487 results about "Pid control algorithm" patented technology

The invention belongs to the field of robot control, and particularly relates to a robot self-adaptive impeller welding control method and system fused with multi-modal data, and the method comprises the steps: obtaining an impeller workpiece image and three-dimensional point cloud data through an industrial vision subsystem, and extracting a three-dimensional welding seam position point set representing a welding seam track; generating a candidate welding path set based on welding seam geometric feature analysis; in combination with welding seam morphology and process requirements, optimal welding process parameters are predicted through a regression model, and a welding gun attitude angle is calculated through quaternion conversion according to a curved surface normal vector; in the welding process, the relative position deviation of a robot and a workpiece and the parameter deviation of welding current / voltage and a planned value are monitored in real time, when the deviation exceeds a preset tolerance interval, a PID control algorithm is adopted to dynamically adjust robot motion parameters or welding process parameters, and closed-loop control over the welding process is achieved; according to the method, precise planning of the welding path and self-adaptive regulation and control of the process are achieved, and the welding quality and the forming consistency are remarkably improved.

The invention discloses a mixed emulsion explosive one-key production control method and system, and relates to the field of automatic and intelligent control. By means of automatic and intelligent control means, the problems of low efficiency, high cost, quality fluctuation, process uncertainty and the like in traditional mixed emulsion explosive production are solved, accurate feeding of raw materials is achieved through a quality sensor array and a PID control algorithm, and the production efficiency is improved. The stability of production parameters is ensured through multi-sensor data fusion and an advanced control algorithm, so that the consistency of product quality is improved; meanwhile, a feedback control loop and a continuous learning mechanism are established, closed-loop control in the production process is achieved, technological parameters are optimized, the production stability and reliability are ensured, the production efficiency and the product quality are remarkably improved, and the labor cost is reduced.

The invention belongs to the technical field of drilling, and provides an active vibration reduction method and system based on self-adaptive adjustment of a drill rod load in order to effectively reduce vibration of a drill rod. A real-time feeding oil pressure signal is converted into real-time feeding thrust, and a real-time rotating oil pressure signal is converted into real-time rotating torque; filtering the original vibration signal by adopting a singular value subspace decomposition method to obtain a real vibration signal; according to the preset initial value of the feeding thrust and the preset initial value of the rotating torque, a neural network self-adaptive PID control algorithm is used for conducting self-adaptive comparison calculation, the vibration adjustment amount is obtained, and active vibration reduction is conducted according to the vibration adjustment amount; the system comprises six closed-loop control modules including a preset parameter input module, a signal acquisition module, a signal filtering module, a control algorithm module, a control output module and an execution module, accurate vibration reduction control is achieved, the bounce phenomenon of a drill bit is eliminated, the deviation error of a drill hole is reduced, meanwhile, stick-slip vibration is restrained, and the clamping stagnation failure rate of a drill rod is greatly reduced.

The invention discloses a sensing optical cable laying robot path planning and obstacle avoidance system and method, and belongs to the technical field of robot path planning. The system comprises an environment sensing module, a data preprocessing module, a path planning module, an obstacle avoidance control module and a post-processing module. According to the method, environment information is acquired and preprocessed through a laser radar and a camera, path planning is performed based on an improved dynamic RRT algorithm, a self-adaptive step length adjustment mechanism is introduced, the step length is dynamically adjusted according to environment complexity, obstacle distance and path curvature, and a smooth path is generated by combining real-time obstacle detection and dynamic re-planning functions. A PID control algorithm is adopted to adjust the speed and the steering angle of the robot to achieve obstacle avoidance, and a post-processing module optimizes an evaluation path. The real-time performance, the path quality and the environment adaptability of the robot in a complex dynamic environment are improved, and efficient, safe and accurate laying of optical cables is ensured.

The invention relates to the technical field of laser temperature control, in particular to a temperature control method and system for a multi-environment VCSEL laser, and the method comprises the steps: collecting the temperature of the VCSEL laser at each moment, and the current of a thermoelectric refrigerating unit used for carrying out the temperature control of the VCSEL laser at each moment; determining the temperature fast adjustment intensity and the temperature oscillation characteristic value of the VCSEL laser at each temperature control moment; obtaining a steady state adjustment value of the VCSEL at each temperature control moment; determining the magnetic field interference suppression intensity of the VCSEL laser at each temperature control moment; and correcting a first threshold value and a second threshold value of the integral separation PID control algorithm, determining a switching coefficient of an integral item in the integral separation PID control algorithm, and performing temperature control on the VCSEL at each temperature control moment. Therefore, the temperature control precision of the VCSEL laser is improved.

The invention discloses a real-time monitoring and intelligent deviation rectifying system and method for hoisting of fabricated building components, and the real-time monitoring and intelligent deviation rectifying system comprises a monitoring module, a data preprocessing module, an intelligent decision-making module and a deviation rectifying execution module, the real-time monitoring and intelligent deviation correction method comprises the steps of monitoring data collection, monitoring data preprocessing, intelligent prediction, PID-based real-time balance adjustment and dynamic iteration and optimization. Component postures, stress states, environment wind loads and hoisting equipment operation parameters are monitored in real time through a multi-source sensor, intelligent prediction and decision making are conducted in combination with a deep neural network model, and high-precision tracking of a target tension value is achieved in combination with a PID control algorithm; therefore, intelligent prediction and self-adaptive regulation and control of the hoisting operation of the fabricated building component in the high-altitude complex operation environment are realized.

The invention relates to the technical field of general control or regulation systems, in particular to a sushi type S-shaped layered horizontal self-driven transmission mushroom and vegetable shelter planting system. The system comprises a data acquisition module, a path planning and scheduling module, a motor driving control module, an environment regulation and control module and a central controller. The system collects environment parameters, carrier states and crop growth information in real time through a sensor network, and constructs system state vectors. The central controller combines a heuristic path planning algorithm, an adaptive PID control algorithm, a model prediction control algorithm and a DQN optimization strategy based on deep reinforcement learning to realize carrier path optimization, motor driving precision control, cabin environment prediction regulation and control and system closed loop feedback optimization. The system has the advantages of flexible orbit scheduling, efficient operation response, fine environment control, high intelligent level and the like, and can realize subarea fine management and continuous optimization evolution of the system in a multi-category crop co-cabin planting scene.

The invention relates to the technical field of air compressor optimization, and discloses an intelligent air compressor optimization control method and system based on an IOE control system.The intelligent air compressor optimization control system comprises a collection unit, a preprocessing unit, an analysis unit and an optimization unit, rich operation data such as air inlet pressure, flow, exhaust pressure and temperature are comprehensively collected in real time, denoising is conducted through a moving average method, and data accuracy is ensured; normal, overload and abnormal fluctuation modes are clearly divided, accurate judgment is performed by means of a preset interval and reasonable calculation, and powerful support is provided for control decision making; in a normal mode, intelligent regulation is performed according to a parameter average value, and operation efficiency and stability are improved; the valve opening degree is adjusted according to the deviation degree in the overload mode, the load is effectively reduced, and equipment is protected; in the abnormal fluctuation mode, a PID control algorithm is used, the opening degree, the cooling amount and the like of the valve are flexibly adjusted according to deviation and the change rate, and parameters are rapidly recovered to be stable. The fault rate and the maintenance cost can be greatly reduced, and the working efficiency is remarkably improved.

The invention relates to the technical field of pH value adjustment, and discloses a pH value adjustment method and system, a storage medium and equipment. The method comprises the following steps: denoising time sequence data of a pH sensor to obtain a smooth pH value sequence, and calculating a first-order difference of the smooth pH value sequence to obtain a pH value rate change sequence and rate characteristics; when any value in the sequence exceeds a preset threshold value, extracting feature distribution data, and inputting the feature distribution data and real-time state data of the solution into a solution state evaluation model to obtain an estimated value of the buffer capacity and reaction rate change of the solution; based on the estimated value, the pH value rate change sequence and the rate characteristics, calculating a preliminary control sequence of the acid-base addition amount, adopting a self-adaptive PID control algorithm to adjust parameters, generating an optimal control sequence, controlling the acid-base addition equipment to adjust the addition amount, obtaining new pH value data, and performing fast Fourier transform to obtain a stable pH value sequence. The stability of pH value control of the solution is improved.

The invention relates to the technical field of electrochemical machining, in particular to an electroplate liquid additive automatic supply control method based on conductivity monitoring data. The method comprises the steps that the temperature, the original conductivity and the carbonate concentration of electroplating liquid are obtained, an activation energy coefficient is determined based on the change trend of the original conductivity and the temperature, dynamic thermodynamic decoupling treatment is conducted on the original conductivity, and the net conductivity of the electroplating liquid is generated; according to the cumulative variation of the net conductivity in the historical time period and the total amount of the additive in the historical time period, the transmission inertia factor of the electroplating liquid is calculated in combination with the carbonate concentration, and the retardation risk index is determined based on the evolution trend of the transmission inertia factor, so that a PID control algorithm is reconstructed, and the supply amount of the additive is obtained; and performing automatic replenishment control based on the replenishment amount. According to the method, the accuracy of automatic supply control is improved by evaluating the degradation state of the bath solution components and self-adaptive integral saturation suppression.

The invention discloses a frequency modulation control method and system for a thermal power generating unit, and relates to the technical field of frequency modulation control, and the method comprises the steps: collecting a frequency modulation instruction signal of a power grid, decomposing the frequency modulation instruction signal, and obtaining a plurality of intrinsic mode function components and residual components; performing spectral analysis on each intrinsic mode function component, marking the component of which the main frequency exceeds a high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculating a fluctuation amplitude and a change rate; a thermal system control instruction is generated through a PID control algorithm, the coal feeding amount and the main steam pressure are adjusted, and an auxiliary compensation control instruction is generated for the high-frequency disturbance component through a fuzzy control algorithm; a thermal system control instruction and an auxiliary compensation control instruction are converted into operation parameters of a thermal power generating unit control mechanism and issued for execution, when the control effect deviation continuously exceeds a deviation threshold value, an optimization process is triggered, and the frequency modulation stability and the equipment safety of a unit in the environment that new energy is accessed to a power grid in a high proportion are remarkably improved.

The invention relates to the technical field of gas path control, and particularly discloses a gas path control method and system, an intelligent terminal and a storage medium, a PID control algorithm is used for calculating a pressure control quantity according to a current error so as to gradually enable the system to reach a stable state close to a target control value, and dynamic gain compensation and machine learning feed-forward compensation are introduced so as to achieve a stable state close to the target control value. Nonlinear compensation is carried out on disturbance caused by environment temperature changes, and rapid response is carried out based on the speed of temperature changes so as to make up for the lag problem in the dynamic change process.

The invention discloses a hydrogen and oxygen supply method for a hydrogen fuel cell emergency power supply vehicle. The method comprises the following steps: 1, providing a hydrogen and oxygen supply system for the hydrogen fuel cell emergency power supply vehicle; 2, information acquisition; 3, data processing; the FL-LADRC algorithm disclosed by the invention has the characteristics of simple structure, low calculation burden and low implementation cost on the premise of ensuring the disturbance suppression capability, and is particularly suitable for being used by an embedded platform or resource-constrained equipment. According to the method, the problem that the cathode pressure cannot be measured is solved by introducing the sliding mode differential observer, and the dynamic coupling relation between the oxygen flow and the cathode pressure is compensated in real time in combination with the improved expansion state observer, so that the operation risks such as oxygen starvation and flooding are effectively eliminated; in addition, compared with a traditional PID control algorithm, the fuel cell air supply system adopts the IGA-BP prediction and the NNMPC control algorithm, the performance is remarkably improved, and the urgency and stability requirements of the emergency power supply vehicle in the power protection operation can be better met.

The invention provides a glyceryl triacetate production parameter control method and system based on reinforcement learning, and relates to the technical field of optimization control methods, and the method comprises the steps: obtaining the production parameters of glyceryl triacetate; based on the kinetic model, constructing a kinetic equation of the esterification reaction of glycerol and acetic acid; constructing a digital twinborn simulation environment of the glyceryl triacetate production process; defining a reinforcement learning framework by taking a digital twin simulation environment as a scene; according to the reinforcement learning framework, taking the Elman neural network as a state predictor, and predicting the state of the glyceryl triacetate; solving the reinforcement learning framework through an MO-MPO algorithm, and determining an optimal control strategy and an optimal production parameter sequence corresponding to the optimal control strategy; judging whether the process capability index is smaller than a process capability index threshold value or not; if yes, continuing to solve the reinforcement learning framework; otherwise, outputting an optimal production parameter sequence; and controlling the optimal production parameter sequence through a PID (Proportion Integration Differentiation) control algorithm.

The invention provides a centralized dust control method and system for a driving working face, and the method comprises the steps: collecting actual measurement environment parameters of the driving working face in real time through a sensor, and carrying out the preprocessing of the actual measurement environment parameters, and obtaining the preprocessed actual measurement environment parameters; acquiring a target environment parameter of the driving working face, and determining an absolute value of an environment parameter difference value according to the target environment parameter and the preprocessed actually measured environment parameter; according to the absolute value of the environmental parameter difference value, an execution mechanism adjustment instruction value is determined through a PID control algorithm; and controlling the driving working face centralized dust control system based on the execution mechanism adjustment instruction value. Wherein the executing mechanism adjusting instruction value comprises the angle variation of a guide vane in the negative-pressure air duct body, the opening size variation of an air distributor in the negative-pressure air duct body and the rotating speed of a fan. According to the technical scheme provided by the invention, the safety and the environmental protection property of the tunneling operation are improved.

The invention is suitable for the technical field of electric power line construction, and provides a tension machine control system based on tension feedback and a control method thereof, and the method comprises the following steps: obtaining lead parameters, working condition data and environment data of current stringing construction in real time; determining the comprehensive specific load of the wire according to the wire parameters and the environment data; updating a target tension value of the wire in real time according to the comprehensive specific load, the wire parameters, the working condition data and the environment data of the wire; according to the working condition data, the actual tension value of the current wire is determined, and the tension deviation is calculated based on the current target tension value; and based on a digital PID control algorithm, the tensioner is controlled in real time according to the tension deviation. According to the wire parameters, the working condition data and the environment data, the target tension value of the wire can be updated in real time, then the tension machine can be automatically controlled based on a digital PID control algorithm by sensing the actual tension value of the wire in real time, and high-precision control over tension is achieved.

The invention relates to the technical field of automatic control, and discloses a flood season water quality monitoring method and system based on a variable speed integral PID controller. The method comprises the following steps: acquiring and fusing pollutant concentration data and water level fluctuation parameters in a flood season water body through a sensor network to obtain a current water quality state index; according to the current water quality state index, time sequence change data of pollutant concentration is extracted, concentration gradient information is calculated, freshness analysis is carried out on the concentration gradient information, and weighted gradient information is generated; fusing the weighted gradient information with historical water quality monitoring data, determining a comprehensive gradient trend, and obtaining a preliminary update value of a variable speed control coefficient through a variable speed integral PID control algorithm according to the comprehensive gradient trend; if the preliminary update value exceeds a preset range, an iterative optimization algorithm is adopted to obtain a refined variable speed control coefficient, operation parameters of water quality control equipment are adjusted, and a dynamic regulation and control result of the water quality in the flood season is output, and the control accuracy of the concentration of pollutants in the water quality is improved.

The invention provides an intelligent cabinet heat dissipation control method and system, and belongs to the technical field of cabinet heat dissipation control. According to the method, data items all have acquisition time and cabinet area identifiers; the method comprises the following steps: dividing a cabinet hot area by using fuzzy clustering based on a historical sample, dynamically modeling by combining an adaptive PID control algorithm, optimizing control parameters through a particle swarm optimization algorithm, adjusting a hot area control model weight coefficient according to real-time feedback, generating a hot area-equipment association map, and constructing an adaptive heat dissipation control network; predicting a temperature trend through a decision tree model by using a correlation map and real-time operation characteristics generated by the network, and generating a fan rotating speed adjusting strategy, an air conditioner power distribution scheme and a multi-stage heat dissipation control strategy according to the temperature trend; inputting a heat dissipation control strategy and an execution result as feedback into the self-adaptive heat dissipation control network, and dynamically optimizing a correlation map and control parameter modeling; and multi-cycle feedback closed-loop optimization control is realized through multi-time feedback and parameter adjustment.

The invention discloses a power plant direct-current oil pump motor control loop low-oil-pressure self-starting pressing plate adjusting system, particularly relates to the field of direct-current oil pump pressing plate adjustment, and comprises a pressing plate state monitoring module, a working condition decision module, a soft start execution module, a hard start straight-through module and a transient protection module. According to the low-oil-pressure self-starting pressing plate adjusting system of the power plant direct-current oil pump motor control loop, forced locking is achieved through the pressing plate state monitoring module when a pressing plate does not exit, and the risk that an armature winding bears full-pressure impact and counter electromotive force impact when an IGBT is not ready is avoided; soft start and hard start are distinguished through the working condition decision module, and response delay of a single soft start strategy in an emergency is avoided; the IGBT conduction angle climbing rate is dynamically adjusted through a PID control algorithm by means of a soft start execution module, a programmable timer controls time sequence switching of a contactor, smooth progressive climbing of motor current is achieved, bus voltage is stabilized, and current impact and back electromotive force influence in the starting process are reduced.

The invention relates to the field of oil field heating furnace control, and discloses an oil field heating furnace intelligent digital implementation method and control method.The control method comprises the following steps that S1, a temperature sensor is used for monitoring the temperature of an oil field heating furnace in real time; s2, calculating a temperature error between the upper limit and the lower limit of the real-time temperature and the set temperature according to the monitoring data of the temperature sensor; s3, a self-adaptive PID control algorithm is applied, and heating power is calculated based on the temperature error; and S4, dynamically adjusting the heating power to control the temperature of the oil field heating furnace. The precision and stability of temperature control can be improved, the oil field heating furnace can control the target temperature more accurately, and the production efficiency is improved. Meanwhile, the self-adaptive PID control algorithm can automatically adjust parameters according to actual working conditions and environment changes, the adaptability and robustness of the system are improved, and the requirements for manual intervention and adjustment are reduced. In addition, the stable and efficient heating process can be achieved by dynamically adjusting the heating power, and energy and cost are saved.

The invention discloses a hovering accelerator estimation method and system for an electric power inspection unmanned aerial vehicle, equipment and a medium, and the method comprises the steps: taking a hovering accelerator of the unmanned aerial vehicle as an estimator, taking a vertical acceleration as a measurement quantity, and carrying out the real-time estimation of the hovering accelerator of the unmanned aerial vehicle through an extended Kalman filtering algorithm; the extended Kalman filtering algorithm is integrated into hovering control of the unmanned aerial vehicle for the first time, compared with an existing PID control algorithm, the control precision and the dynamic response capability of fixed-point hovering of the unmanned aerial vehicle are improved, better robustness is achieved, high-precision, real-time and dynamic stable hovering control can be achieved, the method can be suitable for the unmanned aerial vehicle with the weight changing in real time, and the hovering control accuracy of the unmanned aerial vehicle is improved. And the method has better generalization ability.

The invention provides an intelligent planning method for a welding path of a welding seam, and belongs to the technical field of automatic welding. The problem that in the prior art, the welding precision is not high is solved. The intelligent planning method for the welding path of the welding seam comprises the steps that a welding seam area is scanned, and three-dimensional point cloud data of the welding seam and a surrounding area are obtained; preprocessing the three-dimensional point cloud data to obtain optimized point cloud data; performing welding seam region segmentation on the optimized point cloud data, and extracting a point cloud set with welding seam geometric features; extracting weld center points from the point cloud set, and fitting the weld center points into a weld center line; a welding path is obtained based on weld joint center line planning; the welding gun carries out welding operation according to the planned welding path; and actual welding points of the welding gun are collected in real time, deviation calculation is conducted on the actual welding points and planned welding path points, and the movement track of the welding gun is corrected through a PID control algorithm and the calculated deviation value. The precision of the welding process is effectively improved.

The invention discloses a GIS in-place robot coordination control method with a posture correction function, and belongs to the technical field of robot coordination control. The method comprises the following steps: establishing a 2D-3D coordinate mapping corresponding relation; fusing the corresponding relation with an operation state predicted by an IMU-based inertial measurement and system dynamics model; performing error calculation on the obtained 6D pose information and target pose information; constructing a nonlinear kinetic equation of the robot, and converting a control target into an optimization problem of various constraints; and converting the obtained control instruction into a torque signal for actually driving the robot to move. According to the method, the influence of mismatching on pose estimation is effectively inhibited by establishing the 2D-3D coordinate mapping relation; through a joint torque PID control algorithm, the torque required by each joint is calculated in real time, and high-precision tracking of an expected trajectory is realized; an MPC optimization control framework with multiple constraints is constructed, and precise, smooth and safe coordination control over the GIS in-place process is achieved.

The invention relates to the technical field of coal mining, in particular to a dry coal preparation control system based on data analysis, which comprises a real-time data acquisition module, a data analysis module, a self-adaptive control module and a feedback optimization module. The real-time data acquisition module acquires information such as granularity, density, images and moisture of coal particles through a granularity sensor, a density sensor, an image sensor and a humidity sensor, and transmits data to the central processing unit. And the data analysis module analyzes the collected data based on a random forest algorithm to generate a sorting precision prediction value. The self-adaptive control module dynamically adjusts key parameters of the coal dressing equipment according to the predicted value by utilizing a PID control algorithm, and the key parameters comprise the wind speed, the screen inclination angle, the material flow speed and the like. The system not only improves the coal dressing precision and stability, but also improves the self-adaptive capacity of the equipment through intelligent control and optimization, and the system is suitable for popularization and application. The method has remarkable economic benefits and wide application prospects.

The invention relates to the technical field of circulating water treatment, and provides a circulating water multi-stage purification system and a control method thereof.The control method comprises the steps that water quality parameters of each purification step of the circulating water multi-stage purification system and proportional parameters of a PID control algorithm are collected, and target water quality parameters are marked; acquiring a collection moment cluster, marking a target water quality parameter and a target collection moment, determining a dosing effect and a first reference value of a proportion parameter, and further determining a second reference value of the proportion parameter of each purification step; a water quality parameter cluster is obtained, the adjustment influence degree is calculated, and a third reference value of the proportion parameter of each purification step is determined; and determining the optimal value of the proportion parameter of each purification step by combining the second reference value and the third reference value of the proportion parameter, so as to realize circulating water multi-stage purification control. According to the invention, the proportional parameter value of the PID control algorithm can be adaptively determined, and accurate adjustment of the water quality of the water circulation system is ensured.

The embodiment of the invention discloses a chip temperature control method, device and equipment and a medium, and relates to the technical field of chip testing. The method comprises the following steps: acquiring a temperature fluctuation standard deviation and an error change rate of a to-be-tested chip based on an acquired temperature of the to-be-tested chip; matching a target weighting coefficient combination in a preset fuzzy rule base according to the temperature fluctuation standard deviation and the error change rate; determining a dynamic PID control parameter based on the target weighting coefficient combination and a preset basic PID parameter; and adjusting the power output of the temperature control module by adopting a preset PID control algorithm according to the dynamic PID control parameters so as to control the temperature of the chip. According to the invention, under the condition that only local heating or cooling is carried out on the chip, severe temperature fluctuation of the chip caused by dynamic load change can be effectively handled, and rapid, stable and high-precision control of the chip temperature is realized, so that strict requirements of extreme temperature testing are met.

The invention belongs to the technical field of laser welding, and particularly relates to a synchronous laser plastic welding pressure control method and device.The method comprises the following steps that S1, in the presetting stage, target welding pressure is set for a laser welding system; s2, a preparation stage: driving a lifting platform to move through a servo motor so as to link a lower mold to ascend and to be assembled with an upper mold, so that the pressing force of the first welding piece and the second welding piece reaches target welding pressure; s3, in the welding stage, a laser device is started, laser welding is conducted on the first welding piece and the second welding piece, the torque of a servo motor is adjusted through a PID control algorithm, so that the first welding piece and the second welding piece keep constant pressure, and the laser welding depth is gradually increased; s4, a pressure maintaining stage, wherein the pressure maintaining process is executed on the target workpiece, so that the laser welding depth of the target workpiece is slightly increased; and S5, a feedback stage: calculating the actual welding depth of the target workpiece and feeding back the actual welding depth to a control system to judge whether the actual welding depth meets the welding standard or not.

The invention relates to the technical field of switching power supply analog control, in particular to a control method and system for a small-duty-ratio BOOST module based on digital control, and the method comprises the following steps: S1, carrying out the sampling of the equal-proportion reduced output voltage of an operational amplifier through an ADC analog-to-digital converter, processing the sampled voltage value through a filtering algorithm to obtain an output voltage VO; and S2, carrying out calculation processing on the output voltage VO through a PID control algorithm, and obtaining an expected output voltage through a fixed-frequency adjustment duty ratio PWM and a fixed-duty ratio frequency modulation PFM. Efficient and stable voltage boosting is achieved through double-closed-loop digital control, dynamic response and anti-interference capacity are achieved, the core lies in collaborative design of power conversion and a control strategy, input direct-current voltage is boosted to higher stable output voltage, a double-closed-loop (voltage loop + current loop) control strategy is adopted, and the voltage boosting effect is achieved. And closed-loop adjustment is realized by combining PWM driving and ADC sampling.

The invention discloses a closed-loop control method for a hydraulic control butterfly valve of a PCCP (prestressed concrete cylinder pipe) long-distance high-pressure water conveying pipeline, and belongs to the technical field of long-distance high-pressure water conveying pipeline control. The problems that in the prior art, due to manual scheduling or single-point PID control, a long-distance PCCP water conveying system has response lag and lacks global cooperation, the water attack risk is difficult to effectively deal with, and the optimal overall energy consumption of the system cannot be considered are solved. According to the invention, by constructing a hierarchical control architecture in which a distributed measurement and control network is coordinated with a central supervision control and data acquisition system platform, a variable-parameter PID control algorithm is built in an equipment PLC, so that millisecond-level identification and active suppression of a sudden water attack working condition are realized; a hydraulic simulation model and a multi-objective optimization algorithm are deployed in a central supervision control and data acquisition system master station, and a whole-line optimal pressure set value is solved through iterative calculation and is issued to each PLC for execution, so that the system energy consumption minimization is realized on the premise of ensuring the pipeline safety.

The invention discloses a chip dynamic temperature adjusting method based on a PID control algorithm, and the method comprises the following steps: S1, collecting and processing multi-point temperature data, and obtaining a unified temperature vector; s2, performing thermal mode extraction, and calculating a target temperature deviation to generate an error signal; s3, constructing a segmented polymorphic PI D controller, and performing mode switching to calculate a proportional item; s4, generating an integral term for each thermal mode, and performing change rate processing to generate a differential term; s5, the proportion, the integral and the differential are combined, and the distributor outputs an actuator instruction; and S6, issuing an executor instruction, and executing amplitude limiting and slope constraint to complete adjustment. According to the invention, through segmented multi-state PI D control and a mode perception distributor, rapid response and stable adjustment of the chip temperature are realized.