440 results about "Fuzzy control algorithm" patented technology

The invention discloses a battery charging monitoring and adjusting system based on multiple areas, and relates to the technical field of battery management. According to the system, electrochemical impedance spectroscopy, infrared thermal imaging and electric heating parameters are synchronously collected, a physical connection and heat conduction topological relation of a battery pack is constructed in combination with a graph neural network, and monomer aging distribution and a cross-regional heat diffusion path are accurately recognized. Based on multi-region data aggregation, battery health protection, temperature equalization and a power grid demand target are fused, and charging current constraint and equalization priority parameters are dynamically generated. And through a fuzzy control algorithm, an active energy transfer mode and a passive risk isolation mode are intelligently switched, the energy distribution efficiency is optimized, fault spreading is blocked, the risk level of the system is evaluated in real time, a hierarchical regulation and control instruction is triggered, and the weight is dynamically adjusted and optimized through a feedback mechanism. The problems of extensive monitoring, strategy stiffness and safety response lag of a multi-area battery system are solved, the charging safety and economy in a complex scene are remarkably improved, and the service life of the system is remarkably prolonged.

The invention discloses a charging chip real-time power scheduling control method, and relates to the technical field of new energy automobile charging pile power scheduling, and the method comprises the following steps: S1, obtaining the operation parameters of charging equipment in real time, including the voltage fluctuation value of an input power grid, the output current of a charging interface, and the temperature of a charging chip; according to the method, the power grid voltage fluctuation, battery SOC / temperature and chip working condition multi-source data are collected in real time, a multi-target optimization model of dynamic weight distribution is combined, the service life loss of the battery is minimized, the charging efficiency and the power grid load are balanced at the same time, the user charging mode and the battery state difference are taken into consideration by adopting a priority scheduling strategy, and the charging efficiency is improved. Millisecond-level power fine control is achieved through cooperative adjustment of the PWM duty ratio and the switching frequency, personalized charging requirements are met, the overall energy efficiency is improved, a dual safety defense line is constructed through a graded load reduction protection mechanism and a fuzzy control algorithm, and a power distribution scheme is intelligently reconstructed when a power grid is abnormal or a battery is overheated.

The invention relates to the technical field of temperature regulation and control, in particular to a liquid cooling control method and system of a battery control device, in the liquid cooling control method and system, through real-time collection and area screening of temperature and power data, accurate recognition of a high-temperature area is achieved, a clear cooling requirement partition is provided, and the cooling requirement of a battery is met. A dynamic adjustment strategy of pressure and flow parameters of the liquid cooling pump is optimized through a genetic algorithm, the cooling response speed and control precision are improved while energy consumption and cooling efficiency are effectively balanced, the pump speed and the valve opening degree are adjusted in real time, temperature changes are rapidly responded through automatic control, gradual implementation of a cooling target is ensured, and the cooling efficiency is improved. The hysteresis in the heat management process is reduced, the temperature control effect is continuously evaluated through a fuzzy control algorithm, the cooling intensity is dynamically adjusted according to the monitoring result, efficient cooling is ensured, meanwhile, equalization of temperature distribution is achieved, and a systematic heat management framework is established through long-term data monitoring and continuous optimization of cooling operation. And efficient and stable operation of temperature management is realized.

The invention belongs to the technical field of ship path tracking, and discloses a ship path tracking method based on adaptive line-of-sight guidance and fuzzy adaptive PID, and the method comprises the steps: presetting a path point, and obtaining a real-time coordinate; obtaining an actual expected heading angle # imgabs0 # and a ship observation heading angle # imgabs1 #, subtracting the actual expected heading angle # imgabs0 # and the ship observation heading angle # imgabs1 # to obtain a heading deviation # imgabs2 #, and calculating a heading deviation rate # imgabs3 #; the course deviation and the course deviation rate are input into a fuzzy self-adaptive PID motion control module, and gain parameters are output through a fuzzy control algorithm; the gain parameter and # imgabs4 # are input into a PID controller to calculate a ship rudder angle # imgabs5 #; inputting # imgabs6 # into the motion mathematical model to update the motion state, and forming a closed-loop updated motion state to enable the ship to approach a preset path point; and judging a ship path after the state information is updated. The expected course of the ship is calculated in real time and the sideslip angle of the ship and the control parameters of the ship are adjusted in real time through self-adaptive sight guidance, and the control parameters are automatically adjusted in real time by means of the fuzzy self-adaptive PID motion control module to achieve accurate motion control, so that the ship travels according to a preset planned path.

The invention discloses an energy efficiency control method for a cooling fan of an industrial electric cabinet, and the method comprises the steps: firstly collecting temperature, humidity, equipment current / voltage and other multi-mode sensing data, carrying out the PCA algorithm dimension reduction and feature extraction, combining with Granger causality test, thermodynamic principle and machine learning algorithm, and carrying out the building and fusion, thereby obtaining a cooling efficiency model. Thirdly, preprocessing current and voltage data of the equipment, training and optimizing an LSTM model to predict load power, and calculating a fan rotating speed control value through a heat dissipation efficiency model; then, a PWM speed regulation signal is generated by adopting a fuzzy PID control algorithm, and a pulse width modulation and smooth speed regulation mixed strategy is applied to the duty ratio; and finally, energy efficiency indexes are collected to compare and update the weight of the LSTM model, knowledge distillation is introduced to optimize new model training, and self-adaptive adjustment of the rotating speed of the fan is achieved. The rotating speed of the fan can be accurately adjusted, energy consumption is reduced, the energy utilization efficiency is improved, performance reduction of equipment due to overheating is effectively avoided, and the service life of the equipment is prolonged.

The invention discloses a metal plate laser cutting control method, and relates to the technical field of laser cutting, material parameters, thickness information and cutting path data are obtained, a mixed enveloping rectangle algorithm is combined with a genetic algorithm to optimize a cutting sequence, and a path sequence containing idle stroke avoidance and nested graph priority is generated; constructing a laser parameter prediction model based on the material, thickness and path characteristics, and dynamically adjusting the power gradient; the slag splashing state is judged through data fusion of a capacitive sensor and an encoder, a quality feedback signal is extracted in combination with machine vision, and laser parameters are dynamically adjusted through a fuzzy control algorithm; wavefront distortion is monitored in real time, the correction frequency is adjusted according to the slag splashing state, and a deformable mirror is used for compensating the phase; when the quality is abnormal, historical parameter combinations are retrieved through a cosine similarity algorithm for joint compensation. According to the method, the path cutting efficiency is improved, and the problems of low efficiency of path planning and parameter adjustment lagging in the prior art are solved.

The invention provides an ecological circulation barrel-in-barrel culture data acquisition method and system, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the feature extraction of a historical data flow through a multivariable coupling analysis model, carrying out the mode matching through a preset environment threshold interval and a culture environment state matrix, and obtaining a culture environment state matrix; generating a water quality health degree evaluation index and an ecological imbalance early warning signal; and analyzing the water quality health degree evaluation index and the ecological imbalance early warning signal based on a fuzzy control algorithm, dynamically calculating a final feeding amount curve and a water change intensity function, and generating a regulation and control instruction set containing the feeding frequency, the bait particle size and the water pump rotating speed. According to the invention, real-time evaluation and accurate intervention of the water quality health state can be realized.

The invention relates to a winding tension control method and system. The method is applied to a winding tension control device, the device comprises a tension control part and a linear speed control part, and the method comprises the following steps: acquiring a real-time tension detection value and a tension set value of the tension control part, calculating a tension error and a tension error change rate, and performing fuzzy reasoning according to a fuzzy control algorithm to obtain a linear speed control value; pID output parameters are obtained through integral separation PID and used for indicating and controlling a first servo motor of a tension control part; and acquiring a real-time linear speed value and a linear speed set value of the linear speed control part, calculating a linear speed error and a linear speed error change rate, and inputting the linear speed error and the linear speed error change rate into the PID compensation model based on a fuzzy control algorithm to obtain a PID compensation parameter for indicating and controlling a second servo motor of the linear speed control part. According to the method, the tension and the linear speed are subjected to fuzzy control and PID control respectively, the control precision can be improved, and the stability, the response speed and the production efficiency of the winding process are effectively improved.

The invention discloses a UV illumination control method and system for a reel-to-reel exposure machine. The method comprises the following steps: acquiring a real-time moving speed and a tension change value of a coiled material; when the tension change value is greater than the tension threshold value, predicting the deformation trend of the surface of the coiled material based on a nonlinear regression algorithm in combination with the real-time moving speed to obtain a deformation influence value; according to the deformation influence value, a PID control algorithm is adopted to adjust the UV light source, and a light intensity distribution value is obtained; according to the light intensity distribution value, a fuzzy control algorithm is adopted to calculate the output intensity requirement of the UV light source, and speed adjustment is carried out in combination with the real-time moving speed, so that optimized irradiation parameters are obtained; performing area judgment according to the optimized irradiation parameters to obtain an overexposure area and an underexposure area; and adjusting the intensity and distribution of the UV light source in the overexposure area and the underexposure area until the area exposure quality reaches a preset standard range. The method can realize real-time response regulation and control on tension and speed change of the coiled material, and solves the problem of non-uniform exposure dose.

The invention discloses an automatic batching and stirring control system based on an industrial computer, belongs to the field of new wall material production control systems, and aims to solve the problems that the real-time performance is poor, and the influence of raw material characteristic changes on a fall value cannot be pre-judged. Weighing, humidity, infrared flow velocity, temperature, pressure, torque and airflow sensors are integrated, multi-dimensional parameters such as material weight, flow velocity, humidity and air pressure in a bin are monitored in real time, the influence of environmental interference on the sensors is dynamically compensated through multi-parameter collaborative feedback, the real-time performance and reliability of data acquisition are improved, a fuzzy PID control algorithm and a machine learning model are fused, and the real-time performance of the system is improved. A nonlinear mapping relation is established through a training data set, the initial valve opening degree and the fall value are predicted, errors are corrected in real time, dependence on historical data is reduced, the first-time use error of a new formula is reduced, the response time for coping with sudden environment changes is shortened, a single adjustable-caliber electromagnetic valve is adopted, the inner wall is coated with a nano anti-sticking coating, and the service life of the valve is prolonged. And the opening degree is dynamically adjusted in combination with a PID algorithm.

The invention provides a high-efficiency control method and system for a central air conditioner refrigeration machine room, and relates to the technical field of automatic control, and the method comprises the steps: 1, obtaining chilled water supply and return water temperature difference and flow data, and calculating the dynamic cold load demand of a building in combination with the personnel distribution thermal imaging data of each floor; and 2, on the basis of the dynamic cooling load requirement, a dynamic adjustment model for the number of running water chilling units is built, matching degree calculation is conducted on the actual cooling load value and the single refrigerating capacity of the water chilling units through a fuzzy PID control algorithm, and a final unit running combination scheme is generated. By calculating the cooling load requirement, dynamically adjusting the operation parameters of the water chilling unit, the chilled water pump and the cooling tower and balancing the equipment operation time, the system energy efficiency is effectively improved, the energy consumption and the operation and maintenance cost are reduced, and stable operation of the refrigerating system is guaranteed.

The invention discloses a highway tunnel lighting intelligent control method and system based on the Internet of Things, a sensing module is composed of a millimeter wave radar vehicle detector, a tunnel interior brightness sensor, a tunnel exterior brightness sensor and a vehicle speed detector, and a transmission module is a dual-mode communication module composed of a Zigbee wireless network module and a power line carrier communication module. A fuzzy control algorithm library is built in an edge computing gateway of the control module and is used for fusing data of the sensing module in real time and generating a dimming instruction, and each Internet of Things segmentation controller of the control module manages a plurality of lamps and is internally provided with a fault isolation circuit; and an intelligent management platform is arranged in the application module and is used for receiving an instruction of the control module and generating a dynamic dimming strategy. According to the invention, the millimeter-wave radar and video tracking data fusion, Zigbee + PLC dual-mode transmission and edge gateway self-learning algorithm are combined; according to the invention, the defects of the traditional scheme in the aspects of real-time performance, reliability, energy efficiency ratio and operation and maintenance cost can be systematically solved.

The invention discloses a time sequence-based fuzzy PID (Proportion Integration Differentiation) control algorithm dynamic thermal assistance method, which comprises the following steps of: acquiring temperature data of a drilling and riveting area in real time through an infrared sensor, mapping temperature deviation and a change rate thereof to an adjustment weight of a PID parameter based on a fuzzy rule base, and solving the problem of parameter mismatch of the traditional PID in a nonlinear system. Process parameter database matching: establishing an association rule base of a material combination such as a metal-composite material and a preset temperature threshold value, and dynamically setting a temperature control target by combining a thermal physical property heat conductivity coefficient and a melting point of the material so as to realize differential regulation and control of dissimilar materials; the temperature-vibration coupling model based on the LSTM neural network is constructed to precisely and cooperatively regulate and control internal correlation of temperature and vibration, vibration disturbance brought in the temperature rising process is accurately obtained, and dynamic adjustment of the temperature and vibration in the drilling and riveting process is achieved by finely adjusting the power of the active damper.

The invention discloses a target tracking method fusing visual perception and motion control. The method comprises the following steps: improving a YOLOv8 model and pre-training the improved YOLOv8 model; s2, preprocessing an image acquired by a camera, inputting the preprocessed image into the YOLOv8 model trained in the step S1, and outputting a target bounding box and a target center pixel coordinate; target center pixel coordinates are transmitted to a development board of a pre-burning algorithm program through a serial port, the development board is designed according to a stepping motor mathematical model, sine acceleration and deceleration serve as the basis, PID control, sliding mode control and fuzzy control algorithms are fused, and code burning is generated after in-loop simulation optimization; and the development board drives a stepping motor to adjust the posture of the holder according to the target center pixel coordinate control instruction, so that the target stops moving after being kept in the view center. The problems that a traditional YOLOv8 model is large in target recognition error under the complex background, PID control is prone to oscillation under the nonlinear working condition, buffeting exists in sliding mode control, and response lags when fuzzy control is independently used are solved.

The invention discloses a spray drying device for boron carbide production, the spray drying device comprises a spray drying tower, a hot blast stove, a cyclone separator and a system controller, an atomizer and an online detection module are arranged in the spray drying tower, and the online detection module is used for monitoring temperature parameters in the spray drying process; comprising a first temperature sensor, a second temperature sensor and a temperature signal processing unit, the temperature signal processing unit adopts a multi-stage filtering and error compensation technology, noise and interference are effectively suppressed, and the accuracy of detection data is ensured. The air inlet temperature and the air outlet temperature are monitored in real time through the online detection module, the fuzzy-PID control algorithm is combined, the temperature control precision and the response speed are remarkably improved, and temperature fluctuation is reduced. The device dynamically adjusts the heating power of the hot blast stove according to real-time working conditions, the energy utilization efficiency is optimized, and the energy consumption is reduced.

The invention relates to a motor power self-adaptive control method and system based on multi-dimensional sensor data, and the method comprises the steps: collecting multi-dimensional signals, such as ground resistance, motor temperature and battery voltage, in real time, carrying out the self-adaptive filtering and noise reduction, analyzing the correlation of all parameters through a multivariable decoupling algorithm, and determining a power demand weight; when it is detected that the ground resistance is a dominant factor, the system generates a load feature vector through weighted fusion, a database is matched to determine an optimal power target value, and PWM output is dynamically adjusted through a fuzzy control algorithm; and a closed-loop feedback mechanism continuously optimizes control parameters to ensure that the system quickly responds to sudden change of ground resistance. According to the method, intelligent adaptation of the motor power is achieved, the problems that adjustment lags behind and multi-parameter coupling processing is insufficient in the traditional technology are effectively solved, the stability of the sweeping robot under the complex ground working condition is remarkably improved, and the service life of the motor and the service life of a battery are remarkably prolonged.

The invention discloses a control system and method for an automatic beer production line, relates to the technical field of automatic control, is used for solving the problems that state judgment is lagged and abnormal trend is difficult to identify in time, identifies electronic tags of key equipment through an RFID reader-writer, imports models and serial numbers into a database, and automatically associates operation parameters. The distributed sensors collect temperature, pressure, flow and vibration data in real time, the analysis unit calculates the operation deviation and the health degree, a multi-condition control strategy is configured through the programmable logic controller based on the health degree, a time window and a task priority algorithm are combined, real-time data and historical data are compared to recognize abnormity, and the real-time data and the historical data are analyzed. And a fuzzy control algorithm is fused to generate an adjustment instruction, the equipment state is automatically adjusted, time sequence modeling is utilized to analyze whole-process data, a start-stop strategy is formulated, energy distribution and process optimization are performed, and intelligent scheduling and self-adaptive optimization of the beer production line are realized.

The invention discloses an intelligent anesthesia depth regulation and control system based on a multi-modal biological signal, which relates to the technical field of anesthesia depth regulation and control and comprises a multi-modal biological signal acquisition module, a signal fusion processing module, an intelligent anesthesia depth analysis module, an intelligent regulation and control decision module and an intelligent control terminal. Multi-modal biological signals of a patient are collected in real time, multi-modal physiological signals such as electroencephalogram, electrocardio and blood oxygen are fused, intelligent analysis is performed in combination with a deep learning model and a fuzzy PID control algorithm, and in combination with a pharmacokinetic model, the individual difference of the patient can be considered, the anesthesia depth of the patient is accurately evaluated, and the accuracy of anesthesia is improved. Individual anesthetic dosage adjustment is completed, a basis is provided for accurate regulation and control of anesthetic, accurate closed-loop regulation and control of anesthesia depth are achieved, physiological changes of a patient can be responded in real time, the anesthetic dosage can be adjusted in time, and compared with a traditional manual regulation and control mode, the risk of knowing and excessive anesthesia in an operation can be reduced.

The invention provides a seawater cooling control system and method which are applied to the technical field of ocean engineering, and the seawater cooling control system comprises a cooling water well, a first temperature sensor, a water level gauge, a water suction pump, a water delivery pump, a monitoring buoy, a second temperature sensor, a flow meter and a controller. The first temperature sensor and the second temperature sensor monitor the temperature in the well and the coral reef area and the water flow speed of the flow velocity metering area respectively, the water level gauge ensures that the water volume in the well is stable, and data are analyzed in real time through the controller to generate a control instruction. The difference value between the environment temperature and the whitening threshold value, the cooling water temperature in the well and the coral reef flow speed serve as input variables, the flow requirement of the water delivery pump is dynamically calculated through a preset rule base, and self-adaptive adjustment is achieved. Through cooperative feedback of the double temperature sensors, it is ensured that the water delivery temperature is strictly controlled within a coral tolerance threshold value, and heat stress whitening is avoided. Layered water taking is combined with a fuzzy control algorithm, energy consumption is reduced compared with a traditional deepwater extraction scheme, and negative effects of shading measures on zooxanthellae are avoided.

The invention provides a control system and a control method for a suspension aeration fan, and relates to the technical field of intelligent control, and the system comprises an intelligent control module which is used for carrying out the automatic analysis of the operation state of the suspension aeration fan through a fuzzy control algorithm according to the real-time operation parameters of the suspension aeration fan and the environment parameters of an aeration tank, generating a fan adjusting instruction; the execution module is used for adjusting the rotating speed and air flow operating parameters of the fan according to the fan adjusting instruction so as to control aeration; and the coupling module is used for constructing a multiphase flow coupling model, realizing real-time solution of the oxygen transfer coefficient and performing reverse optimization adjustment on the operating parameters according to a simulation result of the multiphase flow coupling model. Through the synergistic effect of the intelligent control module, the execution adjustment module, the multiphase flow coupling optimization module and the fault early warning module, intelligent, efficient and stable operation of the aeration process is achieved, and the reliability and safety of the system are improved.

The invention discloses a robot track online compensation and precision control method and system based on multiple sensors, and belongs to the technical field of robot track control. The method comprises the following steps: acquiring target trajectory data and original data of each sensor, and performing time alignment on the original data of each sensor to generate a fusion data set comprising vibration acceleration data and pose data; performing time-frequency feature extraction based on the vibration acceleration data to obtain a dominant vibration frequency spectrum; constructing a mechanical transfer function model of the joint driving torque and the tail end vibration displacement; based on the mechanical transfer function model, constructing an adaptive notch filter to generate a feed-forward compensation sequence; according to the target trajectory data, the pose data and weight parameters, updated in real time, of the sensors, a trajectory fusion deviation value is obtained through calculation; and after the feedforward compensation sequence and the trajectory fusion deviation value are integrated, a joint driving current instruction is generated based on a fuzzy PID control algorithm. The robot trajectory control precision can be improved.

The invention discloses a modularly-designed new energy automobile charging pile and a charging method, and relates to the technical field of new energy automobiles. Battery parameters, power grid parameters and media parameters in the automobile charging process are collected, collected battery data features are extracted, a battery health assessment mechanism is established, load analysis is carried out, and a fuzzy rule is established; according to the method, social media real-time event data are introduced, the data dimension is expanded, logic judgment is innovated, multi-source data such as batteries, power grids and social media are fused, the load state of the power grids is comprehensively described, and the method is high in practicability and high in practicability. By means of the self-adaptive fuzzy control algorithm, the weight is dynamically adjusted, and the charging power is precisely regulated and controlled, so that the power supply safety is balanced, the charging cost of a user is reduced, the capacity of the charging pile for coping with complex scenes is enhanced, and the intelligence and comprehensive performance of the charging pile are remarkably improved.

The invention discloses a full-automatic feeding control method and system for multiple areas of cattle and sheep, and the method comprises the steps: obtaining basic information and ingestion behavior data of cattle and sheep in each area, carrying out the preprocessing, and carrying out the training through a support vector machine algorithm, and obtaining a cattle and sheep ingestion speed prediction model; a relation model of the feed physical parameters and the feeding speed is constructed, and the initial feeding speed of each area is obtained based on the relation model and the feed physical parameters of each area; acquiring real-time feeding behavior data and real-time satiation degree data of the cattle and the sheep in each area, and judging whether the average feeding speed of the cattle and the sheep meets the requirement or not; if the requirements are not met, based on the change condition of the feeding speed of the cattle and the sheep, a fuzzy control algorithm is adopted to generate a feeding speed regulation and control instruction; and obtaining feeding demand data of cattle and sheep in each region and current feed supply data, and calculating an optimal feed supply speed. Accurate feeding is achieved, the feeding efficiency is improved, and the problems that in traditional feeding, supply and demand are not matched, and the efficiency is low are effectively solved.

The invention relates to the technical field of laser control, in particular to a light spot consistency control method and system for DFB lasers, and the method comprises the steps: obtaining the current and temperature of each DFB laser at each moment in each control period; calculating the burr saliency, the temperature rise drift coefficient, the temperature drop drift coefficient and the heat source interference value of each DFB laser in each control period; and determining expansion and contraction factors of a positive universe and a negative universe in the fuzzy control algorithm, and controlling the temperature of the DFB laser in real time so as to control the light spot consistency of the DFB laser. According to the method and the device, by selecting the proper telescopic factor and dynamically adjusting the discourse domain range of the fuzzy control algorithm, the response speed of temperature control of the DFB laser is improved, the temperature of the DFB laser is controlled more accurately, and light spot consistency control is realized.

The invention provides a temperature control method, device, equipment and system, a storage medium and a program product, and relates to the technical field of industrial control, and the method comprises the steps: determining a PID parameter of a temperature controller of a controlled object; and based on the obtained current environment temperature of the controlled object and the target control temperature of the controlled object, carrying out adaptive adjustment on PID parameters of the temperature controller according to a fuzzy PID control algorithm. And the temperature controller is adjusted according to the PID parameters after self-adaptive adjustment, and temperature control is carried out on the controlled object according to the adjusted temperature controller. According to the invention, the PID parameters of the temperature control system are adaptively adjusted according to the fuzzy PID control algorithm, so that the PID parameters can adapt to the dynamic change of the environment temperature of the system, the overshoot of the system can be reduced, the reaction time of the system can be shortened, and the system can accurately control the temperature of the controlled object under the variable working condition or multi-disturbance condition.

The invention discloses a control method and device based on a PLC system fuzzy algorithm, and belongs to the technical field of water treatment. The device comprises a PLC control module which integrates a fuzzy control algorithm and is used for processing an input signal in real time and generating a control instruction; the target value setting module is used for receiving a liquid level or flow target value set by a user and displaying the liquid level or flow target value through a human-computer interaction interface (HMI); the sensor feedback module is used for acquiring an output actual value of the equipment in real time and transmitting data to the PLC control module; the fuzzy rule base is used for storing fuzzy control rules based on deviation and deviation change rate, and the fuzzy control rules define control logic in an IF-THEN form; the execution control module is used for controlling the running state of the equipment according to the defuzzified control parameters, a preset adjustment interval and a single adjustment amplitude; and the opening degree limiting module is used for setting the maximum opening degree and the minimum opening degree of the equipment, and when the control parameter exceeds the limit, the control parameter is automatically cut off to a boundary value.

The invention relates to an AC / DC generator regulator control method, system and device and a medium, and the method comprises the steps: obtaining the real-time load data and environment data of a generator, carrying out the preprocessing of the real-time load data and environment data of the generator, and obtaining the preprocessed data; transmitting the preprocessed data to a pre-trained load prediction model for comparative analysis to obtain a load prediction result; generating a preliminary control strategy of the generator according to the load prediction result; constructing a virtual model of the generator by using a digital twin condition, simulating states of the generator under different loads and operation, optimizing parameters of the preliminary control strategy based on virtual simulation data, and generating an optimization strategy of the generator; and based on the optimization strategy of the generator, the operation parameters of the generator are adjusted by applying a self-adaptive anti-interference control and fuzzy control algorithm so as to realize stable and efficient operation. The method has the effect of improving the adjustment precision of the generator.

The invention relates to the technical field of electrocatalytic oxidation devices, and discloses an electroplating rinse sewage complex breaking electrocatalytic device based on titanium-based nano conductive ceramics, which comprises an oxidation pond and an acquisition module, the acquisition module acquires catalytic liquid information in real time, and the catalytic liquid information comprises components and state data of a catalytic liquid. And the catalysis module is responsible for treating a catalytic liquid and destroying a complex by utilizing an electro-catalysis reaction. The central control module analyzes complex components of a catalyst through a convolutional neural network (CNN) and a recurrent neural network (RNN), and dynamically adjusts electro-catalysis parameters on the basis of a fuzzy control algorithm in combination with historical data and real-time information so as to optimize the catalytic effect. And the early warning module monitors the changes of the catalytic liquid and the electro-catalysis parameters, judges whether early warning needs to be given out or not by comparing the changes with a preset threshold value, and takes corresponding measures according to the risk level. Through real-time data analysis and intelligent control, the accuracy and efficiency of the catalysis process are improved, and the safety and stability of the treatment process are ensured.

The invention discloses a diamond cutting tooth self-adaptive vibration suppression method based on a fuzzy control algorithm. The diamond cutting tooth self-adaptive vibration suppression method comprises the following steps that S1, a multi-channel signal data set in the diamond cutting tooth machining process is collected in real time; s2, acquiring a preprocessed multi-channel signal data set; s3, carrying out integration to form a feature vector containing multi-dimensional dynamic features; s4, inputting the feature vectors into a fuzzy control module, and performing fuzzy processing on the feature vectors of the channel signals to realize fuzzy quantization of the processing state; s5, generating a control output quantity by using a fuzzy reasoning algorithm according to the fuzzy quantization result, and converting the control output quantity into an executable process control instruction through a defuzzification algorithm; and S6, the process control instruction is fed back to a machining execution mechanism. The method has higher sensitivity and adaptability in unstable machining state recognition, the judgment accuracy of the initial vibration stage can be remarkably improved, and the judgment basis of a control system under complex disturbance is enhanced.

The invention discloses a working area personnel positioning method and system based on a data communication technology, and relates to the technical field of personnel positioning, and the method comprises the steps: estimating the position of a worker in real time through the fusion of an RFID tag and a multi-band signal, and the weighted fusion of a triangulation positioning algorithm and a dynamic signal; according to the method, extended Kalman filtering, multi-target tracking and particle filtering technologies are combined, signal interference is compensated, positioning precision is optimized, a fuzzy control algorithm is adopted for safety early warning, edge calculation and cloud calculation are combined, historical data are analyzed, and the moving trend of workers is predicted. According to the invention, by combining RFID tags, multi-band signals, dynamic signal fusion, multi-target tracking, particle filtering and fuzzy control technologies, high-precision and real-time personnel positioning and safety management are realized, the position of a worker can be accurately estimated, signal interference, attenuation and reflection effects in an environment can be effectively compensated, an early warning strategy is dynamically adjusted, and the working efficiency is improved. And the safety of the working area is improved.