240 results about "Fuzzy pid" patented technology

The invention discloses a self-adaptive dynamic control method and system for the machining process of a numerical control machine tool, and relates to the field of intelligent control, and the method comprises the steps: collecting machining data in real time through physical and virtual sensors, and constructing a standardized data set after layering preprocessing; a CNN-LSTM hybrid model is utilized to extract spatial-temporal characteristics to realize working condition classification, and an NSGA-II algorithm is combined to solve a multi-objective optimization problem to generate an optimal control parameter solution set; parameters are dynamically adjusted through fuzzy PID, and a GRU model is adopted to predict machining errors for feed-forward compensation, so that closed-loop control of perception-decision-execution-feedback is formed. The system continuously monitors the actual machining deviation, parameters are optimized again when the actual machining deviation exceeds a threshold value, and cooperative improvement of machining precision and efficiency is achieved. The method has the advantages that NSGA-II multi-target optimization, fuzzy PID correction and GRU error prediction compensation are recognized through CNN-LSTM working conditions, closed-loop feedback iteration is combined, the machining precision and efficiency are improved in a balanced mode, the service life of a tool is prolonged, and the method is suitable for complex working conditions.

The invention discloses a UPA pressure automatic compensation system and method for mask substrate polishing. The UPA pressure automatic compensation system comprises a pressure execution module, a distributed sensing feedback network and an intelligent control unit. Wherein the pressure execution module is used for directly polishing a mask base plate and comprises a force application shaft, a polishing head, an air source, a UPA air bag and an electric proportional valve, the distributed sensing feedback network comprises an air path pressure sensor and a tail end contact pressure sensor, and the intelligent control unit receives a collection signal of the distributed sensing feedback network and sends the collection signal to the polishing head. On the basis of a current process formula and process parameter coupling model, a data fusion algorithm, a feed-forward compensation algorithm and a fuzzy PID algorithm are operated to obtain a feed-forward compensation amount and a fuzzy PID output amount, the feed-forward compensation amount and the fuzzy PID output amount are superposed, a total control voltage is generated and output to an electric proportional valve, and then the input air pressure of a UPA air bag is adjusted. Therefore, closed-loop control over the polishing pressure of the mask substrate is achieved. Through multi-sensor data fusion, fuzzy PID self-adaptive control and intelligent feed-forward compensation based on a process parameter coupling model, real-time, accurate and constant control of the polishing pressure is realized, so that the surface precision and yield of the mask substrate are improved.

The invention relates to the field of coal mine geological disaster monitoring, in particular to a coal mine surface slope remote sensing data fusion monitoring method and system, and the method comprises the steps: collecting multi-source data through a satellite-unmanned aerial vehicle-ground three-stage network, and carrying out the cleaning, correction and standardization preprocessing; utilizing an improved LSTM model which introduces an attention mechanism and a geological parameter correction item to predict slope displacement and risk levels; distributing monitoring resources through a PSO (Particle Swarm Optimization) algorithm, dynamically adjusting an equipment state through a fuzzy PID (Proportion Integration Differentiation) algorithm, and fusing multi-source data through a Bayesian algorithm to generate a high-dimensional matrix; and finally, storing data based on the alliance chain and performing early warning based on a dynamic threshold value. The system correspondingly comprises six core modules. The problems of narrow coverage, poor timeliness and low data utilization rate of traditional monitoring are solved, millimeter-level precision monitoring is realized, the early warning response is less than or equal to 5 minutes, the cost is reduced by more than 40%, and the method is suitable for safety and ecological monitoring of various coal mine slopes.

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 desulfurization towers, in particular to an ultrasonic agglomeration dedusting and demisting device of a desulfurization system and an operation method thereof, and aims to solve the problems that in the prior art, fine particles in flue gas are not subjected to agglomeration pretreatment, a targeted cleaning mechanism is lacked, and a demister is easily blocked due to filter residue attachment after long-term operation; and finally, the dedusting and demisting efficiency of the desulfurizing tower is reduced. According to the invention, the ultrasonic generation module is started, parameters are dynamically optimized based on a PLC and a fuzzy PID algorithm to induce agglomeration of PM2.5 and fog drops, the particle size is increased through a depressurization ring, and then efficient gas-liquid separation is carried out through a dual separation mechanism; when filter residues are attached, the motor drives the spray pipe to rotate and spray, the cleaning assembly is matched for wiping, the guide assembly guides waste liquid, the intelligent system adjusts in real time and triggers a cleaning program, a pretreatment and cleaning mechanism is established, blockage is eradicated, stable operation of parts is ensured, and the dust and mist removal efficiency is improved.

The invention relates to the technical field of industrial environmental protection, in particular to a double-hearth lime kiln low-emission collaborative dust removal system and a control method. The control method comprises the steps that a flue gas sensing module collects real-time flue gas parameters and kiln body working condition data; the working condition linkage regulation and control unit dynamically adjusts operation parameters of the dust removal equipment through a fuzzy PID working condition matching algorithm; the regional collaborative dust removal assembly performs differential dust removal according to flue gas characteristics and treatment requirements of different dust raising points, and flue gas flow guide is performed through a double-hearth time sequence valve group during kiln body switching; the noise elimination and vibration isolation cooperation unit adjusts the noise elimination amount and the vibration isolation damping according to the rotating speed of the draught fan and controls noise and vibration. The tail gas deep purification unit evaluates the dust removal state through a flue gas and dust coupling model, carries out deep treatment on the dedusted tail gas and controls the tail gas emission concentration; the anti-blocking optimization unit carries out cooperative anti-blocking through dynamic rapping and airflow purging based on historical operation data and real-time working conditions. Therefore, the problems of poor dust removal stability, high operation energy consumption and the like in the prior art are solved.

The invention relates to an automatic printing calibration method and system combining vision and AI and a storage medium, a multi-mode sensing unit integrated on a printing head assembly synchronously collects two-dimensional images, three-dimensional shapes and working spacing data of a printing area in real time, and data fusion is carried out by using a model based on a neural radiation field; generating a high-fidelity multi-dimensional digital mapping; carrying out defect identification and positioning by adopting a pre-trained convolutional neural network CNN model, and predicting an optimal adjustment parameter according to the defect information and the historical sequence through a long short-term memory network LSTM model; the edge calculation and control unit is combined with a material characteristic database to generate a hierarchical calibration instruction in a millisecond level, adopts fuzzy PID self-optimization control to dynamically set PID control parameters, and is combined with feed-forward compensation of the inertial measurement unit to perform accurate, smooth and robust control on an execution mechanism, so that the accuracy of calibration is improved. And full-automatic, high-precision and real-time online calibration of the printing process in a complex industrial environment is realized.

The invention relates to the technical field of industrial furnace temperature control, and discloses a tunnel furnace fuzzy PID temperature control process with strong anti-interference adaptive ability, which comprises the following steps: temperature signal acquisition: acquiring actual temperature values of each area in real time through temperature sensors arranged in different heating areas of a tunnel furnace, and calculating temperature signals of the actual temperature values; the collected temperature signal is converted into a digital signal to be transmitted to the temperature controller; and interference signal identification and classification: calling a preset interference identification model by the temperature controller, and carrying out fluctuation characteristic analysis on the acquired temperature signal. By adopting a dual-redundancy temperature acquisition mode combining distributed optical fibers and K-type thermocouples and combining an interference identification model based on an LSTM neural network, accurate identification and classification of interferences such as feed quantity fluctuation, power supply fluctuation and airflow disturbance in a kiln are realized, and through dynamic correction of fuzzy PID (Proportion Integration Differentiation) parameters and an interference compensation mechanism, the disturbance of the kiln can be accurately identified and classified. And the anti-interference capability of the tunnel kiln temperature control system is obviously improved.

The invention discloses a self-adaptive pipetting system and method based on multi-mode sensing fusion. The system comprises a PLC (Programmable Logic Controller), a fusion multi-mode sensing module, a high-throughput execution module, a self-adaptive protocol matching module and a man-machine interaction module. According to the invention, through multi-channel cooperation and continuous transmission, the experiment efficiency is greatly improved; multi-modal sensing data are fused, and real-time closed-loop control and dynamic compensation are performed by adopting algorithms such as fuzzy PID (Proportion Integration Differentiation) and the like, so that the pipetting volume precision reaches + / -1%, and the repeatability is improved by 20-30%; a protocol feature library and an intelligent matching algorithm are built in, and experimental parameters can be automatically analyzed, matched and optimized; equipment state and process parameters are monitored in real time, faults and pollution risks are automatically early warned, and the operation safety and reliability are remarkably improved in combination with automatic anti-pollution design; a PLC is deeply fused with a sensing module and a decision module, a sensing-decision-execution intelligent closed loop is constructed, and an accurate and reliable integrated solution is provided for automatic pipetting.

The invention discloses a hydraulic servo control system and method for a mining guniting robot. Belongs to the technical field of servo control. Comprising a hydraulic driving unit, a sensing and feedback unit, an electrical control unit, an embedded host and a man-machine interaction unit, wherein the electric control unit adopts a fuzzy PID (Proportion Integration Differentiation) controller for controlling the joint position of the mechanical arm according to the information of the sensing and feedback unit; aiming at linear synchronous control of chassis walking, an anti-integral saturation speed feedforward PI controller is adopted to adjust the opening size and direction of a hydraulic proportional valve in real time, and closed-loop control of the position is achieved.

The invention belongs to the technical field of heavy-load vehicle control, and particularly discloses a bottom die trolley walking control method and system, and the control method comprises the steps: starting a task and setting parameters; collecting multi-dimensional data in real time; a displacement target is judged; calculating theoretical motion parameters; target torque distribution and instruction adjustment; and finishing the task and resetting the system. According to the control method, torque control, speed control, displacement control and energy consumption optimization are fused, a closed-loop feedback strategy, a fuzzy PID self-adaptive algorithm and a multi-motor cooperative algorithm are utilized, and track pre-detection and energy recovery are combined, so that the heavy-load and high-rigidity bottom die trolley can still run stably and accurately under the non-ideal track condition, and the control method is suitable for large-scale production. The control precision and stability of trolley running are remarkably improved, running deviation caused by poor rails and structural rigidity is reduced, the linear and dimensional precision of segmental beam prefabrication is guaranteed, and meanwhile the equipment failure rate, the maintenance cost and the energy consumption are reduced.

The invention discloses an end face tool sharpener control system, and relates to the technical field of numerical control systems. The end face tool sharpener control system comprises a data preparation and recording module, a tool type parameter dynamic modeling module, a multi-axis linkage control module, a grinding wheel pressure self-adaption control module, a grinding wheel abrasion compensation module and a technological parameter optimization module. By comprehensively collecting multi-dimensional historical processing data and constructing a set framework, automatic classified storage of parameters is realized; the NURBS curve interpolation algorithm is adopted, and the machining precision and smoothness of the complex shape are guaranteed; instructions are synchronized in real time, errors are compensated, vibration is monitored in combination with an acoustic emission sensor, and machining stability is improved; a fuzzy PID model and machine learning are utilized to dynamically adjust parameters and optimize the parameters in advance; through machine vision and digital twinning, abrasion is accurately recognized, and the finishing period is predicted. And based on the hybrid model and reinforcement learning, predicting a processing result, dynamically adjusting parameters, and performing error compensation and sensitivity analysis.

The invention relates to the technical field of air conditioner control, in particular to a refrigeration and dehumidification optimization method, device and equipment and a storage medium. According to the method, expected humidity and expected temperature serve as target parameters, real-time environment humidity and real-time environment temperature are collected to serve as real-time working parameters, and temperature and humidity two-dimensional control is achieved by calculating derivative parameters; the limitation of a traditional single temperature control mode is broken through, and the health risk caused by excessive reduction of humidity is avoided; the self-adaptive fuzzy PID algorithm is adopted to calculate the basic frequency, and compared with a traditional PID control method, the algorithm can dynamically adapt to environment changes, and the real-time performance and accuracy of compressor frequency adjustment are improved; through the cooperative adjustment of the refrigeration correction target frequency and the fan target gear, the refrigeration efficiency is optimized, and the convergence of the temperature to the target parameter is accelerated; by adjusting and monitoring the working state of the air conditioner, continuous optimization of the refrigeration and dehumidification process is ensured, and the reliability of the whole system and the somatosensory comfort of a user are improved.

The invention relates to the technical field of hydrogen energy preparation and process control, and discloses a fuzzy PID (Proportion Integration Differentiation)-based pressure control method for an alkaline electrolytic water hydrogen production system, which comprises the following steps of: firstly, acquiring current, pressure and separator liquid level data of the system in real time, and calculating a source-load gradient synergistic factor for representing the hysteresis degree of source end disturbance and load end response according to the current, pressure and separator liquid level data; and then pump valve heterogeneous cooperative control is executed, the rotating speed of a circulating pump is actively adjusted through the factor so as to change the flow speed of electrolyte, and feed-forward regulation and control of the gas holdup are achieved. Meanwhile, a gas phase rigidity coefficient is solved according to liquid level changes, a virtual damping domain is constructed, and PID integral and differential parameters are corrected in a self-adaptive mode; and finally, asymmetric variable universe fuzzy reasoning is executed, a hydrogen side universe is compressed through a source load gradient, an oxygen side driven dead zone threshold value is dynamically set, and a double-side valve instruction is output. According to the method, the problems of pressure lag and rigidity time varying under wide power fluctuation are effectively solved through flow velocity auxiliary adjustment and rigidity self-adaption strategies, and efficient and stable operation of the system is achieved.

The invention discloses a multi-fuel combustion boiler SCR (Selective Catalytic Reduction) ammonia injection fuzzy PID (Proportion Integration Differentiation) parallel superposition mixing control system and method, and belongs to the field of boiler flue gas pollutant control. The system adopts a hybrid control architecture in which a fixed parameter PID controller and a fuzzy logic controller (FLC) work in parallel. The system calculates the deviation and the change rate of the NOx concentration of an outlet in real time, on one hand, the fixed parameter PID controller outputs the reference ammonia spraying amount, and accurate control under the stable working condition is achieved; on the other hand, the fuzzy logic controller outputs an intelligent compensation control quantity according to the deviation and the change rate, and the intelligent compensation control quantity is specially used for coping with severe working condition changes. And finally, the two outputs are superposed as a total ammonia spraying instruction. According to the method, the adaptive capacity and the control robustness to multi-fuel complex working conditions are improved. The fuzzy controller can perform coarse adjustment quickly when the working condition changes drastically, and the deviation is restrained quickly; and the fixed PID is responsible for fine adjustment after the system is stable, so that ammonia escape is effectively reduced, and the denitration efficiency is ensured.

The invention relates to the technical field of intelligent agriculture and water-saving irrigation equipment, and discloses a dynamic optimization and intelligent regulation and control system and method for a drip irrigation pipe for intelligent agriculture, and the system comprises a dynamic pipe optimization unit, a multi-source sensing monitoring module, and an intelligent regulation and control execution module. Through cooperation of a PID algorithm of the central control module and a fuzzy PID strategy, when the pressure deviation is larger than 0.05 MPa, Kp is increased for quick response, when the pressure deviation is smaller than or equal to 0.05 MPa, Ki is increased for stable pressure, dripper flow uniformity compensation is matched, and the dripper flow deviation is smaller than or equal to 5%; in an extreme weather emergency level, the irrigation interval is shortened, the flow speed is reduced and evaporation is reduced at high temperature and strong wind, heat tracing and heat preservation are performed at low temperature, pipes are thickened to prevent icing, irrigation is delayed and pressure is reduced when rainfall is predicted to be larger than 20 mm, and soil is prevented from being too wet; and meanwhile, unmanned aerial vehicle inspection is integrated, regional valves are automatically closed and the flow is adjusted when faults occur, and the overall uniformity is guaranteed. Finally, the water resource utilization rate is increased by 20%-25%, the crop yield is increased by 10%-15%, and the energy consumption per unit area is reduced by 30%.

The invention belongs to the technical field of high-temperature alloy smelting equipment control, and discloses a method and system for predicting, controlling and adjusting water flow of a consumable vacuum furnace for high-temperature alloy. Aiming at the problems of water flow regulation lag, low prediction precision, large quality fluctuation and high energy consumption in the smelting process of an existing vacuum consumable electrode furnace, the method predicts the water flow in the next five seconds by adopting an LSTM-XGBoost fusion model through multi-source data acquisition and wavelet transform preprocessing, realizes self-adaptive adjustment within one second by combining a fuzzy PID algorithm, and improves the prediction accuracy of the water flow in the next five seconds. The model is reversely optimized based on the cast ingot flaw detection qualification rate and the composition segregation degree; the matching system comprises a data acquisition module, a data processing module, a prediction control module, an execution module, a feedback monitoring module and a software system, and supports off-line operation and multi-mark alloy adaptation. And the flaw detection qualification rate of the high-temperature alloy cast ingot is increased to 97.8%, the cooling water consumption of a single furnace is reduced by 11.8%, the energy consumption of a water pump is reduced by 20.8%, the quality stability of the cast ingot can be effectively guaranteed, the production cost is reduced, and the method is suitable for vacuum consumable remelting production of high-temperature alloys such as GH4169 and the like.

The invention provides a temperature control system and method based on a fuzzy PID composite algorithm, and relates to the technical field of temperature control. According to the system, the circulation rate of a liquid-phase heat transfer medium is precisely regulated and controlled through a micropump, the gas-phase heat transfer efficiency is enhanced in combination with a fan, and real-time feedback of a temperature detection module and closed-loop cooperative adjustment of a main control module are matched; a composite control framework is constructed through a fuzzy control module and a PID control module, and wide-range, high-precision and rapid temperature control over a target object is achieved. The fuzzy control module dynamically adjusts PID parameters in real time according to the temperature deviation and the deviation change rate, the PID control module outputs accurate control signals based on the adjusted parameters, a micropump and a fan are driven to adjust the temperature of a target object, and the problems that a traditional temperature control system is slow in response, narrow in temperature control range and poor in high and low temperature scene adaptability are solved. The system is suitable for scenes such as temperature control of high-power-density assemblies and heat dissipation of electronic devices.

The invention discloses a magnetorheological polishing liquid supply system and method based on a jet technology, and relates to the technical field of magnetorheological polishing, the magnetorheological polishing liquid supply system comprises a liquid storage and conveying module, the liquid storage and conveying module comprises a liquid storage device, a conveying device and a pulsation attenuation module, and the magnetorheological pulsation attenuation module is provided with a magnetorheological pulsation attenuator which is connected in series between an outlet of a servo variable pump and a conveying pipeline; the spraying execution module comprises a nozzle and a position adjusting assembly; the multi-dimensional detection module comprises a visual sensor, a Coriolis flow meter and an MEMS pressure sensor; the modeling and predicting module is used for calculating pipeline resistance according to the relative position of the nozzle and the workpiece and predicting pulsation by decomposing a pump pulsation rule through Fourier transform; and the dynamic regulation and control module is used for controlling the attenuator to counteract the pulsation according to the pulsation prediction output reverse current, and regulating the displacement and the rotating speed of the pump in real time through a fuzzy PID algorithm in combination with preset target flow and pressure. The problem that in the prior art, the injection parameter control precision is limited is solved, and high-precision regulation and control are achieved.

The application provides a double-fed variable-speed pumped storage unit cooperative control method based on a fuzzy PID, and belongs to the field of pumped storage unit control methods.The method comprises the following steps: S1, obtaining an error and an error change rate in a pumped storage unit; S2, inputting the error and the error change rate into a designed fuzzy controller to output a proportional coefficient increment and an integral coefficient increment; S3, combining an original proportional coefficient quantity and an original integral coefficient quantity of the pumped storage unit to output updated control parameters; S4, obtaining an actual water head and a theoretical water head of the pumped storage unit, dynamically adjusting a proportional coefficient gain coefficient and an integral coefficient gain quantity, and combining the updated proportional coefficient quantity of the pumped storage unit and the updated integral coefficient quantity of the pumped storage unit to jointly input into a PID controller; and S5, outputting an opening degree signal by the PID controller to an actuating mechanism, so that the actuating mechanism controls the opening degree of the variable-speed pumped storage unit.The method has high adaptability.

The invention relates to the technical field of fully-mechanized coal mining automation control, and discloses a hydraulic support lifting control method and device based on flow proportion and attitude feedback, and the method comprises the steps that a controller establishes a physical parameter model, and the controller calculates the target flow of a stand column oil cylinder and the target flow of a bottom lifting oil cylinder according to a kinematics coupling model; the controller executes a feedforward and fuzzy PID composite control strategy, the controller generates a feedforward instruction and combines the feedforward instruction with the feedback control quantity to synthesize a final valve control instruction, and the controller drives the electro-hydraulic control valve set to act; the controller monitors the synchronous error of the adjacent hydraulic supports and corrects a final valve control instruction, and the controller monitors the speed matching state and executes attitude priority deviation correction; the controller judges whether lifting is completed or not according to the displacement of the stand column oil cylinder, the displacement of the bottom lifting oil cylinder and the pitch angle of the hydraulic support, and the controller executes valve port smooth closing logic. According to the invention, the track tracking precision and the dynamic response speed of the lifting frame are improved, the action synchronism and the attitude stability are ensured, and hydraulic impact is eliminated.

The invention relates to the technical field of industrial real-time control software, in particular to a tea processing equipment self-adaptive temperature control system based on fuzzy PID, and the system comprises the steps: obtaining a temperature parameter, a moisture content parameter and a color characteristic quantity; calculating a deviation signal, a deviation change rate and a water content change rate; calculating a model drift vector according to the acquired parameters and scaling an optimization domain space in a sparrow search algorithm; performing online global optimization on the PID control parameters, and if a preset condition is met, superposing a penalty weight in a target function, and outputting reference PID parameters; monitoring a sudden change point identification switching moment; at the switching moment, smooth interpolation switching is carried out on the multiple sets of fuzzy rule matrixes, and PID parameter correction increments are output; and generating an adaptive control signal based on the reference PID parameter, the PID parameter correction increment, the deviation signal and the deviation change rate, and driving an execution mechanism to perform process control. And self-adaptive industrial control is realized by sensing the change of physical property parameters.

The application discloses an industrial label printing self-adaptive optimization method based on multi-dimensional defect quantification. The method realizes intelligent management and control of label printing quality through task data preparation, image acquisition and parallel diagnosis, defect quantification and shunt decision, quality trend analysis and self-adaptive tuning, and predictive maintenance warning. The core of the method is to construct a defect severity index quantification model, combine the improved YOLOv8 algorithm to realize accurate classification and root diagnosis of defects, and realize real-time fine tuning of printing parameters through a fuzzy PID self-tuning tuning engine, and match a cache level real-time bit-level check to ensure data accuracy. The application breaks through the limitations of traditional passive detection, realizes active optimization and predictive maintenance, greatly improves production efficiency and reduces the rate of defective products, ensures stable label printing quality and accurate data, and is suitable for high-speed industrial label printing scenes.

The present application relates to the technical field of chemical process equipment control, and particularly relates to a polyformaldehyde polymerization auxiliary agent feeding system, which comprises a collection module, a buffer module, a metering module, a control module, a conveying module, a blocking module and a connecting module. The collection module acquires auxiliary agent attribute parameters and environmental data in real time; the buffer module maintains a micro-positive-pressure inert environment through a nitrogen sealing unit to prevent material oxidation; the metering module generates high-precision data by monitoring quality changes using a liquid loss balance; the control module dynamically adjusts the conveying rate based on a fuzzy PID algorithm; the conveying module uses a micro gear pump to reduce internal leakage; the blocking module absorbs fluid pulsation through a pulse damping unit; and the connecting module has a flexible pipeline structure to block mechanical vibration transmission. The modules cooperate to realize the precise conveying of several milliliters to tens of milliliters of auxiliary agent per hour, improve the feeding stability and precision, and ensure the polyformaldehyde polymerization reaction effect.

This invention provides a miniature general-purpose electrical control device and method, including a power adapter module, a PLC programming control unit, a central coordination controller, and an integrated control module. The invention acquires input power signals, identifies their type and amplitude range, and generates electrical state identifiers. Based on these identifiers, it selects the corresponding rectifier topology, converting the input power into a stable intermediate DC bus voltage, forming a reconfigurable DC energy pool. It acquires multi-channel load state data through miniature sensor nodes, generating a multi-dimensional load feature vector. Using an improved fuzzy PID coordination controller, it integrates load characteristics with a preset channel priority strategy, calculates energy demand weights, and generates a dynamic power allocation matrix. Based on this matrix, it adjusts the operating mode and power flow of the bidirectional DC / DC converter. This invention significantly improves power adaptability and energy utilization in multi-input, multi-output power supply scenarios, effectively addressing complex operating conditions such as grid fluctuations and uneven load distribution.

The invention discloses a plasma activated water preparation system based on fuzzy PID (Proportion Integration Differentiation) adaptive temperature and power matching cooperative control. The plasma activated water preparation system comprises a human-computer interface, a main controller, a temperature / power sensor, a parallel double fuzzy PID controller, an intelligent coordinator, a power / temperature actuator and a plasma reaction machine, a temperature / power sensor sends a water body temperature Tfb and a discharge power Pfb to a main controller in real time, a temperature fuzzy PID controller and a power fuzzy PID controller output suggested powers Ut and Up, an intelligent coordinator outputs a final power instruction and a cooling control signal after arbitration according to a state machine that Tfb is smaller than or equal to Tset normal power, Tfb is larger than Tset and Pfb is larger than Pmin and power is preferentially reduced, and Tfb is larger than Tset and Pfb is smaller than or equal to Pmin and is forcibly cooled. And the power actuator continuously adjusts the discharge power according to the discharge power, and the temperature actuator implements auxiliary heat dissipation, so that the water temperature is accurately locked in the optimal active matter generation interval under the nonlinear and time-varying working conditions, the discharge intensity is ensured not to be lower than Pmin, and high-activity, high-energy-efficiency, continuous and stable plasma activated water preparation is realized.

This invention belongs to the field of dehumidification equipment technology and discloses a precise temperature control system for a variable frequency dehumidifier with dual-mode temperature and humidity coordination. Through deep collaboration between the dual-mode decision module and the temperature and humidity calibration module, it dynamically switches between dehumidification-priority and temperature-priority modes based on a fuzzy PID fusion algorithm. Adjustment weights are allocated in real time according to temperature and humidity deviations. Combined with dew point temperature modeling and complementary correction technology, it achieves synchronous and precise control of both parameters. A multi-sensor layout covers key locations, coupled with an adaptive self-calibration mechanism and data preprocessing function, ensuring the accuracy and stability of the collected data and adapting to various extreme temperature and humidity conditions. During mode switching, collaborative commands link various execution modules, avoiding humidity rebound after cooling shutdown or dehumidification failure during temperature control. The variable frequency speed control module uses an adaptive fuzzy PID algorithm with multi-input fusion to dynamically optimize speed parameters. Combined with a dynamic frequency step size adjustment mechanism, it achieves rapid response to large deviations and precise fine-tuning for small deviations.

The invention relates to the technical field of oil and gas field moisture on-line metering, in particular to a moisture bimodal metering system based on vortex reinforcement for a gas well, which comprises a three-section type vortex separation pipe and a metering unit. The separation pipe adopts a spiral flow deflector and an umbrella-shaped flow stabilizer, so that the separation efficiency is enhanced, and the pressure drop is reduced; the metering unit realizes high precision through pressure-temperature compensation, and meanwhile, the accuracy is improved by combining a Coriolis flowmeter and density feedback calibration; the liquid level is controlled by adopting a fuzzy PID algorithm, and the response time is less than or equal to 2s. The device can remarkably improve the metering precision, and is suitable for efficient separation and precise metering of conventional gas field moisture.

The invention relates to the technical field of ship power systems, in particular to a ship power system energy efficiency optimization control method based on artificial intelligence, and the control method comprises the steps: S1, carrying out the real-time collection and preprocessing of multi-source data; s2, power system energy efficiency state modeling based on an LSTM-CNN fusion model; s3, solving energy efficiency optimization parameters based on an improved particle swarm algorithm; and S4, carrying out optimal control instruction execution and feedback adjustment based on fuzzy PID (Proportion Integration Differentiation). According to the ship power system energy efficiency optimization control method based on artificial intelligence, the convergence speed can be improved through precise modeling of the LSTM-CNN fusion model and dynamic optimization of the improved particle swarm optimization, compared with a traditional control method, the comprehensive energy consumption rate of the ship power system can be reduced, the fusion model can rapidly capture dynamic changes such as sea conditions and loads in real time, and the control method is suitable for large-scale popularization and application. And the fuzzy PID controller can realize overshoot-free adjustment, so that the operation and maintenance cost can be effectively reduced, and the equipment failure rate is reduced.

The application discloses a water mist removal method and system of an unmanned sensing device, relates to detection control, and comprises the following steps: collecting temperature data and humidity data of a vehicle-mounted environment in real time through at least two temperature and humidity sensors; performing filtering processing on the collected temperature data and humidity data, and calculating a historical temperature change rate to form a feature vector; inputting the feature vector into a pre-trained lightweight neural network model, performing reasoning, and outputting a water mist level of a current environment, wherein the water mist level comprises four levels of safety, early warning, mildness and severity; determining corresponding air supply temperature parameters and fan rotating speed parameters through a preset mapping relationship table according to the water mist level; calculating a power control signal of a PTC heating sheet by using a fuzzy PID algorithm according to the air supply temperature parameters; and simultaneously generating a rotating speed control signal of the fan according to the fan rotating speed parameters. In view of the fact that a traditional passive demisting mode fails within several minutes in a high-humidity saturated underground environment, the application improves the active demisting effect through hierarchical control.