2362 results about "Distribution control" patented technology

The invention relates to a control method and device for wind load resistance of a mooring unmanned aerial vehicle and a storage medium. The method comprises the following steps: collecting and modeling a mooring unmanned aerial vehicle to obtain a system dynamics model; state estimation is carried out to obtain system wind load disturbance data and expected attitude data; performing optimal control solution on the plurality of mooring points to obtain tension distribution control data of each mooring point; inputting into a discrete time neural network controller for attitude compensation calculation to obtain thrust vector compensation control data; performing adaptive robust control on the attitude of the mooring unmanned aerial vehicle to obtain a rotating speed control instruction of each motor of the four rotors; and performing safety threshold judgment, and when any monitoring data exceeds a preset threshold, outputting a working mode switching instruction and executing safe landing control. According to the invention, a multi-stage safety protection mechanism is established, and reliable operation of the mooring unmanned aerial vehicle under extreme conditions is ensured through real-time monitoring and mode switching.

The invention relates to the technical field of unmanned aerial vehicle-unmanned ship data fusion, and discloses an unmanned aerial vehicle-unmanned ship multi-source heterogeneous big data fusion system and method, and the system comprises a task scheduling module which is used for executing the path planning and task distribution of operation tasks; the control and data acquisition module is used for controlling the unmanned aerial vehicle and the unmanned ship to execute a synchronous measurement task; the space-time reference unification module is used for performing dynamic synchronization and consistency alignment processing; the multi-source data fusion module is used for carrying out fusion processing on the aligned heterogeneous sensing information data; the self-adaptive robust enhancement module is used for monitoring the noise level and the change condition of the signal-to-noise ratio of the sensor in the fusion process; and the intelligent analysis and visualization module is used for executing environment modeling, target identification and geographic information expression processing. According to the method, the fusion weight self-adjusting mechanism driven by the maximum entropy is introduced, so that the internal structure can be intelligently adjusted when the data quality fluctuates. According to the technical effect, the target that the weight is dynamically adjusted along with signal noise is achieved.

The invention discloses an intelligent household electrical appliance interaction control method and system, and the method comprises the following steps: collecting the operation state parameters, environment perception data and user behavior characteristics of each household electrical appliance in a living space in real time, and generating an environment perception data packet through a multi-modal data fusion model; constructing a user habit preference model library, generating a household appliance control strategy decision tree in combination with historical interaction records, and matching an optimal control strategy set according to a real-time scene type; and when a user active intervention signal or an environment sudden change event is detected, a dynamic strategy reconstruction mechanism is triggered, an instruction updating request carrying a priority identifier is broadcasted to the associated household appliance group, and a redistribution control instruction set is generated. The method has the following advantages and effects: multi-source environment data can be deeply fused, the user habit model is constructed in real time, and the method has a dynamic strategy reconstruction capability so as to solve the problems of response lag, strategy stiffness and energy efficiency imbalance in a complex home environment in the prior art.

The invention discloses a multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method, and relates to the technical field of liquid cooling energy efficiency optimization. The multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method comprises the following steps: S1, collecting and preprocessing two-phase liquid cooling control data; s2, the thermal load level of each area is evaluated periodically, a discrete time linear state space model is constructed, and the thermal load change rate is extracted; s3, the cold distribution amount of each area is quantified periodically, the pump speed and the valve opening target value are calculated, and an adjustment control instruction is generated; and S4, high heat risk and low heat stability areas are recognized, the cooling capacity compensation requirement is evaluated, a cooling capacity enhancement and recovery distribution value is output, and a corresponding control instruction is generated. The problems that an existing two-phase liquid cooling system generally only depends on temperature feedback for adjustment, so that cooling capacity distribution response lags behind, a short-time overheating phenomenon is prone to occurring in a high-heat area, and cooling capacity waste exists in a low-heat area at the same time are solved.

The invention provides a lithium battery equalization thermal management method. Real-time temperature data is obtained by constructing a thermal distribution monitoring network, the temperature difference between a center and an edge area is analyzed, a thermal load distribution coefficient is calculated, and a dynamic heat dissipation intensity adjustment model is established; driving the multi-channel cooling system to operate according to the heat dissipation demand priority, and adjusting the flow distribution proportion of a cooling medium; a dynamic nonlinear feedback correction mechanism is adopted, secondary adjustment is carried out for uneven temperature distribution, and an optimal heat dissipation parameter combination is determined in combination with historical data. Uniformity control over temperature distribution of the battery module is achieved, the problem of heat accumulation in a center area is effectively solved, the heat dissipation efficiency under the rapid charging working condition is improved, and the safety performance and the service life of the battery module are guaranteed.

The invention relates to the technical field of storage batteries, in particular to a storage battery monitoring, detection, treatment and evaluation integrated system and a storage battery management method, and the system comprises a plurality of accompanying modules, a collection power distribution control module, a storage battery management capacity checking host and a remote platform; the internal resistance analysis test of the system is based on multi-frequency-point alternating current excitation (0.5 Hz-7. 5kHz), a complex impedance spectrum of not less than 20 frequency points can be constructed, and the internal polarization characteristics of the battery are analyzed; the system adopts a feed network type discharge capacity checking, so that discharge electric energy is fed back to a power grid, and the capacity detection precision is improved to 98%; according to the system, EIS data and an LSTM neural network are fused, and a battery state of health (SOH) prediction model is established; the system is based on a DSP digital power supply technology, and can realize 50A active equalization topology.

The invention discloses a protection device for power distribution control equipment, and relates to the technical field of protection devices, the protection device comprises a base, the top of the base is provided with a buffer damping assembly, the top of the buffer damping assembly is provided with a power distribution cabinet shell, and a filter screen cleaning assembly is arranged below the left side wall of the power distribution cabinet shell. The inner wall of the rear side of the power distribution cabinet shell is fixedly connected with a plurality of equidistantly arranged power distribution equipment clamping assemblies. According to the power distribution cabinet, vibration can be effectively absorbed and buffered through the arranged buffering and damping assembly, the vibration is prevented from being directly transmitted to precise power distribution control equipment in the power distribution cabinet, meanwhile, noise can be reduced, the arranged filter screen cleaning assembly can clean a filter screen at regular intervals, a good heat dissipation effect is maintained, and the arranged power distribution equipment clamping assembly is capable of clamping the power distribution equipment. The device can firmly clamp the power distribution equipment, wiring looseness caused by shaking is avoided, meanwhile, an operator can easily take out the power distribution equipment from a power distribution cabinet, and the equipment maintenance time is greatly shortened.

The invention discloses a vehicle power supply distribution control management system and method, and relates to the technical field of vehicle power supplies, and the method comprises the steps: collecting the historical driving data of a vehicle and the driving behavior data of a driver, analyzing the driving habit of the driver, and monitoring the driving state of the vehicle in real time through combining with a vehicle-mounted sensor; comprehensively judging whether the vehicle enters a high-load state or not; when the vehicle enters a high-load state, the charging and discharging power of each battery module is dynamically adjusted according to the temperature distribution and load requirements of each battery module in the battery pack; evaluating the power supply condition of each battery module according to a power adjustment result, sending an early warning prompt to a driver if the power supply is insufficient, and continuously monitoring and analyzing the temperature difference between the battery modules in the battery pack and predicting the temperature change of each battery module if the power supply is sufficient, and the cooling strategy of the vehicle system is intelligently adjusted, and temperature balance of all battery modules of the vehicle in the high-load state is achieved.

The invention discloses an intelligent wireless charging power distribution method and system, and aims to improve the efficiency and safety of simultaneous charging of multiple devices, and the system design comprises a plurality of key modules: a device detection and recognition module automatically recognizes the charging devices and collects the power demands of the charging devices; the power demand analysis module calculates the power demand of each device according to the device electric quantity and the charging mode, and the power distribution control module dynamically adjusts the power output according to the priority, the distance and other factors; the real-time monitoring and feedback module ensures the stability and safety of the charging process, and the data recording and learning optimization module optimizes the charging strategy by analyzing historical data. Through cooperative work of the modules, the system can adjust the charging power in real time, optimize the charging efficiency, improve the user experience, and ensure the safety of the charging process. The system shows good adaptability in a multi-device environment, and important reference and application prospects are provided for development of a wireless charging technology.

The invention relates to a communication equipment optimization method and device based on power management. The method comprises the following steps: performing delay power consumption domain transformation and minimum mean square error power equalization processing on power consumption data of communication equipment to obtain power consumption characteristic data; inputting a heterogeneous equipment management neural network to carry out power management prediction to obtain an equipment power consumption prediction parameter; deploying a virtual power supply manager and executing power supply response control on the communication base station and the standby power supply to obtain power supply adjustment parameters; constructing an equipment power consumption scheduling matrix, and performing equalization optimization on the equipment power consumption scheduling matrix by adopting a block iteration mode to obtain a multi-equipment power consumption scheduling scheme; and executing power distribution control according to the multi-device power consumption scheduling scheme, generating an initial power distribution strategy, and dynamically adjusting the initial power distribution strategy through a three-layer Bayesian network model to obtain a target power distribution strategy. According to the invention, the accuracy and adaptive capability of power distribution are improved.

The invention relates to the technical field of power system frequency, and discloses a thermal power generating unit-energy storage coupling frequency modulation system for improving power grid frequency stability, which comprises a thermal power generating unit module, an energy storage system module, an energy management and distribution control module and a communication and monitoring module. The thermal power generating unit provides a frequency stabilization basis through inertia response and power regulation, and the energy storage system compensates frequency deviation in a quick response mode. And the energy management module dynamically adjusts the power distribution proportion between the thermal power generating unit and the energy storage system based on the optimized objective function to realize efficient collaborative frequency modulation. The output power and the state of charge of the energy storage system are controlled by constraint conditions. The communication and monitoring module collects power grid frequency, load fluctuation and energy storage state data in real time, generates frequency modulation control signals and issues the frequency modulation control signals to each module. By combining the stability of the thermal power generating unit and the quick response characteristic of the energy storage system, the response speed and the adjustment precision of power grid frequency adjustment are remarkably improved, and meanwhile the frequency adjustment cost is reduced.

The invention provides a water flow dynamic distribution control method driven by air conditioner terminal load prediction, and relates to the technical field of air conditioner engineering.The method comprises the steps that 1, the people flow density, the environment temperature and humidity and the equipment running state of each air conditioner terminal service area are collected in real time, and a load prediction mechanism is constructed based on a spatial-temporal feature fusion algorithm; the minimum cooling capacity demand of each tail end in the future time period is predicted; 2, based on the minimum cooling capacity requirement, areas with similar load characteristics are classified into the same cluster through hot area clustering, and building scale dynamic cooling load distribution is generated with cluster mass center data as the benchmark; and step 3, calculating an energy flexibility penalty coefficient based on the dynamic cooling load distribution in combination with the real-time deviation between the indoor temperature and the comfortable temperature difference, and generating a regional water flow regulation weight. According to the method, dynamic distribution of the water flow is driven through load prediction, the water pump frequency and the refrigerating unit strategy are dynamically adjusted in combination with real-time energy consumption feedback, and self-adaptive adjustment of the branch water flow is achieved.

The invention discloses a vehicle stability adaptive control method under low attachment road surface multi-source interference, and belongs to the field of vehicle control, and the method comprises the following steps: S1, multi-source interference perception and attachment coefficient prediction; s2, dynamic correction of tire dynamic parameters: correcting tire cornering stiffness and slippage stiffness on line; s3, multi-source interference collaborative observation and estimation: dynamically estimating an interference source by using an enhanced extended state observer; s4, phase plane stability envelope analysis and weight adjustment: dynamically allocating control priorities; and S5, on the premise of considering an interference source, performing dynamic torque distribution and actuator cooperative control: optimizing four-wheel torque by using a quadratic programming algorithm to obtain a torque distribution result. By adopting the vehicle stability adaptive control method under the low-attached road surface multi-source interference, the problems of insufficient modeling precision, weak interference suppression, target conflict and redundancy deficiency in low-attached road surface vehicle stability control are solved, and the trajectory tracking precision and the yaw stability are remarkably improved.

The invention provides an intelligent control method and system for air purification equipment. According to the method, multi-dimensional environment data, including pollutant three-dimensional space data captured by air purification equipment, real-time airflow velocity and concentration distribution, in an open type pollution environment are obtained, a pollutant distribution thermodynamic diagram is generated, and the multi-dimensional data and the thermodynamic diagram are jointly coded to form a pollution concentration gradient map. Meanwhile, a historical control strategy data set is collected, cross-environment matching is carried out on the historical control strategy data set and the atlas, and diversion control characteristics associated with the pollutant diffusion direction are extracted; on the basis of the mapping relation between the characteristics and the atlas, a dynamic flow guide parameter set is determined, an intelligent control instruction of the air purification equipment is finally generated, and directional airflow disturbance and air distribution optimization control over the high-concentration area are achieved. According to the technical scheme, the intelligent control efficiency and precision of the air purification equipment can be improved.

The invention discloses a parallel processor dynamic resource allocation system and method based on reconfigurable hardware, and relates to the technical field of computer chips, and the system comprises a workload monitoring module which is responsible for monitoring the workload type and the resource demand of a task processed by a parallel processor in real time, and determining the task type and the resource demand by identifying the task type and the resource demand; a monitoring result is fed back to the resource allocation control module; the resource allocation control module is responsible for generating a corresponding resource allocation control signal based on feedback information of the workload monitoring module and dynamically configuring the reconfigurable hardware module; the reconfigurable hardware module is responsible for realizing efficient adaptation to diversified tasks through a plurality of reconfigurable units formed by programmable logic devices according to different working load dynamic reconfiguration functions and connection modes; and the data caching and transmission module is responsible for cross-module data circulation and global data storage. Different task requirements can be accurately adapted, and the resource utilization rate is improved.

The present invention relates to the technical field of solvent purification, and discloses a propylene glycol methyl ether acetate purification control method and a propylene glycol methyl ether acetate purification process, the propylene glycol methyl ether acetate purification control system comprises a rectification device and a rectification control system, the rectification device comprises a rectification tower, a raw material preheater, a condenser, a reflux tank and a reboiler, the rectification control system comprises an environment temperature measuring unit, a tower top temperature measuring unit, a tower bottom temperature measuring unit, a feeding temperature measuring unit and a regulation and control module, the rectification control system is pre-trained with a parameter prediction model, and the parameter prediction model takes the environment temperature, the tower top temperature, the tower bottom temperature and the feeding temperature as input to output regulation and control parameters. The regulation and control parameters comprise the opening degree of a steam valve, the power of a condenser and the opening degree of a return valve, a primary distribution controlled parameter is obtained according to a preset distribution strategy, the primary distribution controlled parameter is specifically the optimized regulation and control parameter, and the tower top temperature is controlled within a preset tower top temperature range according to the primary distribution controlled parameter.

The invention relates to the field of power distribution control, and particularly discloses a self-healing control system and method based on multi-agent collaboration, and the system comprises a regional agent and a local agent which are disposed in a power distribution network. Wherein the local intelligent agent is configured to obtain real-time operation data of a monitoring point in the power distribution network, and perform rapid fault detection on the real-time operation data; the regional intelligent agent is configured to fuse the fault analysis information of the plurality of local intelligent agents to determine fault position information when the power distribution network has a fault, generate a self-healing control strategy according to the fault position information, and send the self-healing control strategy to the local intelligent agents for execution; through cooperative work of the distributed intelligent agents, the problems of low response speed, low positioning precision, weak autonomous capability and the like in traditional power distribution network fault management are solved. In addition, the system does not need to depend on centralized control of a master station, can still operate autonomously when communication is interrupted, and improves the efficiency and reliability of fault processing through cooperation of multiple agents.

The invention discloses a power domain controller system, which relates to the technical field of vehicle design and research and development and comprises a domain control board, a power module and a high-voltage power distribution part, the domain control board comprises a vehicle control unit, a heat management controller, a battery management system, a gear shifting controller and a power distribution control unit, wherein the heat management controller, the battery management system, the gear shifting controller and the power distribution control unit are electrically connected with the vehicle control unit. The heat management controller is electrically connected with the power distribution control unit. The power module comprises a slow charging motor, a DCDC converter and a relay, the slow charging motor is electrically connected with the battery management system, and the DCDC converter is electrically connected with the gear shifting controller; and the high-voltage power distribution part comprises a copper bar, a relay and a fuse. Through multi-module integration, the number of physical controllers and wiring harness complexity are reduced, the system development and maintenance cost is remarkably reduced, and meanwhile platform expansion is facilitated.

The invention relates to the technical field of refrigerating system control, discloses a load distribution control method, system and equipment for a refrigerating host parallel system, and aims to solve the problem of how to find the number of operating refrigerating host nodes corresponding to an optimal energy efficiency value in the parallel system. The method comprises the following steps: acquiring a three-dimensional performance array table corresponding to inlet and outlet temperatures, load rates and energy efficiency values of each refrigeration host; the real-time refrigerating capacity of each refrigerating main machine is obtained, the real-time total refrigerating capacity of the system is determined, and the range of the number of the main machines needing to operate is determined by combining the rated refrigerating capacity and the minimum refrigerating capacity of the main machines; determining the energy efficiency value in the table corresponding to each host under each corresponding number of host combinations in the number range, calculating the total energy efficiency value of each corresponding number of host combinations, and obtaining the number of hosts corresponding to the maximum total energy efficiency value as the optimal number of running hosts; and loading and unloading are carried out based on the current operation number and the optimal operation number. By means of the method, the system meets the refrigeration requirement and meanwhile reaches the optimal energy efficiency value.

The invention relates to the technical field of intelligent illumination, and discloses an intelligent illumination explosion-proof single lamp controller optimization scheduling method and system, and the method comprises the steps: firstly obtaining the deployment position of a controller, determining a target illumination region, collecting ambient light data to construct an illumination distribution diagram, and recognizing a distribution control link; monitoring real-time energy consumption of a link, analyzing load characteristics and calculating an optimal dimming coefficient; acquiring a signal response frequency band based on the dimming coefficient, fitting to generate a dimming response curve, identifying a defect response section and calculating a harmonic distortion rate; illumination compensation is carried out according to the harmonic distortion rate, scheduling grouping is carried out after a compensation threshold value is determined, high-load nodes are identified, and power is corrected; and finally, acquiring the temperature change gradient of the lamp according to the load correction parameter, generating a regulation and control instruction, and formulating an optimal scheduling strategy. According to the invention, the scheduling optimization of the explosion-proof single lamp can be improved.

The invention discloses an intelligent fertilizer distribution control system based on Beidou positioning, and relates to the technical field of agricultural automation, and the system comprises the steps: building a fertilization simulation model, and obtaining the relation data of the disc opening size and the fertilization amount of a fertilizer distributor through an experiment; soil analysis data and remote sensing image data are collected and preprocessed; generating a fertilization prescription map by using a multi-objective optimization model based on the preprocessed soil analysis data and remote sensing image data according to the soil characteristics and crop requirements of the field; high-precision positioning data are obtained through a Beidou positioning system, and the fertilization prescription map and the high-precision positioning data are fused to complete field space calibration; based on the field space calibration result and the high-precision positioning data, adopting a Dijkstra algorithm to generate an optimal fertilizer spreading path; in combination with the real-time speed of the tractor and the fertilization simulation model, the disc opening size of the fertilizer spreader is dynamically regulated and controlled, and the fertilization amount is accurately controlled by using a control algorithm; the tractor corner and the field boundary are monitored in real time, and the fertilizer distributor is automatically closed.

The invention relates to the technical field of batching automatic control, and discloses a material flow and energy flow bidirectional coupling tin smelting automatic batching method and system. Carrying out automatic calculation to carry out material balance, energy balance calculation and material-energy coupling optimization configuration, and determining a decision variable value of production optimization batching, namely a batching scheme; a batching scheme and target parameters are displayed through a window and are transmitted to a DCS (Distributed Control System) through an OPC (Optical Product Control) server, and the feeding amount of a feeder and hardware instrument equipment are controlled by the DCS; the current crude tin grade, the Fe / SiO2 ratio in slag and the melt temperature are analyzed and compared with target values. The system comprises a batching calculation module, a distribution control module and a parameter correction module. Through material and energy flow analysis, precise smelting burdening, process optimization, energy conservation and emission reduction are achieved, and the production efficiency and environmental friendliness are improved.

The invention discloses a micro-grid load distribution control method, device and equipment based on entropy increase disturbance, and the method comprises the steps: analyzing the operation state of a micro-grid through chaos measurement, and constructing an entropy increase disturbance excitation mechanism to actively excite the vitality of a system; after random disturbance is applied, inherent frequency characteristics of each power supply are extracted, and a frequency synchronization coordination mechanism is established to realize multi-source coordination; adopting counter-example search to actively identify distribution scheme vulnerabilities, and generating an enhanced distribution strategy to improve robustness; evaluating the load bearing capacity of each power supply, constructing a load conduction topology and analyzing pressure distribution; each power supply bearing limit parameter is obtained through boundary active detection, and the equipment potential is fully excavated; and a final control instruction is generated based on a multi-layer time sequence synchronization mechanism, and multi-power-supply coordinated output is realized. A chaos theory is introduced into micro-grid control, local optimum is avoided through active disturbance, a multi-layer coordination mechanism is adopted to adapt to new energy volatility, and a self-adaptive load distribution control scheme is provided for a micro-grid with high-proportion renewable energy access.

The invention relates to the field of locomotive power battery electric quantity control, and particularly discloses a locomotive power battery electric quantity hysteresis equalization control method, which comprises the following steps that: a traction force exerting mode is reset into an axle load transfer mode, and the initial value of an electric quantity equalization compensation coefficient K is a rack axle load transfer coefficient corresponding to zero speed; judging whether the current mode is a power battery power supply mode; if yes, the TCU receives the electric quantity of a front power battery and the electric quantity of a rear power battery in real time according to the current locomotive working mode, calculates the electric quantity average value difference value, monitors the auxiliary load power and the traction motor power and calculates the power difference value; entering a hysteresis control logic process; calculating a dynamic traction force compensation coefficient, ensuring that the traction force compensation amount is matched with the actual load characteristic of the system, correcting the traction characteristic curve in real time, and dynamically compensating the electric quantity difference of the battery; and performing traction distribution control according to the locomotive speed and outputting corresponding traction.

The invention relates to the technical field of light guide film light intensity distribution regulation and control methods based on microstructure optimization, discloses a light guide film light intensity distribution regulation and control method and system based on microstructure optimization, and aims at solving the problems that an existing light guide film is fixed in light intensity distribution, insufficient in optimization precision and difficult to customize. The method comprises the following steps: constructing a light guide film model and a target light intensity distribution diagram, initializing microstructure parameters and simulating to obtain simulated light intensity distribution; deviation is calculated and serves as optimization algorithm input, and microstructure parameters are iteratively adjusted through a particle swarm optimization algorithm based on gradient guidance until convergence is met; and converting the optimized microstructure parameters into a manufacturing instruction. Through the scheme, reverse high-precision customization of light intensity distribution of the light guide film can be realized, the design efficiency, the light energy utilization rate and uniformity are remarkably improved, and the research and development period is shortened.

The invention discloses a face recognition and encryption verification multi-grid article distribution control method and a distribution vehicle, and relates to the technical field of recognition and verification safety, and the method comprises the steps: fusing three-dimensional environment information through employing a vehicle-mounted edge calculation terminal and a navigation positioning terminal, and constructing a dynamic safety response strategy; the warehouse is analyzed through the vehicle-mounted warehouse control unified management terminal and the dynamic safety response strategy, and an edge intelligent control mechanism is obtained; processing based on a vehicle control and monitoring terminal and an edge intelligent control mechanism to obtain a real-time state; a vehicle interaction terminal and an intelligent operation terminal are utilized to obtain a face image and a visual dynamic feature, and a multi-modal detection strategy is utilized to analyze the face image and the visual dynamic feature to obtain a final authorized face image and a final authorized visual dynamic feature; and a dual-mode intelligent redundant unlocking technology is constructed, and face recognition and encryption verification are performed on the distribution vehicle based on the dual-mode intelligent redundant unlocking technology. According to the invention, compliance, high-efficiency and safe distribution of high-value materials is realized in an unmanned environment.

The invention relates to the technical field of internet of things and intelligent control, and provides a medicine distribution device based on the internet of things. An existing medicine distribution system mainly depends on manual operation or single automatic equipment, so that the efficiency and precision in the distribution process are low, the medicine identification technology bureau is limited to simple package bar code scanning, and identification and distribution of unpackaged medicines are difficult to process. According to the multi-modal data fusion technology, two-dimensional images, three-dimensional forms and spectral data are combined, medicine is accurately recognized, and automatic grabbing and accurate distribution are achieved through the mechanical arm and the force feedback control device. And the control layer adopts an inverse kinematics algorithm, a path planning algorithm and fuzzy logic control to ensure accurate operation and safe grabbing of the mechanical arm. The system also utilizes a reinforcement learning algorithm to dynamically optimize a drug distribution strategy, and improves the accuracy and flexibility of the distribution process through a real-time feedback mechanism.

Systems, methods, and computer-readable storage media to protect tokens using a protection architecture. One method includes identifying asset tokens including links to a plurality of asset metadata objects. Further, the method includes generating a container metadata object including metadata of the asset tokens. Further, the method includes generating a container token including a link with the container metadata object. Further, the method includes encapsulating the container token and the asset tokens within a container including a container control structure restricting outputs of the container metadata object and the plurality of asset metadata objects. Further, the method includes generating an allocation token compatible with a segmented allocation control structure restricting outputs by the container of a first segmented allocation of the asset tokens based on metadata of a subset of the plurality of asset metadata objects. Further, the method includes providing, using the segmented allocation control structure, the allocation token.

The invention discloses a hybrid expert model training system based on layer freezing, which relates to the field of model training and comprises an external memory, a freezing controller, a resource allocation controller and a plurality of computing devices. The external memory stores a data set for training the hybrid expert model; the freezing controller performs freezing decision making according to a path selected by an expert and sends the decision to the computing device for execution; the resource allocation controller executes a lexical grouping algorithm based on a frozen layer expert selection path to calculate expert popularity, and allocates computing resources according to the expert popularity; and the computing device stores the hybrid expert model, executes model training operation, executes a layer freezing task according to a layer freezing decision, and feeds back a freezing layer expert selection path and an expert selection path to the resource allocation controller and the freezing controller respectively. According to the method, training of the hybrid expert model is performed through a layer freezing technology, so that the training cost is reduced while the model precision is kept; computing resource allocation is carried out based on a word source grouping algorithm, and equipment load balancing is achieved.

The invention provides a highland cooperative control method fusing a graph convolutional neural network and reinforcement learning, through controlling urban road traffic signal lamps, an expressway ramp signal machine and a variable speed limit unit, expressway traffic congestion is relieved, the urban traffic passing efficiency is improved, road driving vehicles are controlled by means of the signal lamps and the speed limit unit, and the traffic efficiency is improved. Traffic flow scheduling optimization in a global road network is achieved; the whole structure adopts a distributed cooperative control framework, is controlled by a decision-making agent, and performs autonomous decision-making and adjustment according to real-time traffic conditions, so that the adaptability and robustness of the system are enhanced, and the defects of large data calculation amount, difficulty in processing, control strategy lag and the like caused by traditional centralized control are effectively avoided; the graph convolutional neural network model is constructed to aggregate the feature information of the peripheral decision intelligent agent, and the control weight is dynamically allocated, so that the information sharing capability is enhanced, the suboptimal decision caused by lack of comprehensive perception of the surrounding environment is prevented, and the cooperation efficiency of the whole system is improved.