542 results about "PID controller" patented technology

The invention relates to the technical field of environmental engineering water treatment automatic control, and discloses a landfill leachate treatment control method based on cooperative control. The method comprises the following steps: acquiring real-time monitored water quality parameter data streams including a pretreatment stage pH value, a main treatment stage COD concentration, a deep treatment stage membrane pressure difference and the like in a landfill leachate treatment system, inputting the data streams into a cooperative control framework, and dynamically correcting PID controller parameters through a nonlinear gain function to generate a primary adjustment instruction; evaluating and generating a strategy optimization instruction based on the reinforcement learning strategy network; inputting the two into a grey prediction model and outputting a cooperative control signal containing a feedforward compensation amount; and finally, dynamically adjusting the coagulant dosage, the aeration intensity and the working pressure of the membrane component according to the signal to form a closed-loop control loop. The method can master the water quality change in real time, accurately regulate and control the treatment process, improve the stability and reliability of the treatment system, and effectively improve the landfill leachate treatment effect.

The present invention relates to the fields of PID control and Kalman filtering, and disclosed is an improved PID control method based on Kalman filtering. The present invention comprises: in the process of acquiring a target value of an expected signal, taking the difference between the target value and a current feedback quantity of a controlled object to obtain an error value, acquiring an output of PID from the error value, applying the output of PID to the controlled object to obtain a noisy output signal, then, after Kalman filtering, feeding the output back to PID, continuously iterating to make the feedback quantity approach the target value, and finally obtaining a stable output signal. Variable-speed integration and integral separation algorithms are added to an integral term of PID to change an integration speed on the basis of a system deviation, and an incomplete differential algorithm and a low-pass filter are added to a differential term of PID to prevent high-frequency interference. According to the present invention, the optimal estimation of a system state is obtained by means of prediction of a current state and updating of observation data, thereby reducing the influence of measurement errors and noise, and improving the performance and stability of a PID controller.

The invention relates to the technical field of tunnel and underground engineering construction, and discloses an intelligent closed-loop control system and method for a tunnel construction section contour, and the method comprises the steps: collecting geological-geometric data through the fusion of a three-dimensional laser scanner and a geological radar before blasting; dynamically generating a theoretical blasting contour line and adaptive blasting parameters through a convolutional neural network; iMU positioning and a PID controller are combined to realize millimeter-level accurate control of the drill boom; generating a three-dimensional deviation field by adopting an iterative point cloud registration algorithm after blasting; when the deviation exceeds a threshold value, triggering incremental learning to optimize model parameters; and finally, closed-loop iteration is formed. Through multi-source data fusion, contour and parameter intelligent generation, precise execution control, three-dimensional deviation field feedback and an incremental learning mechanism, a complete intelligent closed-loop control system is constructed, the limitation of traditional blasting design depending on experience is broken through, and the precision, efficiency and economic benefits of tunnel construction are remarkably improved.

The invention relates to the technical field of fuel cells, in particular to a method and system for accurately controlling the hydrogen stoichiometric ratio of a fuel cell, and the method comprises the steps: firstly, obtaining a quantitative anode health state value through a fusion calculation model by collecting load current, anode inlet and outlet pressure, temperature, high-frequency resistance and other multi-source signals in real time; a feed-forward model based on a load current change rate predicts sudden change of hydrogen demand, and an optimal hydrogen flow instruction is jointly generated in combination with output of a PID controller which adaptively adjusts parameters according to a health state value. According to the method, the integrated diagnosis parameter, namely the anode health state value, is created, so that the internal state of the fuel cell can be accurately perceived and prospectively judged. Through deep fusion of multi-source heterogeneous information such as high-frequency resistance, anode pressure difference, current and temperature, a comprehensive index capable of comprehensively and quantitatively reflecting anode water content, gas concentration and runner smoothness is generated.

The invention provides a satellite weak and small target on-orbit observation system and method based on intelligent closed-loop feedback, and the system comprises a detection module which carries out the image enhancement and time sequence consistency enhancement of an infrared image, obtains an enhancement feature, and obtains a candidate target set based on the enhancement feature; the tracking module is used for carrying out target matching in the search area; when the matching succeeds, the candidate position is used as an observation value, and the observation value is input into a Kalman filter to obtain a target state vector; when the matching fails, taking a prediction state of the Kalman filter as a target state vector, expanding a search window by taking a prediction position as a center, and executing re-identification; the control module is used for mapping the target state vector into an attitude error and generating a control instruction by adopting a single-neuron self-adaptive PID (Proportion Integration Differentiation) controller; and the closed-loop scheduling module is used for dynamically adjusting operation parameters of at least one module according to the execution error and the detection confidence coefficient. According to the invention, the continuous tracking precision and attitude control stability of the weak and small target are improved.

The invention belongs to the field of automatic control of hydroelectric generating sets, and particularly discloses a primary frequency modulation optimization control method and system based on power opening nonlinear prediction.The method comprises the steps that frequency deviation is converted into primary frequency modulation power variable quantity, the power variable quantity and a basic power set point of a set are added, and a dynamic power target is obtained; integrating the power deviation signal to obtain a power integration opening reference instruction; taking the dynamic power target and the unit water head as input of a feed-forward model, and obtaining a feed-forward dominant opening instruction; the opening degree deviation value is input into a PID controller, and a feedback opening degree correction instruction is generated; and a guide vane opening given value is obtained based on the feed-forward dominant opening instruction and the feedback opening correction instruction and serves as a given signal of a guide vane position control loop. According to the invention, through nonlinear prediction and a unique feedback structure, high self-adaption to the working condition change of the unit is realized, and the rapidity, consistency and robustness of the primary frequency modulation response of the unit are remarkably improved.

The invention provides an efficiency optimization control method of a permanent magnet synchronous motor and related equipment. The method comprises the following steps: acquiring an output current of an inverter; constructing an inverter loss model based on the output current of the inverter and the inverter loss coefficient; constructing a total loss model based on the electromagnetic loss model, the inverter loss model and an equivalent conversion method; constructing a current population by taking the plurality of d-axis current values as individuals; and performing optimization solution based on the total loss model, the current population, a PID search algorithm and an artemisinin optimization algorithm to obtain a global optimal solution and control the permanent magnet synchronous motor. According to the scheme, the driver loss is added into the total loss model, and efficiency optimization can be carried out on the whole motor driving system; in order to solve the problem that a traditional method is not suitable for an IPMSM, a PID search algorithm and an artemisinin optimization algorithm are combined, parameter search is carried out on a motor efficiency optimal point by simulating an incremental PID controller adjusting mechanism, a global optimal solution is obtained, and therefore optimal control over the click efficiency is achieved.

The utility model provides an oxygen injection control system based on dynamic environment variable compensation, and aims to solve the non-linear problem of oxygen content control under environment variable disturbance. Comprising a main oxygen spraying pipeline, an oxygen supplementing pipeline connected with the main oxygen spraying pipeline in parallel, a PLC (Programmable Logic Controller) and a PID (Proportion Integration Differentiation) controller which are respectively connected with the main oxygen spraying pipeline and the oxygen supplementing pipeline and are used for controlling the main oxygen spraying pipeline and the oxygen supplementing pipeline, and an oxygen content measuring pipeline which is in communication connection with the PID controller, the oxygen control system selectively controls the main oxygen spraying pipeline and / or the oxygen supplementing pipeline to be opened or closed.

The invention relates to the field of ventilation control, in particular to an intelligent ventilation control method and system based on an intelligent laboratory, and the method comprises the steps: obtaining a to-be-controlled air volume sequence and a multi-dimensional to-be-controlled turbulence characteristic sequence of any region in a preset sampling period, and calculating a turbulence compensation coefficient of a target dimension, the turbulence contribution degree of any region in the target dimension is calculated; calculating a comprehensive product, calculating a first difference value between the air volume at the marked moment and the comprehensive product, and taking a mean value of the first difference values of all dimensions as an air volume correction value of any region at the marked moment; and taking a result of weighted summation of the air volume correction values of all the areas as comprehensive air volume, and inputting the comprehensive air volume into a laboratory PID controller to complete ventilation control. According to the technical scheme, the precision and timeliness of the ventilation control result can be improved.

The invention relates to the technical field of lasers, in particular to a temperature self-adjusting method and device for a DFB laser with a TEC, and the method comprises the steps: collecting the temperature of the DFB laser at each moment, and the voltage and current of a TEC circuit at each moment; determining a proportional gain compensation item of the PID controller in each parameter adjustment period; analyzing the difference between the temperature change trend of the DFB laser in the local time period in each parameter adjustment period and the overall temperature change trend, and determining an integral gain compensation item of a PID controller in each parameter adjustment period; based on the fluctuation of the instantaneous frequency of the voltage and the current in the TEC circuit in each parameter adjustment period, obtaining a differential gain compensation item of a PID controller in each parameter adjustment period; and adjusting parameters of the PID controller are respectively corrected by using the proportional gain compensation item, the integral gain compensation item and the differential gain compensation item so as to adjust the temperature of the DFB laser. Therefore, the stability of temperature adjustment of the DFB laser is improved.

The invention discloses a GPS oscillator taming system and method based on PID parameter adaptive adjustment, and the system comprises a forgetting factor dynamic updating module which is used for dynamically updating a forgetting factor with the variance of the frequency error of VC-TCXO as a negative index; the system identification module is used for estimating ARX model parameters of the VC-TCXO by adopting a recursive least square algorithm with the updated forgetting factor; the model parameter mapping module is used for mapping the estimated ARX model parameters to obtain PID control parameters; the incremental PID controller is used for calculating a frequency control word increment based on the frequency error; the digital-to-analog converter is used for calculating according to the frequency control word increment to obtain a frequency control word and converting the frequency control word into analog voltage; and the VC-TCXO is used for obtaining the frequency of the GPS reference signal based on the analog voltage corresponding to the frequency control word so as to complete frequency taming. The method is high in calculation efficiency and robustness, and can adapt to the dynamic change and external disturbance of the controlled object in real time.

The embodiment of the invention discloses a pressure control method and system for a once-through steam generator of a nuclear reactor, and relates to the technical field of nuclear power. Determining power deviation according to the operation power and the secondary circuit load; according to the power deviation, the rated power corresponding to the nuclear reactor and the rated feed water flow corresponding to the once-through steam generator in the nuclear reactor, pressure regulation information is determined; and adjusting the pressure of the once-through steam generator according to the pressure adjusting information. According to the embodiment of the invention, a PID controller is not needed in the process of determining the pressure regulation information, but the pressure regulation information determined based on the power deviation directly acts on the feed water flow regulation valve, so that rapid and accurate OTSG pressure control can be realized.

The invention relates to the technical field of diaphragm pump aging test, and discloses a two-parameter intelligent closed-loop diaphragm pump aging test system and method. According to the method, a temperature spectrum and a vibration spectrum are obtained through fast Fourier transform, a frequency domain coherence coefficient is calculated to identify temperature-vibration coupling characteristics, a resonance frequency band and a drift trend thereof are identified in real time by adopting a spectrum peak tracking algorithm, and a multi-objective optimization function considering aging acceleration efficiency and resonance risk is constructed. And solving the optimal temperature stress amplitude and vibration stress frequency by using a particle swarm algorithm, generating a stress loading instruction avoiding a resonance area through a self-adaptive PID controller, and dynamically updating model parameters based on a closed-loop feedback mechanism. According to the invention, the problem of resonance effect amplification caused by traditional fixed frequency stress loading is solved, and refined adaptive stress control is realized.

The present invention relates to an automatic optimization search calculation method for a converted heat supply load based on a load conversion coefficient method. The automatic optimization search calculation method comprises: acquiring data on the basis of a unit design heat supply working condition diagram, and fitting a relationship formula; on the basis of the relationship formula, calculating the difference in the power-generation power of a heat supply extraction steam flow rate at a specific main steam flow rate; on the basis of the difference, calculating a converted heat supply extraction steam load; designing an automatic optimization search loop for the converted heat supply load, determining target loads on the basis of requirements, and setting an optimal comprehensive valve position under different target loads; and using a PID controller to adjust an actual valve position, so as to obtain a correction coefficient of the converted heat supply load for when the actual valve position is the same as the optimal comprehensive valve position, so as to obtain an optimal converted heat supply load. The present invention solves the problems of the calculation of a converted heat supply load under a heat supply working condition of a heat supply unit being inaccurate and it not being possible to adapt to a full-load working condition, further solves the problem of coordinated control of the heat supply working condition being poor, and improves the safe and stable operation of the heat supply unit.

The invention provides a dynamic optimization method and system for a running path of a stacking robot, and relates to the technical field of path optimization, and the method comprises the steps: obtaining a dynamic semantic map carrying a goods allocation priority and a path passing level, and real-time running data containing a real-time load and a multi-task sequence, analyzing to obtain an association relationship among the operation energy consumption, the path steering and the real-time load; further, an improved genetic algorithm is adopted, multi-objective optimization is carried out in combination with goods allocation priorities and path passing levels, and a path optimal solution set is generated; then, taking the path optimal solution set as input, constructing a moving track model by using a time elastic band algorithm, and performing online re-planning in combination with dynamic updating to obtain a reference track and a speed profile; and finally, track control parameters are tracked and generated through the PID controller so as to drive the stacking robot to execute tasks. The operation efficiency, the stability and the execution precision of the stacking robot in the dynamic environment are comprehensively optimized.

The invention aims to provide a lithium iron phosphate battery pack parallel current sharing control method and system, and aims to solve the problem of non-uniform current distribution caused by dynamic change of internal resistance of lithium iron phosphate batteries in the prior art, and the technical problems that a traditional PI controller is slow in response speed, and current impact and voltage fluctuation are easily generated during load sudden change. According to the technical scheme provided by the invention, by establishing a virtual impedance adaptive adjustment mechanism based on depth model predictive control and combining with the adaptive PID controller optimized by reinforcement learning, accurate balance control on the current of each parallel battery pack is realized, and meanwhile, the method has fault detection and reconstruction capabilities and ensures stable operation of the system under various working conditions.

The invention discloses a wind turbine generator adaptive load shedding optimization control method and related equipment. The method comprises the steps of generating three-dimensional turbulent wind field data based on structure parameters and standard wind regime parameters of a wind turbine generator; carrying out aeroelastic coupling simulation based on the three-dimensional turbulent wind field data to obtain a load time sequence of each part under different working conditions, and determining a key part and a dominant load characteristic of the key part; taking the load time sequence of the key part and the reverse slope of the material as input, and calculating an equivalent fatigue load of the key part by using a rain flow counting method; according to the equivalent fatigue load, sensitivity of the key part to wind speed and turbulence intensity is analyzed, a sensitivity result of the key part is obtained, a sensitivity weight in a target function is set according to the sensitivity result, and a sparrow search algorithm is adopted to carry out parameter optimization on a PID controller; and the optimized PID controller is utilized to realize self-adaptive load shedding of the wind turbine generator under the complex working condition. According to the invention, load reduction optimization can be effectively realized.

The invention belongs to the technical field of process optimization control, and particularly relates to a machining process optimization control method for a supporting shaft of a drive axle of a mining truck. The problems that existing machining depends on empirical parameters, quality fluctuation is large, and traditional PID control cannot dynamically adapt to working conditions are solved. The method comprises the following steps: collecting control parameters such as cutting speed and feeding amount and corresponding supporting shaft mass fractions, and constructing a sample data set; preprocessing the data to eliminate abnormal values and complement missing values; calculating influence weights of the parameters on quality, distinguishing key and non-key parameters, and identifying sensitive intervals of the key parameters; solving an optimal parameter combination by using a non-dominated sorting genetic algorithm in combination with the sensitive interval; and the optimal parameter is used as a PID set value, and the improved PID controller dynamic setting fused with the real-time quality deviation is designed. According to the method, experience dependence is replaced by data driving, the machining quality stability and consistency are improved, and the method adapts to complex working conditions.

The invention discloses a self-coupling PID (proportion integration differentiation) flight control method of a rudder-controlled transverse-row type rotor unmanned aerial vehicle based on dynamic multi-dimensional heterogeneous fuzzy logic, and belongs to the technical field of flight control of rudder-controlled transverse-row type rotor unmanned aerial vehicles. A flight control system architecture of the self-coupling PID flight control method is composed of three core modules: (1) a dynamic multi-dimensional fuzzy logic coupling PID controller (DMHFL-SCPID); (2) control instruction distribution; and (3) a six-degree-of-freedom dynamical model of the rudder-controlled transverse rotorcraft. According to the control algorithm, input and output dynamic parameters of a system are analyzed in real time, and four-dimensional flight control quantities (roll, pitch, yaw and height instructions) are generated. A control distribution strategy based on the aerodynamic characteristics of the rotor converts the instructions into actuating quantity of an actuating mechanism, and flight attitude adjustment is realized by changing aerodynamic load distribution of a rotor system, so that the unmanned aerial vehicle is guided to realize accurate tracking along a predetermined flight path.

The invention belongs to the technical field of intelligent control, and particularly relates to a wire drawing machine production temperature control method. The method comprises the following steps: acquiring multi-temperature-zone temperature data of the wire drawing machine and determining a temperature control set range; coupling interference in the temperature zones is processed through an improved neural network decoupling algorithm, and independent controlled temperature values of all the temperature zones are obtained; an orthogonal mode PID controller is constructed, a unique mapping relation between PID three parameters and an orthogonal mode is established, a single-mode core characteristic quantity is extracted through adaptive orthogonal mode decomposition, and three-parameter non-coupling adaptive setting is completed; and a sparrow search algorithm of an improved elite retention variation mechanism is adopted, global optimization is carried out on control parameters to obtain an optimal parameter set, and real-time temperature control of the temperature zone is achieved. The problems of multi-temperature-zone coupling interference and PID parameter setting difficulty of the wire drawing machine are effectively solved, the temperature control precision, the production stability and the product forming quality are remarkably improved, and the high-precision temperature control requirement of high-end wire drawing production is met.

The invention discloses a PID (Proportion Integration Differentiation) tracking control method based on error perception nonlinear gain, which is used for high-precision tracking control of an MIMO (Multiple Input Multiple Output) nonlinear system. Comprising the following steps: 1) constructing an adaptive gain by using current error information, historical error information and prediction error information; 2) realizing intrinsic integral saturation resistance through nonlinear integral design; and 3) complete autonomous operation can be realized without accurate system dynamics priori knowledge or manual adjustment. According to the method, the nonlinear compensation capability and the robust adaptive performance are enhanced while the structural simplicity of the PID controller is kept. Through rigorous Lyapunov analysis, the stability of the method to a non-linear system in a general form is verified, and the method shows excellent performance in both adjustment and time-varying reference tracking scenes. The method can be widely applied to the fields of linear motor servo systems, sea surface ship control, unmanned vehicle dynamics control and the like needing high-precision tracking control.

The invention discloses an unmanned aerial vehicle cluster navigation method and device based on multi-agent reinforcement learning, and a medium, which are applied to an unmanned aerial vehicle cluster composed of a plurality of unmanned aerial vehicles, and the method comprises the following steps: obtaining an observation vector of each unmanned aerial vehicle in the unmanned aerial vehicle cluster, the observation vector comprises the self-state of the unmanned aerial vehicle and the estimated value of the relative position of the teammate unmanned aerial vehicle; wherein the self-state comprises the current position and speed output by the airborne vision inertial odometer; inputting the observation vector into a pre-trained strategy network, and outputting an expected acceleration vector of the unmanned aerial vehicle in a body coordinate system; and in response to the expected acceleration vector, the airborne PID controller drives the unmanned aerial vehicles, so that the unmanned aerial vehicle cluster executes a flight task of mutual obstacle avoidance and target arrival in a distributed manner under the conditions of inter-machine communication and no dependence on instant relative positioning information.

This invention relates to a PID closed-loop fast allocation control method based on virtual measurement, belonging to the field of automatic control technology. The method involves: receiving a general command from the upper level as the setpoint for PID allocation; the controlled variable is the final value of the sum of the output values ​​of all allocated devices after filtering; and adaptively allocating the proportional gain of the PID controller. K P and integration time T i The value is the number of devices put into automatic operation. A , Lock-up BI , Lockdown BD The calculation function value of the set is used to ensure consistent speed, stability, and quality of the allocation control under different conditions of increasing or decreasing input and lockout. The allocation PID control output is expressed as a percentage. After each device receives the control output value of the allocation PID, it is multiplied by its respective allocated rated capacity value to convert it into an engineering quantity value. Then, a manually set bias value is added to obtain the final control output value of each device, achieving flexible increase or decrease while meeting the overall command requirements. This invention has the advantages of simple, fast, flexible, and reliable allocation control.

The invention discloses a boiler flue gas temperature compound control method and system based on multiple regression, and belongs to the field of thermal power generation boiler control. The method adopts a feedforward-feedback composite control structure, and comprises the following steps: generating a feedforward control signal through a pre-trained multiple regression model; meanwhile, based on the deviation between the actual smoke temperature and the target smoke temperature, a feedback control signal is generated through a PID controller; and combining the feedforward control signal with the feedback control signal to generate a final control instruction for coordinating and controlling a first flue gas baffle and a second flue gas baffle on parallel flues at an outlet of a boiler economizer. The baffles are controlled in a coordinated mode, the flue gas flow proportion of different heat exchange degrees is changed, and then the temperature of the mixed flue gas is accurately controlled. The prediction capability of the model and the rectification capability of PID are combined, the response speed and precision of the control system are improved, and the robustness of the system under the variable fuel ratio working condition is enhanced.

The application relates to the technical field of vehicle simulation test control, in particular to a vehicle ACC simulation test system based on traffic flow characteristics. The system comprises a traffic flow simulation module and a sensor simulation module, which are used for acquiring a self-vehicle simulation speed of a simulation vehicle and a front-vehicle simulation speed in the same lane; an ACC control module is divided into a variation analysis unit, a proportional regulation unit and a PID control unit; the variation analysis unit is used for acquiring high-frequency complexity and obtaining a cooperative variation degree at each collection time; the proportional regulation unit is used for adjusting preset proportional parameters of a PID controller according to a variation trend of the cooperative variation degree; and the PID control unit is used for controlling and adjusting the speed of the simulation vehicle in the vehicle ACC simulation test. The application improves the control precision of the vehicle in the simulation test process.

The invention relates to a shoreline identification and course keeping method, system and device based on vision. The method comprises the following steps: acquiring an image of a water area in front of a ship in real time through a shipborne camera; processing the image by using an improved Spatial CNN model to extract a left shoreline and a right shoreline, fitting the left shoreline and the right shoreline into straight lines, and calculating an intersection point of the two fitted straight lines; taking the intersection point as a far-end piloting target point, and calculating a heading adjustment value according to the field angle of the shipborne camera and the position relation of the ship relative to the piloting target point; and inputting the heading adjustment value into a PID controller for PID adjustment so as to generate a steering engine control instruction, and driving the ship to automatically adjust the heading according to the steering engine control instruction. The method is suitable for a complex river environment without map and support of positioning equipment, and autonomous navigation and course control of the ship are realized.

The application belongs to the technical field of temperature control, and discloses a two-stage precise temperature control method, system and device, the method comprising: using a PSO algorithm to solve a BP neural network to optimize the weight and threshold of the BP neural network; using the optimized BP neural network to optimize and solve the parameters of a PID controller to obtain the first target parameters of the PID controller; using the first target parameters to construct a first adaptive PID controller, if the error between the measured temperature and the target temperature is greater than a preset value, using the first adaptive PID controller to update the control amount of heating and refrigeration until the error between the measured temperature and the target temperature is within the preset range, then executing the following; using the optimal value of the WOA algorithm as the displacement parameter of the PSO algorithm to obtain a PSO-WOA algorithm, to obtain the second target parameters and the second adaptive PID controller; using the second adaptive PID controller to update the control amount of heating and refrigeration to realize temperature regulation. The application can improve the temperature control speed and control precision.

The application discloses a control method for caisson sinking in water-rich sand layer and disturbance of adjacent buildings, which comprises the following steps: based on numerical simulation, stratum parameters are inversed and a hydraulic barrier is pre-designed; the sinking rate and the inclination angle of the caisson are collected in real time, the depth of soil removal or the amount of mud injection is adjusted by an inner ring incremental PID controller, so that the rate and the inclination angle tend to be close to the set value; meanwhile, the active control coefficient K c‑eff (t) is calculated, the rate set value is dynamically adjusted by an outer ring supervisor, and the K c‑eff (t) is ensured to be always in a safe interval; a precipitation settlement calculation model based on the layering summation method is established, and when the cumulative settlement or the settlement rate exceeds the standard, the recharge flow is adjusted according to an incremental formula. Through the "mechanical supervision-rate following" cascade control and the settlement-recharge closed loop feedback, the safe and controllable sinking of the caisson in the water-rich sand layer and the effective protection of the adjacent buildings are realized.

This invention discloses a method and circuit for detecting a bilaterally constructed magnetic field. The method includes: acquiring detection values ​​from a single Hall sensor for detecting longitudinal magnetic field strength and an even number of Hall sensors for detecting axial magnetic field strength; preprocessing the detection values ​​from all Hall sensors to obtain several first processed value sequences; calculating the rotation angle for each data point in the second processed value sequence using an inverse cosine trigonometric function; calculating the radial height for each data point in the second processed value sequence using an inverse tanine trigonometric function; controlling the real-time rotation angle and real-time radial height of the bilateral symmetry using an improved PID controller to quickly obtain the desired angle and desired radial height; and using the real-time radial height corresponding to the data from a single Hall sensor as the detected longitudinal height. This invention can simultaneously detect magnetic field strength at different angles, and the detected values ​​are more stable and accurate.

The application discloses a PID control optimization method for a water turbine regulating system based on a PINN, which comprises the following steps: constructing and training a physical information neural network; deploying the trained physical information neural network to an online inference system, and simultaneously, equipping a PID controller as a main control loop of the water turbine regulating system; the PID controller outputs a real control signal, and performs state evolution based on a multi-state mechanism model and outputs a real-time state feedback signal; the real-time state feedback signal is input into the physical information neural network for state recursive prediction and output of a predicted state feedback signal; the real-time state feedback signal and the predicted state feedback signal are continuously compared, and the accuracy and reliability of the physical information neural network under the current operating condition are evaluated; a bypass verification loop is constructed based on the evaluation result, and the main control loop and the bypass verification loop jointly form a closed-loop intelligent control system. The application improves the control accuracy and operation reliability of the water turbine regulating system under nonlinear and time-varying operating conditions.