203 results about "Fuzzy pid controller" patented technology

Disclosed is a motor fuzzy PID parameter tuning method based on an improved whale algorithm. The method comprises: building a brushless direct-current motor speed control system model, and using a fuzzy PID controller to perform motor speed control. A conventional whale algorithm is optimized by using a chaotic convergence factor, a fractional order, and Levy flights, so as to obtain an improved whale algorithm. Secondly, the overshoot of the system is used as a component of an ITAE performance index to obtain an improved ITAE performance index, and the improved ITAE performance index is used as a fitness function for the improved whale algorithm. Finally, the improved whale algorithm is used to optimize input and output membership functions of a fuzzy controller, so as to obtain optimal ΔKp, ΔKi, and ΔKd values, and Kp, Ki, and Kd parameters of a PID controller are tuned to implement motor speed control. The present invention addresses the difficulty of tuning parameters of conventional PID controllers and solves the problem of low precision of motor speed control, has the advantages of high anti-interference capability, little overshoot, and short adjustment time, and improves the dynamic characteristics and robustness of the controllers.

The invention discloses an intelligent film-drawing and unwinding control method and system based on real-time tension, and relates to the field of automatic control and intelligent manufacturing, and the method comprises the following steps: ensuring normal starting of equipment and system states through equipment self-inspection and technological parameter input; tension and speed data are collected in real time and preprocessed, and support is provided for fuzzy PID control; the parameters of the fuzzy PID controller are dynamically adjusted by calculating the tension error and the change rate of the tension error so as to adapt to different membrane material characteristics and unwinding working conditions; an improved genetic algorithm is used for optimizing parameters of a PID controller, overshoot is minimized, the adjusting time is shortened, and the robustness and the anti-interference capability of the system are improved; a closed-loop control system is constructed, and the stability of unwinding tension is ensured through real-time feedback signals; and the system state is monitored in real time in combination with an anomaly detection algorithm, and a control strategy is automatically adjusted or fault protection is performed. The control method disclosed by the invention can be widely applied to the fields of film unwinding and automatic production lines, and has a relatively high intelligent level.

The invention relates to the technical field of self-adaptive control, and discloses a self-adaptive temperature control method and system for an automobile heater, and the method comprises the steps: calculating the real-time temperature deviation and temperature change rate of an actuator according to multi-dimensional temperature data; thermal inertia dynamic analysis is carried out on the historical heating power and temperature response relation through a preset thermal inertia compensation function, and a thermal inertia index of the actuator is obtained; the real-time temperature deviation, the temperature change rate and the thermal inertia index are jointly input into a preset fuzzy PID controller, and a preliminary power adjustment instruction of an actuator is output; analyzing the temperature change trend of the actuator in the time period, and performing prospective correction on the initial power adjustment instruction based on the temperature change trend; and controlling an actuator to execute heating operation according to the temperature control instruction, collecting real-time feedback temperature after the heating operation is executed, and performing joint online correction on parameters of the thermal inertia compensation function and a prediction coefficient of the time sequence model according to the real-time feedback temperature. According to the invention, the accuracy of self-adaptive temperature control of the heater can be improved.

The invention discloses a multi-objective optimization decision control method for shrimp and silkworm polyculture environment parameters, and relates to the technical field of polyculture control. The method comprises the following steps: deploying a water quality sensor network, and combining prawn and nereis growth monitoring equipment; extracting criticality of environmental parameters and biological growth indexes by using historical breeding data and experimental data; constructing a dynamic coupling model, and establishing a dynamic model of the polyculture system based on a differential equation; developing a hybrid optimization algorithm to balance the competition and symbiotic relationship between the prawns and the nereis; and generating a control instruction set based on an optimization result, and adjusting the control equipment through a fuzzy PID controller. According to the invention, intelligent regulation and control of shrimp and silkworm polyculture environment parameters are realized, and economic benefits of shrimp and silkworm polyculture are improved.

The invention relates to the technical field of printed circuit board manufacturing and quality detection, in particular to a PCB forming detection method based on a hole site scatter diagram and SPC analysis, and the method comprises the steps: collecting the actual hole site data of a PCB substrate through an optical scanner or a laser measurement device, generating a scatter diagram containing coordinates, aperture and tolerance, and carrying out the detection of the hole site scatter diagram; an abnormal region is identified by using an improved density clustering algorithm; performing multi-dimensional analysis on the scatter diagram based on an SPC model, extracting characteristic parameters such as hole site density deviation, constructing a dynamic control limit, and calculating a CPK to judge a processing state; and when the CPK is lower than a threshold value, optimization instructions such as drilling path correction and drill bit wear compensation are generated and fed back to the equipment through the anti-saturation fuzzy PID controller to realize closed-loop control. According to the method, the hole site machining quality can be accurately detected, the machining parameters are adaptively adjusted, and the PCB forming precision and the production stability are effectively improved.

The invention discloses a data cable self-adaptive production method and system based on image analysis, and the method specifically comprises the steps: synchronously collecting three-mode image data containing visible light, infrared light and polarization at a gas injection section, an extrusion section and a molding section of a data cable through a multispectral imaging unit; performing spatial alignment on the three-mode image data by adopting a sub-pixel registration algorithm to obtain standard image data; based on the standard image data, combined diagnosis is carried out on the cable gas injection structure, the insulation layer quality and the surface defect through a multi-task analysis engine, and a defect diagnosis result is obtained; and based on a defect diagnosis result, dynamically adjusting the traction speed, the extrusion temperature and the gas injection pressure by utilizing a fuzzy PID controller optimized by reinforcement learning to form online process parameter closed-loop control. The defects of single function, static detection, high data dependence and the like of a traditional data cable production detection method are effectively overcome, and a more efficient and intelligent solution is provided for data cable production.

The invention provides a quadrotor unmanned aerial vehicle suspension swing suppression flight control method based on a DDPG. The method comprises the steps that a kinetic model of a quadrotor unmanned aerial vehicle suspension system is established; performing input shaping processing on an expected reference track signal by using a ZVD input shaper; the unmanned aerial vehicle suspension system is decoupled into position control of a position loop and attitude control of an attitude loop by adopting a cascade trajectory tracking control strategy, and a fuzzy PID controller of the position loop is designed based on a fuzzy theory; the shaped track signal is input into a fuzzy PID controller, and parameters of the PID controller are adjusted on line; performing attitude settlement on the virtual control quantity output by the fuzzy PID controller, and inputting the virtual control quantity into an active disturbance rejection controller; roll, pitch, and yaw torque control quantities are generated based on the virtual control quantity of the attitude loop and the control quantity generated by the DDPG-based tilt angle controller. Under a complex external interference environment, a preset track is tracked with high precision, load swing is effectively suppressed, reliable execution of a transportation task is successfully guaranteed, and meanwhile, the control precision and the anti-interference capability of the system are remarkably improved.

The invention relates to an automatic identification control method and system based on heat dissipation of a liquid cooling plate in a heat exchange system. The method comprises the following steps: acquiring real-time operation data of a target liquid cooling plate; establishing a dynamic thermal resistance network model, and calculating a current thermal resistance value; refrigeration demand parameters are obtained, and a demand weighted thermal resistance value is generated in combination with the current thermal resistance value; thermal resistance deviation is obtained based on the demand weighted thermal resistance value, and the opening degree of a cooling liquid flow valve in the heat exchange system is dynamically adjusted through a fuzzy PID controller; the PID parameters are updated through a preset optimization algorithm, and the fuzzy PID controller is optimized; according to the automatic identification control method and system based on heat dissipation of the liquid cooling plate in the heat exchange system, real-time dynamic adjustment of the flow of the cooling liquid is achieved by establishing the dynamic thermal resistance network model and combining fuzzy PID control, the problems that a traditional method lags in response and is insufficient in control precision are solved, and the control efficiency is improved. The method has the effects of improving the dynamic response speed, improving the control precision and optimizing the energy efficiency.

The invention relates to the technical field of chemical safety and intelligent control, in particular to an explosion-proof intelligent temperature control method and system for a hydrogen peroxide storage tank based on multi-modal monitoring, and the method comprises the steps: collecting multi-dimensional data such as temperature, pressure and H2O2 concentration through a sensor array, carrying out the Kalman filtering and wavelet transform denoising, recognizing local abnormal points through an improved WMDS-DBSCAN algorithm, and obtaining the explosion-proof intelligent temperature control of the hydrogen peroxide storage tank based on the WMDS-DBSCAN algorithm. Predicting a hot spot diffusion trend in combination with an unsteady heat conduction equation and an RF-ADI algorithm; weighted Delaunay triangulation is utilized to construct a self-adaptive monitoring grid, risk area probability distribution is output through an SAM-LSTM-CNN hybrid neural network, and a dynamic amplitude limiting fuzzy PID controller adjusts the opening degree of a nozzle to achieve temperature control. According to the method, multi-modal data and an intelligent algorithm are fused, abnormal accurate detection, risk prediction and self-adaptive temperature control are realized, a closed-loop optimization mechanism is formed, and the operation safety and reliability of the hydrogen peroxide storage tank are effectively improved.

The invention discloses a method and a system for adjusting a tea leaf fixation process and a medium, and aims to realize cooperative regulation and control of enzyme activity and aroma substances in a fixation process. The method comprises the following steps: collecting multi-modal sensing information in a fixation process, and carrying out feature extraction on the multi-modal sensing information to obtain multi-dimensional features; dynamically constructing an LSTM prediction model based on the multi-dimensional features, and outputting an enzyme activity prediction value sequence; the enzyme activity predicted value sequence is input into a fuzzy PID controller for reinforcement learning optimization, a temperature-rotating speed adjusting instruction is generated, and adjusting parameters of the controller are dynamically updated through a reward function of the chlorophyll retention rate and the energy consumption ratio; according to the temperature-rotating speed adjusting instruction, adjusting the hot air temperature of each temperature area of the enzyme deactivation chamber, the rotating speed of the enzyme deactivation cylinder and the axial segmentation wind speed; and collecting fixation end point judgment information, and terminating fixation when a preset condition is met. According to the invention, the problems of unstable quality and overhigh energy consumption caused by parameter solidification in the traditional enzyme deactivation process are solved, and dynamic optimization and accurate control of the enzyme deactivation process are realized.

The invention discloses a dynamic blood glucose monitoring and intelligent pump speed adjusting system and method, and relates to the technical field of biomedical engineering.The dynamic blood glucose monitoring and intelligent pump speed adjusting method comprises the steps that precise monitoring is conducted through a multi-mode sensing module, an enzyme electrode sensor adopts an anti-interference coating, a Raman spectrum dynamic correction algorithm is combined, and motion artifacts and temperature drift are restrained; the metabolic feature fusion calibration module is integrated with a time convolution network, time sequence modeling is carried out on diet, exercise and historical blood glucose data, an individualized metabolic parameter database is constructed, and self-adaptive signal drift compensation is achieved; the self-adaptive pump control module innovatively designs a double-layer fuzzy PID controller, a base layer generates an infusion rate according to a real-time blood glucose state and insulin activity, an optimization layer introduces an LSTM metabolism prediction model, and the slope of an infusion curve is dynamically adjusted in combination with future behavior pre-judgment; in the edge-cloud collaborative architecture, a lightweight TCN model is locally deployed to guarantee real-time control, and a cloud end optimizes a global digital twinborn model through federal learning and generates a multi-dimensional metabolic risk early warning report.

The invention discloses an automatic control method and system for a bias point of a photoelectric modulator, and relates to the field of signal processing, and the method comprises the steps: generating a composite disturbance voltage signal through a digital signal processor; the bias electrode is injected into the photoelectric modulator and used for collecting the optical signal output by the photoelectric modulator and converting the optical signal into an electric signal; extracting a fundamental component amplitude and phase difference data of a second harmonic component, a third harmonic component and a fundamental wave; dynamic characteristic parameters are calculated through spectral analysis, and the mapping relation between the characteristic parameters and the offset of the offset points is established; outputting the offset direction and the offset level of the offset point through a deep learning model; a bias voltage compensation amount is generated through a fuzzy PID (Proportion Integration Differentiation) controller; and adjusting the bias electrode voltage, smoothing the filter, and eliminating high-frequency jitter. The method has the advantages that high-precision and stable bias point adjustment is realized through the composite disturbance signal, real-time spectrum analysis and deep learning optimization decision in combination with fuzzy PID control and a dynamic closed-loop mechanism, and the system performance and stability are remarkably improved.

The invention discloses a dynamic tension control method for a dry-method winding and unwinding system, solves the problems of high overshoot, long coil diameter sudden change adjustment time and large steady-state fluctuation in low-speed operation of the dry-method winding and unwinding system under a high-speed reversing working condition, and belongs to the technical field of composite material equipment development. The method comprises the steps of collecting data of a winding and unwinding system, identifying total rotational inertia and friction torque on line according to the data, obtaining a friction compensation item according to the friction torque, and obtaining a rotational inertia feed-forward item according to the total rotational inertia; the method comprises the following steps of S1, inputting the tension error and the tension error change rate of the winding and unwinding system into a fuzzy PID controller to obtain a PID parameter real-time adjustment amount, updating a PID parameter, and then obtaining a PID feedback control amount at the current moment k by using the PID controller and the tension error, and S3, synthesizing a friction force compensation item, a rotational inertia feed-forward item and the PID feedback control amount into a final control amount of the winding and unwinding system.

The invention discloses an offshore rocket recovery platform attitude stability control method based on particle swarm optimization, and the method comprises the following steps: S1, collecting and preprocessing multi-source attitude data, and generating a time series data set; s2, constructing a fuzzy PID controller, and setting nine three-axis control parameters; s3, performing global optimization by adopting an improved particle swarm algorithm, and outputting an initial parameter solution; s4, introducing a zebra optimization algorithm to carry out local refined optimization; s5, constructing a collaborative optimization architecture, and fusing and outputting optimal control parameters; s6, the optimal parameters are input into a controller, and a servo system is driven to adjust the three-axis attitude; s7, monitoring disturbance amplitude, dynamically triggering a zebra strategy and feeding back the zebra strategy to the particle swarm; and S8, evaluating the control performance, and feeding back iterative optimization if the control performance does not reach the standard. According to the method, the improved particle swarm optimization algorithm and the zebra optimization algorithm are fused, so that self-adaptive optimization and accurate attitude stable control of attitude control parameters of the offshore rocket recovery platform are realized.

The invention discloses an intelligent temperature field regulation and control method and system based on HVPE equipment, and relates to the field of temperature field control, and the method comprises the steps: S1, carrying out the multi-dimensional collection and time-space fusion of multi-source heterogeneous data; s2, temperature field balance degree quantitative evaluation and distributed cooperative control are carried out, the temperature field balance degree is calculated through data collected in the S1, temperature field unbalance judgment and cooperative control of a heater are completed through a six-dimensional fuzzy PID controller and a consistency algorithm, and the uniformity and stability of the temperature field are improved; s3, heat, flow, deposition and pressure four-field coupling dynamic compensation; and S4, dynamic learning optimization based on digital twinning. According to the intelligent temperature field regulation and control method and system based on the HVPE equipment, comprehensive improvement of temperature field control precision, complex working condition adaptability and equipment operation and maintenance efficiency is achieved based on multi-source heterogeneous data acquisition, temperature field balance control, four-field coupling compensation and digital twinning optimization.

The invention provides a method for realizing dynamic balance of source water minerals based on ion coordinated regulation and control, and belongs to the technical field of water treatment. According to the method, multi-parameter coupling regulation and control are achieved by conducting split-flow pretreatment on source water and building a dynamic synergistic coefficient model, the source water is separated to prepare calcium-magnesium compensation liquid, the ion concentration and the water temperature are monitored in real time, and a synergistic coefficient model fusing ion activity factors and the temperature effect is built; a fuzzy PID controller is used for dynamically analyzing pH fluctuation and collaborative deviation to adjust the injection proportion of compensation liquid, and precise mineralization is achieved by combining turbulence mixing intensity optimization; a closed-loop feedback mechanism and a high-frequency liquid supplementing technology are adopted to quickly correct ion concentration deviation, and the dissolution activity of compensation liquid is differentially regulated and controlled through a reverse temperature difference strategy so as to stabilize pH. According to the method, the ion synergistic effect, dynamic algorithm control and dissolution kinetics optimization are combined, the response speed and balance precision of water quality regulation are improved, and the method is suitable for precise mineral regulation and quality optimization of high-quality drinking water.

The invention relates to the technical field of detection of toner cartridge powder, and discloses a method and a system for improving the uniformity of toner cartridge powder, which are used for continuously sampling powder flow to obtain a real-time weight distribution matrix. And when abnormal flow is detected, noise is eliminated, processed data are input into a fuzzy PID controller, and feeding parameters are dynamically adjusted. Meanwhile, powder is promoted to be uniformly dispersed in combination with a vibration frequency modulation technology, and a weight change trend is predicted by utilizing a long-short-term memory network algorithm. In addition, the method further comprises an anomaly detection and fault diagnosis mechanism, control parameters are continuously adjusted through closed-loop optimization, and finally a batch quality tracing system is established. By means of the method, the precision and consistency of toner cartridge powder conveying can be effectively improved, and intelligent control and quality management in the production process are achieved.

The invention relates to the technical field of ship power and propulsion control. The invention provides a multi-source cooperative propulsion control method and system based on hybrid power and a straight wing steering oar. The method comprises the following steps: collecting ship motion state parameters and environment parameters in real time; constructing a multi-objective joint optimization model, and solving an optimal power distribution proportion and an optimal thrust vector under the current working condition by adopting a dynamic programming algorithm; based on the optimal power distribution proportion, a fuzzy PID controller is adopted to dynamically adjust the torque coupling ratio of the diesel engine and the motor; according to the optimal thrust vector calculation result, vector synthesis is carried out on the propulsive force and the steering torque; and predicting the motion state of the ship based on an extended Kalman filter, and correcting the weight coefficient of the multi-target joint optimization model on line in combination with the change rate of the channel boundary distance. The problem that adaptability to complex working conditions is insufficient due to the fact that a traditional control strategy does not fully fuse ship motion states and environment parameters is solved.

The invention discloses an integrated circuit source measurement unit control method for improving a raccoon algorithm and optimizing fuzzy PID. The method comprises the steps that an output voltage control system of an SMU is set up; acquiring output end voltage data of the SMU system in real time; calculating a voltage error and a voltage error change rate; a fuzzy inference rule base is constructed, fuzzy controller parameters are dynamically adjusted based on the fuzzy rule base according to the voltage deviation value and the voltage error change rate, and then PID parameters are dynamically adjusted; a control signal is generated according to the set PID parameter, and the output voltage of the SMU is adjusted; and S4, optimizing the fuzzy PID voltage controller obtained in the step S4 by adopting an improved raccoon algorithm, selecting a decision variable as a parameter of a fuzzy controller, and assigning the optimized parameter to the fuzzy PID voltage controller to realize control on the output voltage of the SMU. According to the invention, the improved raccoon optimization algorithm and the fuzzy PID controller are combined and applied to the integrated circuit source measurement unit, so that the control performance of the SMU system is improved.

The invention provides an airflow pulsation suppression method and system for a liquid-driven compressor, and the method comprises the steps: obtaining a pressure pulsation frequency spectrum and flow data of an outlet pipeline of the liquid-driven compressor; generating a dominant frequency offset rule based on the pressure pulsation spectrum and the flow data; based on the main frequency offset rule and the main peak frequency of the pressure pulsation frequency spectrum, a target position adjusting signal is generated in combination with a fuzzy PID controller; the actual position of a movable baffle arranged in a resonant cavity of the hydraulic drive compressor is monitored in real time, and feedback compensation is conducted on the target position adjusting signal based on the actual position; and the position of the movable baffle is adjusted based on the compensated target position adjusting signal, so that the through-flow area of the resonant cavity is changed, and airflow pulsation of the outlet pipeline is restrained. According to the invention, the airflow pulsation suppression effect of the hydraulic drive compressor under variable working conditions is improved.

The invention provides an argon flow and micro-positive pressure linkage control method for an electroslag furnace. The method comprises the steps that the oxygen content and micro-positive pressure signals in the furnace are collected; the future furnace condition is predicted through the deep belief network model; optimizing initial parameters of the fuzzy PID controller in an off-line manner by using a particle swarm algorithm; on the basis of the real-time signal and the prediction result, adaptively adjusting controller parameters on line; and finally, an argon flow and dust removal valve opening control instruction is output in a linkage mode. According to the method, future furnace conditions are predicted through the deep belief network model, the control advancement is realized, and the problem of large lag of the system is solved; offline parameter optimization is carried out on the fuzzy PID controller through a particle swarm algorithm, and excellent initial performance adapting to different working conditions is provided for the fuzzy PID controller; the parameters of the controller are adaptively adjusted through online fuzzy reasoning, so that the system has robustness for coping with a dynamic process; finally, accurate and stable linkage control of the oxygen content in the furnace and the micro-positive pressure is achieved through linkage calculation of the argon flow and a dust removal valve opening instruction.

The invention discloses a permanent magnet synchronous motor parameter optimization method based on an improved moth flame particle swarm algorithm. In order to solve the problems that a traditional PID controller is difficult in parameter setting, poor in adaptability, insufficient in control precision and the like under complex working conditions, in the strategy, an MFPSO algorithm fuses a particle swarm optimization (PSO) algorithm and a moth flame optimization (MFO) algorithm. An adaptive inertia weight and Gaussian mutation strategy is introduced, so that particles can focus on local fine search, and the speed of convergence to an optimal solution is accelerated. The optimization capacity of the algorithm in different stages is enhanced by adopting a nonlinear acceleration coefficient, and local optimum is effectively avoided. A grouping evolution mechanism is designed to promote intra-group information sharing and inter-group competition, the population diversity is enriched, and the ability of the algorithm to jump out of a local optimal solution is further improved. The fuzzy PID controller based on the MFPSO algorithm optimization parameters can better meet the requirements of high-performance control of permanent magnet synchronous motors in different fields, and has application prospects and economic values.

The invention relates to the technical field of wireless charging, in particular to a self-adaptive wireless power transmission system and a receiver free positioning method thereof. The system is characterized in that a transmitting end comprises an inverter circuit, a transmitting end compensation network, a compensation network input detection circuit and an array transmitter, and the array transmitter comprises seven transmitting coils; the receiving end comprises a receiving coil, a receiving end compensation network and a load voltage detection circuit; the control system comprises a position prediction module and a fuzzy PID controller. The position prediction module is used for predicting the spatial position of the receiving coil by measuring a mutual inductance value between the transmitting coil and the receiving coil based on a neural network optimized by a seagull algorithm; and the fuzzy PID controller is used for acquiring the spatial position of the receiving coil, adjusting the excitation mode of the transmitting coil and the phase of an input signal of the inverter circuit, and optimizing the magnetic field distribution to compensate the offset influence. According to the invention, high transmission efficiency can still be maintained when the receiving coil deviates to a certain extent, and the anti-deviation capability is remarkably improved.

The invention discloses a cordyceps sinensis intelligent bionic cultivation control system and method based on the Internet of Things, and the method comprises the steps: collecting the temperature and humidity, gas concentration, illumination intensity and larva behavior data of a cordyceps sinensis matrix through a sensor network, and carrying out the fusion through an edge calculation gateway, and generating a dynamic environment map; constructing a plateau ecological digital twinborn model based on the dynamic environment map in combination with historical meteorological data and a host-strain interaction rule, and generating a staged control time sequence; based on a staged control time sequence, temperature and humidity coupling compensation is carried out through a feedforward-feedback composite algorithm, and actuator linkage is adjusted through fuzzy PID; aI vision is used for identifying a larva infection window period and accurate spraying is carried out, and hypha infection is monitored in combination with a near infrared spectrum to dynamically adjust the CO2 concentration; and constructing an LSTM (Long Short Term Memory) model to predict the growth risk in combination with a dynamic environment map and insect body monitoring data, and actively intervening in an abnormal environment. According to the invention, high-precision, dynamic and intelligent regulation and control of the growth environment of cordyceps sinensis are realized.

The invention discloses an intelligent control method for precise grinding of a robot, and the method comprises the steps: obtaining the information of a to-be-ground workpiece and initial grinding parameters, and the initial grinding parameters comprise the load gravity of the tail end of the robot; generating a target contact force based on the to-be-ground workpiece information and the initial grinding parameters; constructing a gravity compensation model through preset coordinate parameters based on the load gravity at the tail end of the robot; in the grinding process, grinding force data are collected in real time; on the basis of the grinding force data, actual contact force is obtained through a gravity compensation model; comparing the actual contact force with the target contact force to generate a contact force deviation and a deviation change rate; based on the contact force deviation and the deviation change rate, a force-position hybrid control instruction is output through a fuzzy PID controller; and on the basis of the force-position hybrid control instruction, control adjustment parameters of the robot are generated. By forming a complete intelligent control closed loop, constant-force grinding can be achieved, and the problems of uneven surface roughness, excessive grinding and the like are effectively solved.

The invention discloses a new energy automobile electric compressor preheating structure and a control method, and relates to the technical field of new energy automobile heat management. The method comprises the three steps of heat source collaborative recovery, heat demand dynamic distribution and self-starting collaborative execution, specifically, motor stator waste heat and compression refrigerant waste heat are recovered through a heat conduction fin array and a spiral flow channel, and a shared heat conduction medium is guided in; based on a fuzzy PID controller, a heat flow guide valve is dynamically adjusted to distribute heat flow according to the lubricating oil way temperature, the suction superheat degree and the shell temperature; the generator is triggered to be rapidly heated in a locked-rotor mode at the ultralow temperature, the preheating requirement is pre-judged in combination with a heat attenuation model, the structure comprises a temperature sensor set, a three-way heat flow guide valve and an embedded MCU processor, efficient waste heat utilization is achieved, external energy consumption is not needed, preheating energy consumption is effectively reduced, and the low-temperature starting performance and operation stability of the compressor are remarkably improved.

The invention provides an AGV safety navigation and obstacle avoidance system based on an intelligent storage environment and a control method. The method comprises the following steps: acquiring three-dimensional point data of an intelligent storage environment through a laser radar, and generating a three-dimensional grid chart after processing and removing interference points; and acquiring the distance between the obstacle and the AGV by using a millimeter wave radar, integrating the distance with the three-dimensional grid diagram, updating the space relationship between the obstacle and the AGV by combining the position of the AGV, and outputting a dynamic environment state quantity with a timestamp. The dynamic environment state quantity is input into a reinforcement learning path planner, a goods shelf dense environment is recognized, and a collision-free steering angle and speed instruction is generated; and the steering flexibility and the braking force of the AGV are dynamically adjusted according to an instruction through a fuzzy PID controller, so that safe navigation and obstacle avoidance in a goods shelf dense environment are realized. According to the invention, the safe navigation and obstacle avoidance capabilities of the AGV in an environment with dense intelligent storage shelves are improved.

The invention relates to a distributed power supply-based grid-connected management optimization method and system, and the method comprises the following steps: S1, obtaining various distributed power supply operation data, power grid side operation parameters and external environment data, and carrying out the partitioning storage of the corresponding distributed power supply data; s2, predicting the output of each distributed power supply by using an output prediction model according to the real-time operation data and the external environment data of each distributed power supply; s3, predicting a load curve by combining load mode recognition and XGBoost regression on the basis of the power grid side operation parameters; s4, based on the output and load curve prediction result of each distributed power supply, adopting hierarchical multi-objective optimization scheduling to obtain an optimal scheduling scheme; and S5, adjusting the power of each distributed power supply based on a fuzzy PID controller according to the optimal scheduling scheme, and dynamically tracking a scheduling instruction. According to the invention, dynamic, optimized and safe management of grid-connected operation of the distributed power supply is realized.

The invention discloses an automatic temperature detection method based on dynamic feedback and an intelligent cooling control system, a plurality of temperature sensors are arranged in an array mode, a fuzzy PID controller outputs PID parameters according to a fuzzy PID control algorithm, the PID parameters can be dynamically adjusted and adapt to dynamic environment fluctuation, and the PID parameter output accuracy is improved, so that the decision accuracy is improved; and therefore, a graded refrigeration strategy is accurately implemented, the refrigeration and heat dissipation effects are ensured, and energy consumption is reduced.

The invention relates to the technical field of ventilation equipment control, and discloses a ventilation clerestory self-adaptive adjustment control method and system according to environment change, and the method comprises the steps: deploying a distributed environment sensor array in a ventilation clerestory and inside and outside the ventilation clerestory, collecting time sequence data and equipment operation state data, and obtaining initial data; an abnormal data cleaning algorithm based on wavelet transformation is adopted to process initial data collected by a sensor, an environment parameter coupling degree matrix is constructed, and the correlation degree between parameters in the data subjected to abnormal data cleaning is analyzed; extracting global features from the cleaned and analyzed initial data, and outputting an environment prediction result; making a decision in the continuous action space to generate an optimal control instruction set; a fuzzy PID controller is adopted to control the ventilation clerestory according to the control instruction, the running state and environmental parameters of the ventilation clerestory are monitored in real time, and when abnormity occurs, a safety protection mechanism is triggered immediately; efficient ventilation is achieved, and the indoor environment requirement is accurately met.