating the steering wheel and the accelerator.

The invention discloses a feature point identification method of a river hydrodynamic condition. The method comprises the following steps: S1, hydrological data collection; s2, dividing flow levels and simulating a flow field of each flow level; s3, arranging alternative control sections; s4, determining a target control section; and S5, constructing a correlation function to determine a target feature point. According to the method, historical hydrological and geographic data of a to-be-monitored river reach are utilized, hydraulic engineering simulation software is combined, a target control section is selected and determined by calculating section similarity indexes, relevancy values of all nodes in the target control section are calculated and selected through a constructed relevancy function, and the flow velocity of the nodes is combined; determining alternative feature points, and finally rejecting points influencing navigation, namely target feature points; the identified feature points are optimal monitoring points for arranging the river flow velocity monitoring device, a scientific basis is provided for reasonably arranging flow velocity monitoring points, only the water flow velocity of a limited number of feature points can be monitored, and the hydrodynamic change condition of the whole river can be mastered.

The embodiment of the invention provides a method for displaying an application interface, electronic equipment and a related medium, the method is applied to the electronic equipment, the electronic equipment comprises an outer screen, a camera is arranged on the outer screen, the method comprises the steps that the outer screen displays a first interface, and the first interface comprises a target control of a target application; receiving an operation instruction acting on the target control; determining display parameters of a layer set corresponding to the operation instruction based on configuration information of the target application; in response to the operation instruction, a second interface is displayed on the outer screen based on the display parameters, the second interface comprises a first display area and a second display area, the application layer is displayed in the second display area, and the decoration layer and the background layer are displayed in the first display area. By implementing the method, the decorative layer can be selectively presented to the user in combination with configuration information of different operation scenes and different applications, and various application interfaces presented to the user are more uniform and attractive while the adaptation degree of the decorative layer and the different applications is improved.

The embodiment of the invention provides an evaporation system control method and an evaporation system, and relates to the technical field of control, the method is applied to a control system in an MVR evaporation system.The method comprises the steps that in response to a starting instruction, a feeding system is controlled to pump to-be-treated liquid into an evaporation crystallization system, and the real-time boiling point rise of the evaporation crystallization system is monitored; and determining to adopt an optimal recovery rate control mode or a boiling point rise control mode as a target control mode based on the real-time boiling point rise, and controlling the feeding system, the evaporative crystallization system and the water production system to treat the to-be-treated liquid according to a preset strategy corresponding to the target control mode, the frequency of the distilled water and the flow of the to-be-treated liquid pumped by the feeding system meet the corresponding recovery rate, so that the control intelligence and reliability of the MVR evaporation system are improved.