178 results about "PID controller" patented technology

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 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.

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.

This invention belongs to the field of concrete pouring technology, and particularly relates to a precise control method for pile foundation concrete pouring based on multi-source sensor fusion. Addressing the problems of large measurement errors, frequent over-pouring, and significant concrete waste in traditional pile foundation pouring, this invention employs a high-frequency ultrasonic probe array coaxially fixed to the outer wall of the pouring guide pipe to uniformly elevate and scan, acquiring three-dimensional point cloud data of the entire pile foundation. After two levels of outlier removal and adaptive multi-scale spectral filtering preprocessing, combined with the expansion of the over-pouring section point cloud, a high-precision three-dimensional model of the pile foundation is constructed. Cross-sectional features at each depth are extracted to generate a pumping flow rate feedforward compensation curve, and a segmented adaptive improved PID controller is constructed with real-time concrete interface elevation and rise speed as feedback quantities to dynamically regulate the pumping flow rate. This invention achieves automated, intelligent, and precise control of the entire pile foundation pouring process, effectively improving pouring control accuracy, significantly reducing concrete waste and construction costs, and solving the measurement and pouring control problems of traditional construction.

This invention discloses a multi-sensor fusion adaptive control method and system for a micro-agricultural box. The method simultaneously collects three types of data: environmental, cultivation medium, and crop images. It utilizes an improved unscented Kalman filter algorithm for multi-source data fusion and multi-parameter coupling calculation, combined with a BP neural network-optimized adaptive PID controller to achieve closed-loop control. The system also includes an image recognition dynamic correction unit and a fault diagnosis and tolerance unit. This invention addresses the pain points of existing micro-planting equipment, such as low control precision, large parameter coupling interference, inability to adapt to the entire growth cycle, and poor reliability for unattended operation. This invention improves temperature and humidity control precision to ±0.5℃ / ±3%RH, reduces pest and disease incidence by more than 95%, and achieves pesticide-free, unmanned adaptive planting, suitable for home and commercial micro-agricultural scenarios.

The application discloses a steam temperature control method and device, a storage medium and an electronic device, relates to the technical field of control, and the method comprises the following steps: acquiring the current steam flow of a boiler, the current swing angle of a burner and the current flue gas temperature of a superheater inlet in a steam temperature control system of a thermal power plant; acquiring a superheater inlet and outlet enthalpy increase model; calculating the current steam flow, the current swing angle and the current flue gas temperature according to the superheater inlet and outlet enthalpy increase model to obtain the first inlet and outlet enthalpy increase of the superheater; calculating according to the first inlet and outlet enthalpy increase to obtain a target temperature value of the superheater inlet, and controlling the steam temperature of the superheater inlet according to the target temperature value. Through the application, the problem that the steam temperature is adjusted by a PID controller in the related art, resulting in relatively low accuracy of steam temperature control, is solved.

The application discloses a kind of high-precision Beidou time service master clock devices based on double-chip atomic clock fusion, it relates to timing synchronization technical field, the device includes satellite receiving module, master control processing module, double-chip atomic clock module, clock taming module, time-frequency output module, display control module and power module;Each module is cooperated by work mode automatic switching mechanism Work;Double-chip atomic clock module adopts two pieces chip level atomic clock and constitutes master-slave redundant architecture, and the phase and frequency deviation information of main atomic clock and slave atomic clock are fused and mutually checked by extended Kalman filtering;The taming algorithm in clock taming module is formed by extended Kalman filtering link, PID controller link, digital phase-locked loop link cascade;Work mode automatic switching mechanism is according to the automatic switching of work mode according to the operating state of the device;Overcome the insufficient of time service precision, low reliability, taming algorithm performance is limited and so on in prior art.

This application discloses a speed-up control system, control method, and controller for a steam-driven feedwater pump. The speed-up control system includes a PID controller, a start-up control valve, a load control valve, and a controller. The PID controller has an 8-second operating cycle and a dead zone of 15 revolutions. The controller controls the load control valve to be fully open and reduces the opening of the start-up control valve based on the output value of the PID controller, causing the pump speed of the steam-driven feedwater pump to increase from the turning gear speed to a first target speed. When the pump speed of the steam-driven feedwater pump reaches the first target speed, the start-up control valve is controlled to be closed. The opening of the load control valve is reduced, causing the pump speed of the steam-driven feedwater pump to increase from the first target speed to a second target speed. In this embodiment, by setting the operating cycle of the PID controller to 8 seconds, the number of output changes of the PID controller is reduced, thereby increasing the service life of the start-up control valve.

The application provides a power output control optimization method for an electric locking valve, and belongs to the field of PID control optimization, and specifically relates to the following: current current and opening and closing displacement of the electric locking valve driving motor are collected in real time, and the electric locking valve locking process is started according to the target current of the driving motor; a current error signal is input into a current PID controller to perform closed-loop adjustment on the current of the driving motor; parameters of the current PID controller are set by using an improved beaver behavior algorithm: based on a competition index and a structural consistency tensor, the position of a population individual is updated through an exponential regulation factor; based on a reflection operator and a regulation parameter, the position of the population individual is updated through a direction modulation matrix; when the valve reaches a locking position, the target current of the driving motor is limited and maintained, so that the valve is kept in a stable locking state; and the power output of the electric locking valve is optimized by using the method.

A control method for a turbine speed regulation optimization system based on hybrid intelligent feedforward compensation belongs to the field of turbine speed regulation system control technology. This method simultaneously triggers two feedforward channels—data-driven and knowledge-driven—when a change in head or load is detected: the data-driven channel outputs a first opening compensation amount using a neural network model trained on historical operating data, while the knowledge-driven channel outputs a second opening compensation amount using a fuzzy logic controller built based on the turbine's physical characteristics and expert experience. The severity index of the operating condition change is calculated based on the changes in head and load, and the two compensation amounts are adaptively weighted and fused to generate the final feedforward opening compensation amount. This compensation amount is then superimposed on the PID controller output command to form the main guide vane opening control signal. This invention overcomes the lag of traditional feedback control through a hybrid feedforward mechanism, improving the dynamic response speed and regulation stability of the unit under conditions of large head fluctuations and frequent load changes.

This specification provides an integrated circuit power supply analytical redundancy self-healing control method and apparatus. The integrated circuit power supply analytical redundancy self-healing control method includes: acquiring the current operating data and historical operating data at multiple historical moments collected by various sensors in an aging bench monitoring system; extracting fusion features from the historical operating data and the current operating data; processing the highly discrete data in the operating data and the prediction results of the operating data from the previous moment to obtain the prediction results of the operating data at the current moment; performing multi-task state evaluation based on the operating data, fusion features, and the prediction results of the operating data at the current moment to generate evaluation results of the output voltage, ripple voltage, and health status of the secondary power supply; updating the parameters of the PID controller based on the evaluation results; calculating and outputting control signals through the updated PID controller to perform self-healing control of the output power of the secondary power supply.

This invention discloses a hierarchical coordinated control method and system for gas-cooled microreactors using deep reinforcement learning, belonging to the field of nuclear reactor control technology. The method constructs a three-layer architecture comprising an intelligent decision-making layer, a signal processing layer, and a PID controller layer. It utilizes a SAC (Smart Agent Control) agent to optimize the incremental output of electrical power and outlet temperature based on the gas-cooled microreactor's thermal parameters. The signal processing layer performs rate limiting and low-pass filtering on the optimized incremental output to generate a smooth setpoint command. The bottom-layer PID controller then outputs turbine speed and airflow signals to perform load tracking. This invention integrates the advantages of deep reinforcement learning in handling strong coupling and nonlinear dynamics with the robustness of traditional PID control. Through a physical constraint layer, it effectively suppresses oscillations and overshoot of the AI ​​control signal, achieving fast, smooth, and safe decoupled control of the gas-cooled microreactor across the entire power range, significantly improving load tracking performance and extending actuator life.

The present application relates to a kind of BP-PID intelligent control system for constant temperature drying oven, belong to industrial oven precision temperature control technical field.The system is by using BP neural network algorithm, the parameter of traditional PID controller is dynamically set online, combined with the high-precision temperature and humidity sensor of multiple point layout in the box, constructs adaptive temperature control loop with self-learning ability.BP neural network is fed forward according to the deviation of system real-time operating state and set value, real-time adjustment PID parameter to match the dynamic characteristics of controlled object.The system can significantly improve the dynamic response speed and steady control precision of constant temperature drying oven under the working condition such as temperature rise, anti-interference, effectively overcome the shortcomings of large overshoot and poor adaptability of traditional PID control, provide highly stable and uniform thermal environment for the drying process of temperature sensitive material, significantly improve product quality and drying efficiency.

The application relates to the technical field of silane gas detection, in particular to a silane gas purity rapid detection method, equipment and system, which comprises the following steps: collecting temperature data of an optical device surface in a gas chromatograph, pressure data inside a chromatographic column and vibration data at a support structure of a temperature sensor of the optical device surface in real time, detecting the purity of silane gas by using the gas chromatograph; obtaining environmental disturbance intensities at all collection moments; decomposing the environmental disturbance intensities at all collection moments to obtain a trend item, a periodic item and a residual item, and obtaining feature importance scores of the trend item, the periodic item and the residual item respectively, and then obtaining working condition degradation indexes when the purity of silane gas is detected at all collection moments; obtaining proportional coefficients of PID controllers at all collection moments, and controlling the pressure inside the chromatographic column when the purity of silane gas is detected. The application aims to improve the precision of silane gas purity detection by controlling the pressure inside the chromatographic column.

The application relates to the technical field of heat exchange device control, in particular to an energy-saving control method and device for an industrial low-temperature air conditioner, which comprises the following steps: analyzing the correlation between an equivalent refrigeration load and the temperature on the air outlet side of an evaporator, combining the difference between the instantaneous temperature and the average temperature of the application area of the low-temperature air conditioner, constructing a first self-adaptive compensation factor, and correcting the proportional gain of a PID controller; analyzing the difference between the equivalent refrigeration loads at all adjacent moments to construct a second self-adaptive compensation factor and correct the integral gain of the PID controller; and generating a control instruction of the low-temperature air conditioner based on the corrected proportional gain and integral gain to dynamically regulate and control the temperature of the low-temperature air conditioner. The application dynamically corrects the PID parameters based on the load and temperature response characteristics, solves the problems of frosting, overshooting and high energy consumption caused by traditional control, and improves the energy-saving control effect and operation stability of the industrial low-temperature air conditioner.

This invention discloses an automatic fuel feeding control strategy for a biomass circulating fluidized bed boiler, solving the problem of how to automatically control the rational supply of biomass fuel in the furnace to ensure stable boiler operation. This invention uses changes in the oxygen content of the flue gas at the boiler tail end to infer changes in the furnace fuel feed. Under the premise of constant air volume, an increase in oxygen content indicates a decrease in biomass fuel feed, while a decrease in oxygen content indicates an increase in biomass fuel feed. A PID control module is established with the oxygen content of the flue gas at the boiler tail end as the input value. The output value of this PID control module is used to adjust the frequency of the fuel feed screw feeder in the biomass circulating fluidized bed boiler. Furthermore, considering the unstable characteristics of biomass fuel, when the oxygen content in the furnace reaches a limit, the feedforward control mode and the lockout function mode of the PID controller are fully utilized to achieve stable boiler operation.

The application belongs to the technical field of black start control of power grid system, and particularly discloses a black start DC excitation regulator and a control method thereof applied to a black start system. The black start DC excitation regulator comprises a rate limiter and a PID controller. The black start DC excitation power source outputs an excitation step signal to a signal input end of the rate limiter. An output signal of the rate limiter is compared with a terminal voltage of a feedback machine, and a difference value is output to a signal input end of the PID controller. An output signal of the PID controller is sent to a generator terminal. The control method comprises the following steps: constructing a black start system; starting initial excitation of the black start DC excitation power source, and adjusting the terminal voltage of the generator through the black start DC excitation regulator; switching to an AC excitation adjustment mode; starting a load, and operating the black start system. The application shortens the excitation time of the black start system with zero start-up and voltage rise, and improves the probability of one-time successful excitation. The application is suitable for black start control of a power grid.

The application discloses a multi-parameter regulated boiler combustion efficiency dynamic optimization method. The specific operation steps are as follows: real-time acquisition of combustion parameters from a power plant system, pre-processing of the collected original data, and feature selection after data pre-processing; the feature data selected and pre-processed are taken as input according to time sequence to construct an IGWO-transformer prediction model; taking the degree of electricity coal consumption, nitrogen oxide emission concentration and fly ash carbon content as optimization targets, a NSGA-III algorithm is used for multi-objective optimization; aiming at the control requirements of the feature data, an independent PID controller is configured for each control object, the actual value collected is compared with the target set value, the control deviation is calculated as the input signal of the PID controller, and the controller is driven to perform dynamic adjustment. The application has the beneficial effects that the data processing and generalization ability are enhanced, accurate prediction and regulation are realized, and the combustion efficiency is improved; the economy and environmental protection are balanced, and dynamic optimization is realized.

This invention discloses an adaptive intelligent welding robot system and method based on multi-source information fusion, relating to the fields of intelligent welding and robot control technology. The system integrates a multi-source heterogeneous sensing module, a spatiotemporal registration and synchronization module, a three-level information fusion module, a digital twin and incremental learning module, a trajectory-parameter collaborative control module, and an execution drive module. It synchronously collects multi-dimensional welding data through multiple sensors, including laser 3D vision. After time synchronization and spatial registration, it completes three-level information fusion using Kalman filtering, hybrid feature selection, and D-S evidence theory. Combined with multiphysics twin simulation and federated incremental learning, a fractional-order PID controller synchronously generates trajectory correction and optimized process parameters. Adaptive welding is then performed by a six-axis robotic arm and other execution components. This invention significantly improves welding accuracy, stability, and adaptability, meeting the high-precision and high-efficiency welding requirements of fields such as bridges and new energy equipment.

This invention discloses a furnace temperature measurement and control system and method for high-temperature areas, including a dual-spectrum imaging module, an onboard processing unit, a gimbal module, a power supply module, and an industrial IoT communication module. The dual-spectrum imaging module is used to acquire thermal image data and visible light image data, and output thermal image frame streams. The onboard processing unit receives continuous thermal image frame streams, and for each frame, executes a hotspot identification algorithm to determine the pixel coordinates of the highest temperature point in the image, and calculates a two-dimensional error vector e between these coordinates and a preset image frame center point. The error vector is input into a PID controller, and control commands are sent to the gimbal module to drive the camera to adjust its aiming direction to reduce and ultimately eliminate the error vector. Key telemetry data and real-time video streams are accessible to operators via the industrial IoT communication module for manual intervention when necessary. This invention features the ability to automatically lock onto and track high-temperature areas without manual intervention.

The utility model relates to the field of PID controller installation, especially a fixing device for PID controller, including box, limiting mechanism and heat abstractor, box is equipped with fixed establishment, heat conduction plate, installation mouth and is used for the installation space of limiting PID controller, installation mouth and installation space intercommunication, heat conduction plate is used for abutting PID controller, fixed establishment is used for fixing box, limiting mechanism is used for inserting installation mouth abutting PID controller, and limiting mechanism is detachably connected with box, heat abstractor is connected with box, and heat abstractor is connected with heat conduction plate, and the heat abstractor strengthens the heat dissipation effect to PID controller, avoids PID controller to damage because of overheating, and guarantees the long -term stable operation of PID controller, through limiting mechanism and box detachable connection, the installation and disassembly of PID controller are convenient, and the work efficiency has been improved, through limiting mechanism abutting PID controller, realizes the quick fixing of PID controller, makes PID controller fixed firm, through fixed establishment and fix the box, convenient to use.

The application provides a heat exchanger real-time control method and system, an electronic device and a storage medium, and belongs to the technical field of intelligent control. The method comprises the following steps: acquiring a wort real-time temperature value and a wort target temperature value at a current time; inputting the wort real-time temperature value and the wort target temperature value into a PID controller to obtain a control amount; performing real-time control on the heat exchanger based on the control amount; and wherein the control parameters of the PID controller are determined by a reinforcement learning network that has been trained. The heat exchanger real-time control method and system, the electronic device and the storage medium provided by the application can improve the control accuracy of the heat exchanger.

The embodiment of the specification discloses a SOEC-methanol system collaborative control method for a renewable energy scene, the technical scheme of the application generates synthetic irradiance through dynamic sky classification, K-means clustering and the like, combines multiple data to construct an input matrix, and predicts photovoltaic power generation power through a double-layer LSTM neural network; then, the prediction is used as a disturbance, a model predictive control (MPC) algorithm is used, a thermal-electric coupling state space model is used as a basis, multiple operation constraints are considered, and control instructions are rollingly optimized; finally, the instructions are executed by a PID controller, SOEC-related equipment is adjusted, and the system state is fed back, so that closed-loop roll optimization is realized.

This invention provides a constant tension control method for the 3D printing process of continuous fiber composite materials, including modeling the tension control process and optimizing the PID controller using the cucurbit optimization algorithm. By real-time monitoring and dynamic adjustment of fiber tension during 3D printing, a mathematical model is established based on the characteristics of the magnetic powder actuator to describe and predict tension changes. The cucurbit optimization algorithm is then used to optimize the parameters of the PID controller. This algorithm simulates the foraging behavior of cucurbits in nature, finding the optimal PID parameter settings through iterative calculation, thereby achieving rapid response and system stability. Compared with the BP optimization algorithm and the traditional PID algorithm, the cucurbit optimization algorithm has higher global search capability and convergence speed. Through the above method, this invention can maintain the stability of fiber tension during 3D printing, reduce printing defects caused by tension fluctuations, improve the molding quality and printing efficiency of continuous fiber composite materials in 3D printing, and has broad application prospects.