149 results about "Transfer function model" patented technology

The invention discloses a charging pile intelligent heat dissipation method and device based on heat conduction line optimization and a medium, belongs to the technical field of charging pile heat dissipation, and aims to solve the technical problem of how to avoid the defects of high thermal resistance, response lag and large energy consumption in a traditional charging pile heat dissipation scheme and improve the heat dissipation efficiency and operation reliability of a charging pile. According to the technical scheme, a heat conduction structure is optimized; deploying a thin film thermocouple and constructing a three-dimensional temperature field model through infrared thermal imaging; establishing a thermal resistance-flow-power transfer function model by adopting a fuzzy PID (Proportion Integration Differentiation) and model predictive control hybrid algorithm; historical charging data are analyzed based on an LSTM neural network, a power peak value is predicted 300 ms ahead of time, and heat dissipation equipment is pre-started.

The invention belongs to the technical field of production monitoring systems, and discloses a numerical control machine tool dynamic fault diagnosis method and system. The method comprises the following steps: generating a global time reference signal through a main shaft encoder and a clock synchronization protocol; the method comprises the following steps: collecting vibration data of a main shaft bearing in each unit time, current data of an electric cabinet and process parameters, and generating a preprocessed data sequence through transmission delay compensation and multi-rate frequency raising processing; inputting the vibration data and the current data into a preset mechanical-electrical transfer function model, and calculating a time delay parameter; performing phase alignment on the preprocessed data sequence based on the time delay parameter to generate an aligned data sequence; inputting the aligned data sequence into a time sequence neural network, and outputting a fusion feature vector; calculating a cross correlation coefficient of the fusion feature vector, and generating a fault diagnosis result based on a preset cross correlation threshold value; the problem of failure of fault feature extraction caused by data asynchronization in the prior art is solved.

The invention relates to the technical field of precision machining, in particular to a cutting force signal synchronous calibration method based on multi-sensor data fusion, which comprises the following steps of: 1, dynamically preprocessing acquired signals; step 2, constructing a reference time axis based on the spindle current signal, and realizing time domain alignment of multichannel signals by adopting a dynamic time warping algorithm; 3, establishing a feature incidence matrix containing a force-vibration-temperature coupling relation, and generating a fusion cutting force feature vector through frequency domain energy weight distribution; 4, a dynamic transfer function model is constructed, model parameters are updated in real time, and the fusion feature vector is mapped into a calibration cutting force signal; and 5, carrying out dynamic compensation on the calibration signal by adopting a nonlinear inverse compensation and residual modal screening strategy. According to the method, the accuracy of cutting force signals can be remarkably improved, errors and uncertainty in the machining process are reduced, and the production quality and efficiency are optimized.

The invention relates to the technical field of high-frequency multichannel synchronous transmission, in particular to a time domain reflection compensation design method for high-frequency signal transmission loss, which comprises the following steps of: 1, responding to a synchronous trigger signal to generate an active reflection reference signal with a determined time domain position; 2, aligning time marks between channels through cross-correlation operation; 3, extracting a reflection feature template of the channel from the alignment signal, and recognizing and eliminating crosstalk components through convolution operation with an adjacent channel template; 4, constructing a time-varying transfer function model according to the amplitude envelope attenuation characteristic and the carrier phase jump characteristic of the reflection characteristic template; and 5, generating a compensation filter based on the time-varying transfer function model, and verifying the compensation effect through secondary reflection. Through cross-correlation operation, accurate alignment of multi-channel signal time scales is realized, the time delay difference between different transmission channels is overcome, signal synchronization of each channel is ensured, and the beam forming precision is improved.

The invention discloses a robot track online compensation and precision control method and system based on multiple sensors, and belongs to the technical field of robot track control. The method comprises the following steps: acquiring target trajectory data and original data of each sensor, and performing time alignment on the original data of each sensor to generate a fusion data set comprising vibration acceleration data and pose data; performing time-frequency feature extraction based on the vibration acceleration data to obtain a dominant vibration frequency spectrum; constructing a mechanical transfer function model of the joint driving torque and the tail end vibration displacement; based on the mechanical transfer function model, constructing an adaptive notch filter to generate a feed-forward compensation sequence; according to the target trajectory data, the pose data and weight parameters, updated in real time, of the sensors, a trajectory fusion deviation value is obtained through calculation; and after the feedforward compensation sequence and the trajectory fusion deviation value are integrated, a joint driving current instruction is generated based on a fuzzy PID control algorithm. The robot trajectory control precision can be improved.

The invention relates to the technical field of attitude determination of a photoelectric pod of an unmanned aerial vehicle, in particular to an MEMS-IMU dual-mode correction attitude determination method for the photoelectric pod of the unmanned aerial vehicle. Comprising the following steps: establishing a damping system second-order transfer function model, and outputting an attenuation coefficient matrix; based on MEMS-IMU three-axis motion parameters, distinguishing a large maneuver turning state and a linear flight state; respectively compensating a roll angle, a pitch angle and a course angle of the MEMS-IMU by using the main inertial navigation according to different states; converting the corrected attitude angle into a quaternion, and optimizing and outputting a fused quaternion through a gradient descent method; taking the fused quaternion as an input, constructing a seven-dimensional state space model, and outputting an error compensation amount through Kalman filtering; dynamically adjusting the main inertial navigation weight according to the accelerated speed root mean square; and outputting a final attitude angle in combination with the error compensation amount and the weight, and verifying the final attitude angle through GNSS (Global Navigation Satellite System) position inversion. The method has the advantages that cross interference is avoided; therefore, the method is suitable for the photoelectric pod scene of the unmanned aerial vehicle.

The invention discloses a fuzzy neural network PID photovoltaic series welding temperature control method based on improved PSO optimization. The method comprises the steps that a target photovoltaic series welding equipment heating transfer function model is acquired; setting an initial PID parameter; adjusting a PID increment parameter of the PID control module in real time according to the temperature error, the temperature error change rate and a preset fuzzy rule base; the neural network is combined with fuzzy control, and parameters and rules of fuzzy control are automatically modified through training data; according to the photovoltaic series welding temperature condition, the fitness function of the PSO algorithm is improved, the adjustment mode of the inertia weight is improved, and the improved PSO algorithm is used for optimizing the initial PID parameters of fuzzy neural network PID photovoltaic series welding temperature control. Self-adaptive precise control and robust control of the welding temperature control system are achieved, the temperature fluctuation phenomenon in the photovoltaic series welding process is effectively improved, and the robustness and control reliability of the system are enhanced.

The invention provides a rapid detection and diagnosis method and system for a short-circuit fault of a transformer winding, and relates to the technical field of transformers, and the method comprises the steps: collecting the electrical parameters of the transformer winding, calculating equivalent impedance, building a transfer function model and an equivalent impedance model, and extracting a frequency domain fault characteristic quantity and a short-circuit force characteristic; and constructing a characteristic quantity judgment matrix to obtain a weight coefficient, carrying out multi-source information fusion by utilizing a D-S evidence theory, and realizing fault diagnosis by combining fuzzy comprehensive evaluation. The method can accurately identify the short-circuit fault type of the transformer winding, and improves the reliability and accuracy of fault diagnosis.

According to the correction calculation method for the rigid water hammer turbine model coefficient, the flow coefficient of the water turbine is defined by rated working condition parameters according to the concept of a water head of the water turbine, the flow is rewritten into a function of the guide vane opening degree and the water head of the water turbine, and the problem that the flow measurement difficulty of a hydropower station is large is solved; establishing a water turbine linearization model by adopting a water turbine output equation recommended by IEEE Working Group, and constructing an increment linearization model from the guide vane opening to the water turbine output in combination with a water turbine flow linearization equation; the influence of pipeline hydraulic loss is introduced into a rigid water attack transfer function, a water turbine output transfer function model under the pipeline rigid water attack is established, the model has the same form as a PSD-BPA water turbine model of the China University of Electricity, and a model correction coefficient can be directly calculated, so that the parameter calculation of the model is simplified, and the application is convenient.

The invention relates to a gas turbine system predictive control method, device, equipment and medium, and relates to the technical field of gas turbine control, and the method comprises the steps: building a transfer function model of a gas turbine system at a plurality of preset load points through a step response experiment, a prediction controller is designed based on the transfer function models corresponding to the different load points, so that a control increment output by the prediction controller is obtained, and the prediction controller comprises a plurality of sub-prediction controllers corresponding to the different load point models; correcting the control increment which does not accord with a preset constraint condition based on an improved He-Make algorithm; and based on the deviation between the control increment corresponding to each sub-prediction controller and the actual output value, performing weighting processing on the control increment sequence corresponding to each sub-controller by using an improved recursive Bayesian weighting algorithm to obtain a final control increment. According to the method, the operation stability and the response speed of the heavy duty gas turbine system can be remarkably improved, and the strong performance advantage is shown in the aspect of set value tracking.

The invention provides a wind speed calibration method for a wind generating set. The wind speed calibration method comprises the steps that the real-time standard wind speed at the current moment is obtained; determining a wind speed standard interval corresponding to the real-time standard wind speed, and calculating calibration parameters of a transfer function model according to the wind speed standard interval; and performing wind speed calibration on a wind speed sensor based on the calibration parameters, the real-time standard wind speed and the transfer function model to obtain a calibrated wind speed. According to the method, measurement errors caused by wind speed changes can be reduced, it is ensured that the wind speed sensor can keep stable performance under different wind speed conditions, the method adapts to various complex and changeable environments, the calibration process is more efficient and reliable, and therefore the control strategy of the wind generating set is further optimized, and the power generation efficiency is improved. The invention further provides a wind speed calibration system of the wind generating set, a computer readable storage medium and electronic equipment, which have the above beneficial effects.

The invention discloses a thermal working time lag process ADRC design method with time lag robustness. The thermal working time lag process ADRC design method comprises the steps that 1, a transfer function model of a first-order inertia time lag process of a thermal process is established; step 2, establishing a time-delay ADRC structure based on model information driving; 3, obtaining a proportional gain with expected closed-loop dynamic representation and a corresponding observer bandwidth setting rule through low-frequency approximation; step 4, scaling control parameters of the ADRC system according to the transfer function model established in the step 1, and setting default adjustment parameters of proportional gain and observation bandwidth; 5, carrying out equivalent two-degree-of-freedom conversion on the closed-loop system, analyzing the nominal stability of the ADRC system based on a double-track method, and obtaining a nominal stability domain of the control parameters; and step 6, in the nominal stability domain obtained in the step 4, according to the regularization rule of the ADRC scaling parameter and the demand of comprehensive robustness, obtaining the time constant of the low-pass filter in the compensation channel by establishing a monotonically decreasing amplitude curve of the time-delay ADRC open-loop Bode diagram.

The invention discloses a data-driven modeling and predictive control method for an electroslag remelting process with a time delay characteristic. The data-driven identification modeling is performed on the electroslag remelting process based on a mechanism relationship between the stroke of a servo motor encoder and the output position of a consumable electrode; converting the transfer function model into a standard linear regression form; estimating a nonlinear time delay parameter by using a one-dimensional search algorithm, and constructing an adaptive forgetting factor by using an estimated parameter change rate; an augmented state vector is introduced into a historical control input sequence, so that an original time-delay system is converted into an equivalent time-delay-free augmented state space model; phase lag caused by multi-source time lag is dynamically compensated through a rolling optimization mechanism, interference of uncertain factors is effectively restrained in combination with feedback correction, an optimal control sequence is obtained, and a controller is made to control an electroslag remelting system with strong nonlinearity and multi-time-lag coupling dynamic characteristics in real time through the optimal control sequence. The method has excellent tracking precision and good control stability in the electroslag remelting tracking control process.

The invention discloses a heat balance regulation and control method and device of a heat supply system and a medium, and relates to the technical field of automatic control of a central heating system.The method comprises the steps that based on a preset time interval, heat supply operation data, heat exchange operation data of all heat exchange stations and room temperature data of user nodes are collected, and the current heat supply working condition of the heat supply system is determined; inputting the heat exchange operation data into a preset extended transfer function model, and calculating a core parameter set of each heat exchange station based on the identification frequency corresponding to the current heating working condition; calculating a control parameter of a primary side valve of each heat exchange station node, and generating an opening degree adjustment amount; performing hierarchical coordination constraint verification on the control parameters and the opening degree adjustment amount to generate an opening degree regulation and control instruction of the primary side valve; and executing the opening regulation and control instruction, regulating the opening of the corresponding primary side valve, and collecting updated data after regulation. And on the premise of ensuring that the heating quality of a user continuously reaches the standard, autonomous optimization and long-term stability of operation of the heating system are realized.

The invention relates to the technical field of communication network maintenance, and discloses a communication network operation quality monitoring and closed-loop operation and maintenance scheduling management system, which comprises an acquisition unit for acquiring network element telemetry data; the observation module extracts a flow fingerprint, converts a link into a transfer function model, and generates a consistency gradient vector according to singular point offset; the echo prediction module converts the scheduling instruction into an expected gradient offset vector; the module calculates the scheduling residual error of the actually measured offset and the expected offset; the decision-making unit generates a path reconstruction instruction, and the scheduling residual error is utilized to check the execution efficiency and update the operation reference; according to the invention, the flow conduction consistency constraint is anchored, the link degradation characteristic and random fluctuation decoupling is realized, and the transient interference generated by the scheduling action is eliminated.

The invention discloses a lithium battery system state-of-charge estimation method based on a Hammerstein model, and the method comprises the steps: constructing a second-order RC circuit equation of a lithium battery, describing a dynamic linear module of the Hammerstein model through a noise transfer function model, and constructing a lithium battery system through a static nonlinear module of an adaptive neural fuzzy network; designing a Gaussian signal, inputting the Gaussian signal into the agent model of the lithium battery system to obtain corresponding Gaussian signal output, and decoupling the static nonlinear module and the dynamic linear block by using the covariance function characteristic of the Gaussian signal; identifying parameters of the noise transfer function model by using a least square method based on a covariance function, solving parameters of the adaptive neural fuzzy network by using a crown porcupine optimization algorithm, and updating the weight of the adaptive neural fuzzy network by using a stochastic gradient algorithm with a forgetting factor; and constructing an OCV-SOC curve of the open-circuit voltage and the state of charge by adopting polynomial fitting, and taking output obtained by the Hammerstein model as input of the polynomial fitting to obtain an estimated value of the state of charge SOC.

The invention discloses an unbiased model predictive control method for an SCR (Selective Catalytic Reduction) denitration system based on dynamic variable gain Kalman filtering. The unbiased model predictive control method comprises the following steps: establishing an augmented state space model of an SCR system; establishing a k-step forward prediction model; constructing a performance index optimization function; designing a Kalman filter for dynamically adjusting the gain according to the information; it is proved that model prediction control based on dynamic variable gain Kalman filtering can realize unbiased tracking of a set value in a steady state; for an SCR denitration system, a transfer function is used for describing the relation between the ammonia spraying amount and the NOx concentration of an outlet, and a control variable value obtained through calculation of the control method is output into a transfer function model. According to the method, the speed and accuracy of disturbance estimation are improved, the controller can act in time after disturbance changes on the basis of realizing unbiased tracking of the set value, the negative influence of the disturbance is suppressed, and the disturbance suppression effect is improved.

The invention relates to the technical field of power system frequency modulation control, in particular to a method for improving the frequency modulation technology through electric heating linkage of a thermal power plant. According to the technical scheme, the method for improving the frequency modulation technology through electric heating linkage of the thermal power plant comprises the following steps that S1, a multi-input first-order inertial transfer function model of dynamic response of a heat supply network is established through a heat source side step test and a system identification method; s2, constructing a multivariable cooperative control model, including an energy correlation model of a thermal load and a steam extraction amount, a linear relation model of the steam extraction amount and an electrical load, and a control model of the electrical load and a valve opening degree; and S3, implementing an electric heating linkage frequency modulation control strategy, triggering dynamic feed-forward compensation according to a homodromous judgment result of the AGC instruction and the power grid frequency deviation, performing hierarchical response control based on the rotating speed deviation, linking a heat supply network quick-closing valve, and generating a weighted heat supply correction instruction. Deep cooperation of heat supply network energy storage and power frequency modulation is achieved, and the frequency modulation performance of the unit is remarkably improved.

The invention discloses a grid-connected stability analysis method for a multi-converter system, and the method comprises the steps: building a transfer function model from the voltage amplitude-phase disturbance to the power harmonic disturbance of a converter port based on the admittance characteristics of converters, the conversion relation between the voltage / current amplitude-phase disturbance and the positive and negative sequence disturbance, and the power disturbance decomposition relation; simplifying the voltage-power harmonic models of the plurality of converters and connecting lines step by step through series aggregation operation and parallel aggregation operation to generate a grid-connected point single-port voltage-power harmonic transfer function model; and combining the grid-connected point single-port model with a power grid side voltage-power harmonic transfer function model, and judging the system stability according to the origin surrounding property of a Nyquist curve of a joint transfer function determinant.

The invention relates to a flexible connection load transfer function identification method based on active frequency sweep excitation, and relates to the field of spacecraft attitude control, and the method comprises the following steps: a plurality of three-super platform actuators sequentially output sine frequency sweep excitation moments of a load in three rotation directions, and a high-bandwidth fiber-optic gyroscope simultaneously measures the triaxial angular velocity of the load; the obtained time domain result is converted into a frequency domain result, and then load transfer function model identification is carried out; and adjusting controller parameters in the three-super platform control unit based on the identification model so as to increase the control bandwidth and improve the secondary control capability on the basis of ensuring the stability margin of the controller in the three-super platform control unit. And a technical basis is provided for ultrahigh-precision pointing, ultrahigh-stability control and high-quality imaging of optical loads of spacecrafts in the future.

The present invention discloses a design of an unmanned aerial vehicle hovering experimental platform and a frequency domain identification method. The method provided by the present invention comprises: inputting a first logarithmic frequency sweep signal and a first dipole square wave signal to the unmanned aerial vehicle at the hovering point, collecting the output data of the unmanned aerial vehicle; preprocessing the output data to obtain input and output frequency response data, respectively obtaining the parameter values of the transfer function model and the parameter values of the state space model; and then performing time domain verification on the transfer function model and the state space model. The present invention utilizes the frequency domain identification method to decouple the data between axes in the frequency domain, and can select a suitable amount of data for identification within a reasonable frequency range, thereby improving computational efficiency and making up for the shortcomings of the time domain identification method.

The present application relates to a method for modeling the transfer characteristics of a DC measurement device using MMC impedance. The method comprises: constructing a differential and common-mode time-domain small-signal model of the MMC main circuit based on Kirchhoff's voltage law; deriving a coupling law based on the frequency coupling characteristics and phase sequence coupling mechanism of the differential and common-mode time-domain small-signal model; converting the differential and common-mode time-domain small-signal model into an HSS-MMC main circuit model based on the coupling law; establishing various control HSS models based on the MMC control loop structure; deriving a transfer function model of the DC voltage measurement device to update the DC voltage control HSS model; combining the various control HSS models with a modulation wave expression to obtain an MMC control system HSS model; jointly combining the HSS-MMC main circuit model and the MMC control system HSS model to obtain a MIMO admittance model; obtaining a SISO equivalent impedance model of the MMC based on the grid impedance expression and the MIMO admittance model; and solving an impedance analytical value using the MMC SISO impedance model based on MMC system parameters and control gains for different frequency disturbances. The method accurately describes the high-frequency impedance characteristics of the MMC.

The invention provides a grid-connected hydroelectric system ultralow frequency oscillation damping joint parameter optimization method based on deep reinforcement learning model identification. The method comprises the following steps: constructing a hydroelectric generating set speed regulation model; defining other models of the power system except the hydroelectric generating set in the hydroelectric system as external system models, and identifying a transfer function model of the external system models by adopting a deep reinforcement learning algorithm, so as to obtain a relationship between the guide vane opening degree of the hydroelectric generating set in the hydroelectric system and the system frequency response; based on a hydroelectric generating set speed regulation model and an external system model, an additional damping controller is used as one of control links of a speed regulator, the additional damping controller and the speed regulator are regarded as a whole, and parameters of the speed regulator and parameters of the additional damping controller are optimized based on a chaotic particle swarm algorithm. According to the method, the phase compensation of the mechanical torque of the hydroelectric generating set is realized on the whole through parameter joint optimization, and the damping characteristic of the set is improved, so that the ultra-low frequency oscillation is effectively inhibited.

The invention discloses an improved Smith control method for a maritime lightering device, and the method comprises the following steps: S1, building a maritime lightering device kinematics equation based on kinematics analysis; S2, solving a maritime lightering device inverse kinematics equation according to the kinematics equation; s3, a hydraulic servo system is considered, and an offshore lightering device transfer function model is established; s4, designing an improved Smith control method, and constructing an output delay observer; and S5, realizing wave compensation and active operation of the lightering device by using an inverse solution control method, and correcting the tail end position of the lightering device by using the output of the improved Smith controller. According to the method, the problem of control residual errors existing in a classical Smith estimation compensation method can be solved, and therefore it is guaranteed that a maritime lightering device can rapidly and accurately compensate ship swaying motion caused by marine environment disturbance.

The present application relates to the technical fields of spectral analysis and computer technology, and discloses a freeze-thaw soil spectral correction method, device, storage medium, and computer equipment. The method includes: obtaining the in-situ spectral reflectance curve of freeze-thaw soil and determining the spectral reflectance group to be corrected corresponding to each band; based on the freeze-thaw soil spectral reflectance correction model and the spectral reflectance group to be corrected, restoring and correcting the spectral reflectance of each band within a preset band range to obtain a corrected spectral reflectance curve. The freeze-thaw soil spectral reflectance correction model is a transfer function model implemented based on a random forest model. Aiming at the problem of spectral information distortion caused by multi-factor changes during the freeze-thaw process of soil, the freeze-thaw soil spectral reflectance correction model can effectively correct the in-situ spectral reflectance curve of freeze-thaw soil, thereby improving the estimation accuracy of surface soil parameters in the freeze-thaw season.

This invention provides a method for the actual calculation of the inertial time constant of water flow in a hydropower unit. It defines a time-invariant inertial time constant based on rated operating parameters; establishes a rigid water hammer transient transfer function that includes the effects of pipeline hydraulic losses and the inertial time constant, thus avoiding the difficulties in measuring large-diameter flow rates in hydropower stations; establishes a transfer function model between the guide vane opening increment and the volute pressure increment based on the rigid water hammer transient transfer function; and establishes a calculation formula for the inertial time constant based on the measured transient data of the guide vane opening increment and the volute pressure increment, using the transfer function model. By performing tests and calculations near rated operating conditions, this method avoids the difficulty in calculating the overflow coefficient due to guide vane opening deviation, and solves the measurement difficulties caused by the fact that the influence of the inertial time constant only exists in the transient process and disappears in steady state.

The present invention proposes a control method, device, electronic device, and storage medium for a piezoelectric nanopositioning system based on rolling optimization, belonging to the field of precision electromechanical control technology. The method comprises: establishing a high-order transfer function model of a piezoelectric nanopositioning system and identifying the model parameters through a frequency sweep method; secondly, converting the model into a high-dimensional state space model, designing optimal control indicators, constructing a finite-time rolling optimization control problem, and improving the tracking capability of the piezoelectric nanopositioning system; finally, converting the rolling optimization control problem into a quadratic programming problem, and designing a coordinate descent method to accelerate the online calculation of the optimal control and ensure that the optimal control input satisfies the state and input constraints of the system. The method of the present invention can solve the problems of existing piezoelectric nanopositioning systems, such as the low order and limited expression capabilities of mathematical models, the narrow bandwidth of control methods, and the difficulty of digital implementation, thereby improving the ability of piezoelectric nanopositioning systems to track high-frequency reference instructions and being suitable for engineering applications.

This invention relates to an intraday MPC scheduling optimization method for combined cooling, heating, and power (CCHP) microgrid systems. The purpose of this invention is to overcome the shortcomings of existing technologies and propose an intraday MPC scheduling optimization method for CCHP microgrid systems. The technical solution of this invention provides an intraday MPC scheduling optimization method for CCHP microgrid systems, comprising: S1, constructing transfer function models for each device in the microgrid system; S2, constructing a custom constraint set based on the energy constraints of each device; the energy constraints include capacity; S3, using the sum of the standard cost function and the custom cost function as the final optimization objective function; S4, setting appropriate time intervals, prediction time domains, and control time domains, and employing a sequential quadratic programming optimization algorithm to achieve MPC optimized scheduling calculations. This invention is applicable to the field of energy dispatching technology.

The invention provides a reheated flue gas baffle control method and system based on feedback correction, and relates to the technical field of thermal power generation. The method comprises the following steps: selecting dynamic characteristic data based on preprocessed historical operation data of a unit, establishing a dynamic characteristic transfer function model, and determining a progressive superposition control variable quantity; determining a baseline feedforward control value of the current unit, and performing baseline feedforward control to serve as initial input; feedforward compensation is conducted according to the outlet temperature change trend of the first temperature reheater, first feedforward control is executed, and a first control variable quantity obtained based on the first feedforward control influence is determined; and according to the outlet wall temperature change of the second temperature reheater, deviation correction is carried out, second feedforward control is executed, a second control variable quantity is determined, weighted stacking calculation is further carried out, a final control signal is generated, and a reheated flue gas baffle is controlled to carry out corresponding operation. The opening degree of the reheating flue gas baffle is accurately adjusted, and the temperature fluctuation quantity of the reheater is effectively reduced.

The invention discloses a photovoltaic grid-connected inverter parameter multi-objective optimization design method, system and device and a storage medium, and belongs to the technical field of new energy grid connection, and the method comprises the steps: constructing a control frame of a photovoltaic grid-connected inverter system, and the control frame comprises a filter and a controller; establishing a harmonic content model for representing the harmonic content of the output current of the system and a transfer function model for representing the dynamic response characteristics of the system based on the control framework; preliminarily determining a feasible region of filter parameters according to the electrical indexes, and determining a final feasible region of the filter and controller parameters based on a transfer function model; establishing a multi-dimensional optimization objective of the system, and solving a multi-dimensional optimization objective function to obtain optimal parameter configuration of the system; the method can achieve the collaborative optimization of harmonic suppression, dynamic adjustment time, steady-state control precision and filter cost, balance performance and economy, flexibly adapt to different engineering priority requirements, can be directly applied to engineering design, and improves the comprehensive operation performance of a photovoltaic grid-connected system.