14 results about "Fuzzy self tuning" patented technology

The invention discloses a bimodal cooperative control-based intelligent chemical adding optimization method for a water supply project. The method comprises the following steps of: S1, acquiring effluent quality and quantity data of a water supply system and a monitoring index of a running state of the water supply system in a plurality of continuous control periods adjacent to a current control period; s2, judging whether the running state of the water supply system is in a stable state or not according to the monitoring indexes and the effluent quality and quantity data, if so, entering step S4, and otherwise, entering step S3; s3, calculating the dosing pump control quantity in the current control period by adopting a fuzzy self-tuning PID algorithm; s4, determining a dynamic prediction time domain adjustment rule, inputting effluent quality and quantity data in a time domain into the machine learning model, and adopting a model prediction control MPC algorithm to obtain a dosing pump control quantity; and S5, according to the control quantity of the dosing pump in the step S3 or the step S4, controlling the dosing pump to add a medicament into the clean water tank, and returning to the step S1 when the water supply system is in a running state and the current control period is completed.

The invention provides a thermocouple temperature measurement adaptive anti-interference method and system applied to an instrument, and relates to the technical field of temperature measurement and control, and the method comprises the steps: obtaining an original thermocouple temperature measurement signal generated by a thermocouple body, carrying out the cold end compensation of the original thermocouple temperature measurement signal, and obtaining a standard thermocouple temperature measurement signal; respectively processing the standard thermocouple temperature measurement signals to obtain corrected thermocouple temperature measurement signals; the corrected thermocouple temperature measurement signal and the closed-loop manipulated variable are used as observed quantities to be input into the extended state disturbance model, an unknown equivalent disturbance quantity corresponding to the corrected thermocouple temperature measurement signal is obtained, and a predicted temperature deviation value and a predicted equivalent disturbance quantity are obtained through an extended state observer; and dynamically adjusting the gain of the PID controller by using a fuzzy self-tuning algorithm, carrying out superposition processing on the PID control quantity and the compensation quantity corresponding to the predicted equivalent disturbance quantity, and compensating the temperature controller by using a temperature regulation and control instruction. According to the invention, the steady-state disturbance suppression capability and the response speed can be improved.

The invention provides an effluent concentration regulation and control method and device of a sewage treatment plant, electronic equipment and a medium, the method is used for regulating and controlling a sewage treatment system, and the method comprises the following steps: acquiring water quality parameters of inflow water of the sewage treatment plant and actual working conditions of hydraulic operation conditions; determining the effluent concentration based on the water quality parameters and a pre-constructed bidirectional long-short term memory neural network; establishing a fuzzy rule base based on the actual working condition, the effluent concentration, a preset target working condition and a preset target effluent concentration; setting a fuzzy self-tuning PID control model based on the fuzzy rule base; based on the actual working condition, the effluent concentration, the target working condition and the target effluent concentration, a control variable is determined through a fuzzy self-tuning PID control model; the sewage treatment system is regulated and controlled through the control variables to reach the target working condition and the target effluent concentration. In the mode, the effluent concentration is automatically regulated and controlled, the regulation and control accuracy is improved, and the labor cost is reduced.

The invention provides an energy-saving compressor intelligent self-adaptive control system based on multi-sensor fusion, which belongs to the technical field of industrial compressor intelligent control and comprises a data acquisition module, a signal conditioning module, a multi-sensor information fusion module, an intelligent control decision module, an execution driving module and a system power supply management module. A state display alarm and remote communication module can be additionally arranged. Multiple sensors collect operation and environment parameters of the compressor, and after conditioning, a comprehensive state evaluation result is generated through D-S evidence theory or fuzzy logic fusion; the intelligent module generates a control instruction based on a load prediction algorithm and a fuzzy PID self-tuning strategy, and the execution module drives the compressor to act; the power supply module supports solar power supply and multi-power supply switching. The system overcomes the limitation that a traditional compressor is single in sensing, rigid in control and the like, comprehensive sensing, accurate evaluation and self-adaptive energy-saving control are achieved, the operation stability is improved, and the energy consumption and the operation and maintenance cost are reduced.

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

The application discloses a kind of composite brake anti-lock control system and method, belong to the technical field of automobile brake anti-lock system, a kind of composite brake anti-lock control system, including sensor unit, wheel slip rate deviation calculation unit, electronic mechanical brake ideal braking torque calculation unit, power motor controller assembly and anti-lock braking system assembly;The power motor controller assembly is connected with four power motors, each the power motor is connected with corresponding electronic mechanical brake, anti-lock braking system assembly includes fuzzy PID controller, composite braking system and torque distribution unit.The application detects when wheel slip rate has the tendency of lock, first macroscopically adjusts electronic mechanical braking force to the vicinity of road adhesion limit, while using fuzzy self-tuning PID control to adjust small range to regenerative braking torque, wheel speed fluctuation is very small in whole braking process, and vehicle has good braking smoothness.

The present invention provides a method, device, electronic device, and medium for controlling the effluent concentration of a sewage treatment plant, including: a method for controlling a sewage treatment system, comprising: obtaining water quality parameters of the sewage treatment plant's influent and the actual operating conditions of hydraulic operating conditions; determining the effluent concentration based on the water quality parameters and a pre-established bidirectional long-short-term memory neural network; establishing a fuzzy rule base based on the actual operating conditions, effluent concentration, a preset target operating condition, and a preset target effluent concentration; setting a fuzzy self-tuning PID control model based on the fuzzy rule base; determining control variables using the fuzzy self-tuning PID control model based on the actual operating conditions, effluent concentration, the target operating condition, and the target effluent concentration; and controlling the sewage treatment system using the control variables to achieve the target operating condition and target effluent concentration. In this method, the effluent concentration is automatically controlled, improving control accuracy and reducing labor costs.

The invention discloses a frequency modulation system of a fused salt energy storage coupling thermal power generating unit, belongs to the technical field of frequency modulation of power systems, and aims to solve the problems of low frequency modulation response speed, low energy storage efficiency and insufficient system coordination of the conventional thermal power generating unit. The system comprises a fused salt energy storage subsystem, a thermal power generating unit main system, a coupling heat exchange device, a power grid frequency monitoring module and a frequency modulation coordination control system, wherein the fused salt energy storage subsystem realizes efficient heat energy storage and release through a layered fused salt storage tank, a fused salt circulating pump, a heat exchanger and an auxiliary electric heating device; the thermal power generating unit main system is responsible for conventional power generation; the coupling heat exchange device injects fused salt heat energy into the main steam pipeline, and the steam enthalpy value is increased; the power grid frequency monitoring module collects frequency data in real time and calculates deviation; the frequency modulation coordination control system dynamically adjusts the fused salt flow and the operation mode through a fuzzy self-tuning PID unit, a heat exchange optimization distribution unit and a state judgment module, and three modes of quick response, combined frequency modulation and conventional stability are achieved.

This invention belongs to the field of power system technology and discloses a method and system for managing three-phase voltage imbalance in low-voltage distribution areas through a combination of composite commutation and active compensation. The method includes: acquiring and preprocessing three-phase voltage and current signals of the distribution area; tracking the grid phase and frequency through a phase-locked loop to generate discrete sampling steps; extracting the negative-sequence voltage component and calculating the imbalance index, then smoothing and anti-jittering to generate a management demand signal; calculating a reference value for the negative-sequence compensation current based on the negative-sequence voltage component and the equivalent negative-sequence impedance of the distribution area; using the error between the reference value and the actual negative-sequence current as input, employing a composite control strategy of fuzzy self-tuning PI and adaptive repetitive control in parallel to generate modulation commands to drive the parallel compensation device to inject negative-sequence current; and executing commutation scheduling when triggering conditions are met. This invention, through the coordinated management of commutation and active compensation, reduces the capacity occupancy of the compensation device and improves the tracking accuracy of the negative-sequence current and the adaptability to the grid frequency.

Provided in the present application are a SOC correction method and SOC correction apparatus for a charging termination stage of a battery. The method comprises: when it is determined, by means of a battery management system and a charging current of a battery, that the battery is currently in a charging state, and the temperature of the battery is within a preset temperature range, acquiring a terminal voltage of the battery; on the basis of the terminal voltage and a starting correction voltage threshold value of a charging termination stage, determining a current charging stage of the battery; and when the current charging stage of the battery is the charging termination stage, on the basis of the terminal voltage, acquiring a target SOC value corresponding to the battery, and on the basis of an error between an actual SOC value and the target SOC value of the battery, using a fuzzy self-tuning PID control algorithm to correct the actual SOC value, so as to obtain a corrected SOC value of the battery. By means of the method and apparatus, a fuzzy self-tuning PID control algorithm is used to correct an overestimated SOC point in advance, such that the overestimated SOC point smoothly approaches a target SOC value, thereby realizing accurate SOC estimation.

The invention discloses a multi-channel temperature automatic cooperative control method and system based on fuzzy decision. The method comprises the following steps: constructing a virtual reference sensor network based on a digital twinning and lightweight large model; establishing a coupling energy flow model, and performing self-adaptive identification on the dynamic coupling relationship when the multiple temperature control channels continuously and normally operate; a double-layer predictive fuzzy decision model is constructed, set point tracks of all channels are coordinated under multiple targets, and global temperature set point dynamic optimization based on fuzzy decision is achieved; establishing a control strategy combining fuzzy self-tuning PID and dynamic coupling feedforward; according to the method, multi-model fusion perception, fuzzy decision and dynamic coupling compensation are introduced, so that the problems of large coupling interference, difficulty in parameter setting and poor long-term precision in the existing multi-temperature-zone cooperative control are effectively solved, and the system health degree is evaluated by utilizing a multi-dimensional health degree index and utilizing a large model to drive parameter cluster adaptive evolution. And the control precision of the multi-temperature-zone cooperative control system is improved.

This invention relates to an intelligent control system for an electromagnetic wave water processor, belonging to the field of water treatment technology. It includes a multi-parameter detection module, an electromagnetic wave generation module, a frequency sweep optimization module, a fuzzy self-tuning control module, and a mode-coordinated controller. The multi-parameter detection module collects water temperature, conductivity, pH value, and flow velocity in real time; the frequency sweep optimization module scans and determines the optimal operating frequency for the current water quality; the fuzzy self-tuning control module generates frequency adjustment amounts based on real-time changes in water quality parameters for closed-loop regulation; and the mode-coordinated controller realizes a dynamic coordinated closed loop of frequency sweeping, tracking, and re-sweeping. This invention, through deep coordination of frequency sweep optimization and fuzzy self-tuning control, combined with pre-compensation and adaptive frequency sweeping stepping, has the advantages of strong water quality adaptability, stable treatment effect, and optimized energy consumption.

The application discloses a kind of based on dual-mode collaborative control's intelligent dosing optimization method of water supply project, it includes S1, obtains the water quality and quantity data of water supply system and the monitoring index of water supply system operating state in multiple successive control cycles close to current control cycle;S2, according to monitoring index and water quality and quantity data, determine whether the operating state of water supply system is in stable state, if yes, enter step S4, otherwise enter step S3;S3, the control amount of dosing pump in current control cycle is calculated using fuzzy self-tuning PID algorithm;S4, determine dynamic prediction time domain adjustment rule, input water quality and quantity data in time domain into machine learning model, and the control amount of dosing pump is obtained using model predictive control MPC algorithm;S5, according to the control amount of dosing pump of step S3 or step S4 control dosing pump to add reagent to clean water pool, and when water supply system is in operating state, and current control cycle is completed, return to step S1.

The invention provides an equipment self-stabilization control system and method, and the system comprises a data collection module and a control module, and the control module comprises a data preprocessing unit, a speed loop feedforward control unit, a speed loop instruction generation unit, a position loop feedback control unit, and a carrier-pointing motion coupling model calculation unit. The speed loop control comprises carrier gyroscope feedforward input, fuzzy self-tuning and first-order low-pass filtering processing; position loop control comprises fuzzy self-adaptive PID and gradient descent method optimization, collaborative optimization of motion compensation and accurate pointing of an equipment station body is achieved through independent control over a speed loop and the position loop, the station body pointing overshoot is reduced to 12% from 35%, the adjusting time is shortened by 60%, the steady-state error is reduced to 0.12 mrad from 0.75 mrad, and the speed loop and the position loop are independently controlled. The problems of insufficient dynamic response and reduced pointing precision of a traditional system in a complex motion environment are solved. According to the invention, a position-speed double-loop control architecture is adopted, and Kalman filtering and fuzzy parameter self-tuning technologies are combined, so that the stability and adaptability of the system are improved.