34 results about "Step response" patented technology

The invention relates to the technical field of response time testing of electro-hydraulic proportional valves, and discloses a response time testing method and system of an electro-hydraulic proportional valve, and the method comprises the steps: collecting multi-point pressure, step response, pipeline length and medium parameters, and unifying the time reference to obtain an original pressure sequence; constructing an inverse filter spectrum to remove damping interference so as to recover a sharp peak value; lagging offset is calculated according to pipeline and medium parameters, time delay compensation is carried out, and an alignment sequence is obtained; intercepting a non-stationary segment to eliminate residual delay deviation; constructing a response dynamic data set, extracting harmonic frequency domain representation, and reconstructing a pressure sequence through inverse transformation and superposition of compensation factors; and calculating a deviation integral quantity, adjusting a dynamic compensation parameter, performing weighted correction, and outputting an optimized reconstruction response sequence. According to the method, accurate reconstruction of the real pressure response of the proportional valve can be realized, so that the accuracy and the reliability of response time testing are improved.

The invention discloses a single-loop droop control method and system for a wind generating set, and the method comprises the following steps: constructing a doubly-fed fan-power converter-power grid three-module coupling model, and completing the dynamic adaptation of the characteristics of a doubly-fed fan of a single-loop droop control architecture without inner-loop current control; based on the input signal-model collaborative integration body and the adaptive architecture, MIMO-GBC is adopted to analyze a phase margin and a resonance peak value of an open-loop transfer function matrix eigenvalue of a dynamic small signal model, and double risks are identified in a full slip rate interval; aiming at the resonance risk, a current induction type virtual impedance strategy is adopted; aiming at insufficient phase margin, adopting a transient phase calibration strategy; and according to the real-time slip ratio of the DFIG and the stator power change, inter-partition linkage optimization is carried out on the virtual resistance and the phase calibration angle so as to minimize a dual-power step response fluctuation square mean value, a parameter setting period and a rotor side converter control period are synchronously matched, and all-working-condition stable control is realized.

The invention relates to the technical field of industrial process automatic control, and discloses an automatic control method for a water sample analysis process, which comprises the following steps: establishing a unit step response reference model for representing a normalized standard track of a controlled object; iteratively searching an optimal amplitude scaling and time elastic factor in the two-parameter search space to minimize the fitting residual error of the reference model and the real-time data; the optimal amplitude scaling factor is utilized to determine a projection steady-state value to drive an execution unit, and the sampling interval is adaptively adjusted according to the optimal time elastic factor, the time elastic factor is introduced to realize closed-loop compensation of system kinetic parameter drift, a steady-state target can be accurately locked in an unbalanced state, and the stability of the system is improved. And the problem of control model mismatch caused by device aging or environment fluctuation is solved.

The invention belongs to the technical field of automation control, and particularly relates to a control parameter optimization method and system for a multistage reaction kettle, and the method comprises the steps: collecting key operation data of a series multistage reaction kettle at each moment in real time, and constructing an initial temperature sequence and an initial valve opening sequence after standardization and adaptive filtering denoising; indexes such as temperature fluctuation standard deviation are calculated based on the initial temperature sequence, the temperature deviation degree is obtained through normalized weighted fusion, and parameters such as the Arrhenius law and the actually measured temperature are combined to construct a reaction nonlinear strength index; on the basis of the index coupling initial valve opening degree sequence change rate, a model vector self-adaptive correction coefficient is obtained in combination with parameters such as a smooth factor; and correcting a basic step response vector controlled by the dynamic matrix by using the coefficient, solving an optimal valve opening adjustment amount, calculating an execution value, and outputting the execution value to an execution mechanism to complete regulation and control, thereby realizing full-cycle optimization of control parameters. According to the invention, the control accuracy of the multi-stage reaction kettle is improved.

This invention discloses a method for controlling the main steam temperature of a power generation boiler. The method includes collecting step response data of the main steam temperature of the power generation boiler, fitting the data using the least squares method, and establishing a mathematical model of the inertia region and lead-forward region of the main steam control channel of the power generation boiler. Then, a predictive compensation controller is introduced in the parallel feedback loop, and the lag component is separated as a separate term using a constant separation method. Next, the PID parameters are optimized using an artificial fish swarm algorithm, and the optimal solution is substituted into the original parameters. Smith predictive compensation control effectively eliminates the lag effect in the system model, shortens the system settling time, and the artificial fish swarm algorithm significantly improves the controller accuracy, effectively shortens the time for the system to reach the target value, reduces the system overshoot, and minimizes the impact of external disturbances.

The application provides a kind of steam turbine governing system electric power step response simulation error analysis method and device, it is related to electric power equipment performance detection field, including: according to the parameter sample of steam turbine governing system electric power step response, preset sample polynomial is fitted, corresponding peak power arrival time is obtained;According to the sample polynomial and historical sample of fitting, the starting step time and steady state entering time of the parameter sample are determined;According to the peak power arrival time, the starting step time and steady state entering time determine the parameter identification error of the steam turbine governing system electric power step response.The application can determine the parameter identification error of steam turbine governing system electric power step response.

The invention provides an electromechanical control system parameter optimization method and system based on an improved intelligent algorithm. The method belongs to the field of electromechanical control, and discloses a controller structure comprising an active resistance increasing control loop, a PID control loop and a series wave trap group. Aiming at the active resistance increasing control loop and the PID control loop, respectively constructing corresponding multi-target fitness functions in combination with respective control targets; an improved intelligent optimization algorithm is adopted, the value of the multi-target fitness function constructed in a minimized mode is used as an optimization target, collaborative optimization is carried out on parameters of all the control loops, and an optimized control parameter set is obtained; substituting the optimized control parameter set into the controller structure, and performing step response verification in a simulation environment; and deploying the multiple groups of optimized control parameters passing verification in an actual controller to realize real-time adaptive control of the electromechanical system according to different working conditions. According to the method, global optimal control parameters meeting complex constraint conditions can be quickly obtained.

The application relates to the technical field of industrial process automation control, and discloses an automatic control method for a water sample analysis process, which comprises the following steps: establishing a unit step response reference model representing a normalized standard track of a controlled object; iteratively searching for an optimal amplitude scaling and a time elasticity factor in a double-parameter search space, so that the reference model and real-time data are fitted to minimize residual errors; and determining a projection steady-state value by using the optimal amplitude scaling factor to drive an execution unit, and adaptively adjusting a sampling interval according to the optimal time elasticity factor. The application realizes closed-loop compensation for system dynamics parameter drift by introducing the time elasticity factor, can accurately lock a steady-state target under a non-equilibrium state, and solves the problem of control model mismatch caused by device aging or environmental fluctuation.

The invention discloses a fuzzy PID (Proportion Integration Differentiation) initial parameter setting method based on a step response model. The method comprises the following steps: step (1), system identification; step (2), fuzzy PID initial parameter setting; and (3) fuzzy PID dynamic control: performing real-time dynamic correction on the initial parameter group obtained in the step (2) through dynamic correction, and then outputting a control signal adaptive to the current working condition. The system can be directly transplanted to common control platforms such as industrial PLCs and single-chip microcomputers, can meet the requirements of various temperature control scenes such as industrial production, precision experiments and biomedical treatment, and has wide application prospects and popularization values.

This invention relates to the field of response time testing technology for electro-hydraulic proportional valves, and discloses a method and system for testing the response time of electro-hydraulic proportional valves. The method includes: acquiring multi-point pressure, step response, pipeline length, and medium parameters, and unifying the time base to obtain an original pressure sequence; constructing an inverse filter spectrum to remove damping interference and recover sharp peaks; calculating hysteresis offset based on pipeline and medium parameters to perform time delay compensation and obtain an aligned sequence; truncating non-stationary segments to eliminate residual delay deviations; constructing a dynamic response dataset and extracting harmonic frequency domain representations, and reconstructing the pressure sequence by inverse transformation and superimposing compensation factors; calculating the deviation integral, adjusting dynamic compensation parameters and weighting corrections, and outputting an optimized reconstructed response sequence. This method can achieve accurate reconstruction of the true pressure response of the proportional valve, thereby improving the accuracy and reliability of response time testing.

The invention discloses an electric engineering machinery metering pump flow response control method, equipment and a medium, belongs to the technical field of hydraulic control, and aims to solve the technical problems that a metering pump in an existing electric excavator is low in response speed, a hydraulic system has certain inertia delay, and accurate hydraulic control is not facilitated. The method comprises the steps that response demand calculation is conducted on the hydraulic oil energy demand in the constant displacement pump; energy output control under related main pump pressure and overflow protection is carried out on hydraulic oil energy requirements; the output energy of the constant delivery pump and the rotating speed of the motor are subjected to fitting prediction processing under the step response model, and an energy output dynamic prediction model is obtained; and carrying out selective calculation on the energy output dynamic prediction model under related control time domain length and prediction time domain length, carrying out feedback correction, rolling optimization and prediction error correction processing on the energy output dynamic prediction model, and outputting and obtaining an energy output response quantity related to motor rotation speed prediction control.

The application discloses a water flow control optimization method based on fishery environment dynamic monitoring and belongs to the technical field of control optimization, mainly including the following steps: constructing a fishery water flow PID control system, adopting an improved gray butterfly brood parasitism optimization algorithm to set parameters, and finally applying the best parameters obtained by optimization to a flow controller. The application utilizes reverse learning initialization to improve initial solution set coverage, gives individuals the ability to jump out of local extreme values through a Levy flight strategy, adopts a vector difference strategy to correct physical dimension and accelerate convergence, and applies a reverse defense restart mechanism to crack iteration stagnation by using spatial symmetry. The algorithm is applied to water flow PID parameter setting, reduces the overshoot and steady-state error of the system step response, shortens the adjustment time, and realizes precise dynamic control of the fishery environment water flow.

The invention provides a circuit fault diagnosis and protection system based on multi-parameter fusion, and relates to the technical field of circuit fault diagnosis and protection, and the system comprises a data collection module, a preprocessing module, a multi-parameter fusion diagnosis module, a protection execution module, a man-machine interaction module and a storage module. Five core parameters of the current, the voltage, the temperature, the power and the harmonic distortion rate of a circuit are collected, after Kalman filtering preprocessing, a fusion algorithm of weighted naive Bayes and an improved BP neural network is adopted for fault diagnosis, and in combination with a hierarchical protection mechanism, stepped response of early warning, current limiting and power failure is achieved. Experimental verification shows that the average diagnosis accuracy of the system on eight common faults such as overload, short circuit, poor contact and harmonic exceeding reaches 98.6%, the response time is about 7ms, the unnecessary shutdown frequency is reduced by 32%, compared with the prior art, the diagnosis reliability and the response speed are remarkably improved, and the system is suitable for multi-scene circuit protection of industrial control, an electric power system, electronic equipment and the like.

The present application relates to the technical field of electric data processing, in particular to a motor compressor fault diagnosis method and device based on multi-source data analysis. The method collects the direct current intensity sequence and vibration intensity sequence of the motor compressor, removes the baseline under the respective dimension data in the step response section, iteratively accumulates and analyzes each time in the step response section, and respectively obtains the current drive cumulative intensity signal and the mechanical vibration cumulative intensity signal; the maximum nonlinear hysteresis is determined through the matching process, the maximum hysteresis time corresponding to the maximum nonlinear hysteresis is taken as the reference, the drive power is queried back as the verification power, the verification power and the maximum nonlinear hysteresis are taken as the fault judgment reference, and the fault judgment is performed. The present application can effectively analyze the motor compressor fault from the two dimensions, take the verification power as the judgment constraint, avoid the influence of inductance working condition on the final fault diagnosis result, and improve the detection accuracy of the motor compressor fault.

According to existing practical engineering application, the invention provides a small signal model establishment method and system suitable for a four-port extra-high voltage direct current system and a medium, and the method comprises the following steps: constructing a first linear state-space equation of an LCC direct current line; respectively constructing control equations, phase-locked loop equations and quasi-steady-state equations of a rectification side and an inversion side, and converting the control equations, the phase-locked loop equations and the quasi-steady-state equations into second and third linear state-space equations; performing coordinate transformation on the output current to obtain an equation under an xy coordinate system; and all equations are combined to obtain a complete small signal model. According to the model, a linearized state-space equation is established based on an LCC quasi-static and control system mathematical model, the system stability is analyzed through characteristic values, and the correctness is verified through time domain simulation step response comparison. The model can be combined with other elements of the power system through a global unified coordinate system, is suitable for stability analysis of the power system containing four-port direct current, and provides reference for system operation planning.

This invention relates to the field of grid converter control technology, and more particularly to an adaptive hybrid synchronization control method for a grid converter, comprising an active power outer loop controller, a hybrid synchronization control link, and an adaptive link; the system control angular frequency in the active power outer loop controller serves as the system control angular frequency input to the adaptive link; the adaptive angular frequency adjustment output by the hybrid synchronization control link is connected to the active power outer loop angular frequency of the active power outer loop controller; and the adaptive link outputs the hybrid synchronization adaptive gain of the hybrid synchronization control link. This invention can adaptively adjust the equivalent damping of the system according to the system state, ensuring a sufficiently fast power step response during normal system operation, and providing sufficient equivalent damping to ensure transient stability when the system enters a fault state.

The invention discloses a limited angle motor position small closed-loop dynamic test method, which comprises the following steps of: 1, detecting position step response, measuring angle step response data under a position closed-loop condition, and analyzing and calculating a steady-state value, rise time, peak time, overshoot rate and steady-state precision of angle response; step 2, frequency response characteristic detection: measuring a time domain signal of limited angle motor angle response under a position closed-loop condition, and analyzing and calculating an amplitude-frequency characteristic and phase-frequency characteristic curve of angle quantity; step 3, detecting position following characteristics, measuring angle following data under a position closed-loop condition, and analyzing and calculating angle following lag time; the method optimizes and realizes testing and data processing of position step response, frequency response characteristics and position following characteristics according to the small closed-loop dynamic testing characteristics of the position of the limited angle motor, and can reduce gross errors and random errors, thereby providing a more accurate testing result.

The application provides a permanent magnet synchronous motor active disturbance rejection control method and controller based on a cascade observer and an exponential approach law, and belongs to the technical field of motor control. The method comprises the following steps: constructing a state space equation based on real-time operation state data; constructing a cascade linear extended state observer; using a front-stage reduced-order extended state observer to obtain a rough estimated value of total disturbance of the system and injecting the rough estimated value into a rear-stage linear extended state observer to track residual disturbance and obtain an accurate observation value of the total disturbance of the system; constructing a comprehensive error variable, performing nonlinear compensation adjustment, and outputting a feedback control amount; taking the accurate observation value of the total disturbance of the system as a feedforward compensation, combining the feedback control amount, obtaining a final control input amount, and applying the final control input amount to a permanent magnet synchronous motor driving system. The application shortens a speed step response by 40% without overshoot, shortens an anti-disturbance recovery time by 82%, and improves dynamic response performance and control accuracy of the motor driving system.

This invention discloses a server intelligent scheduling and control method, relating to the field of industrial process control technology. It addresses the control instability problems caused by thermal response lag and model time-varying behavior of the controlled object. First, the flow excitation and thermal response signals are synchronously differentially sampled. A recursive least squares method with a forgetting factor is used to identify the dynamic transfer function online, extracting the thermal response lag time constant and steady-state gain in real time. Then, based on the time constant, the stability of the step response is analyzed, the maximum input rheological rate is calculated, and a dynamic safe operating envelope domain is constructed by combining the thermal load boundary mapped by the steady-state gain. Under the constraints of this safe domain, a model predictive control objective function is established to solve for the optimal flow allocation and operating condition commands. Finally, a cooperative tracking algorithm drives the flow gateway and voltage module to achieve closed-loop control. The forgetting factor is corrected online using the state observer residual, eliminating model mismatch errors and achieving high-precision adaptive thermal safety control of the server cluster.

This invention discloses a method for parameter identification of a FOPDT model with a variable step response duration, comprising the following steps: S1: Initializing a custom matrix accumulation structure; S2: Real-time acquisition of the step response sampling time t, current output data y_current, and step input signal u_step of the FOPDT model, calculating the integral increment of the output data based on the trapezoidal integral formula, and updating the response integral value in the custom matrix accumulation structure in real time; S3: Constructing a 3D feature vector using the response integral value, the product of the step input signal and the sampling time, and a constant 1, and incrementally updating the 3×3 matrix elements in the 3×3 matrix element storage unit through the self-multiplication operation of the 3D feature vector, thereby achieving real-time iterative update of the 3×3 matrix elements. Temperature controllers equipped with the technical solution disclosed in this invention have significant advantages in control accuracy, start-up speed, and ease of operation, exhibiting outstanding product differentiation and competitiveness, and helping enterprises gain a favorable position in market competition.

The invention discloses a flexible gain scheduling control method for a deep peak regulation unit, and the method solves the problems that the dynamic characteristics of the unit are time-varying and a single model cannot be accurately described in a wide load range through carrying out an open-loop step response test under a plurality of typical working condition points and identifying a transfer function model. According to the method, the model integration type active disturbance rejection controller is adopted, and the transfer function model information obtained through identification is integrated into the extended state observer, so that the extended state observer can identify the inherent dynamic characteristics of the system more accurately. For a deterministic dynamic link, a control instruction can be directly fed forward through model information, the estimation lag of an observer is reduced, and the response speed of control tasks such as load tracking and pressure regulation is greatly improved. For nonlinear or time-varying characteristics, the model information can assist the extended state observer to more accurately separate dynamic and external disturbance / model mismatch in the model, so that the control precision is improved.

The application discloses a kind of distributed control method and system of multi-temperature zone quartz tube type furnace temperature, belong to furnace temperature control technical field.The method includes: based on real-time step response data, the prediction model of each temperature zone subsystem is established;Feedback correction is carried out using measured temperature error to obtain initial prediction output sequence;Quadratic performance index function is established and the minimum prediction error and control increment are taken as the goal to carry out rolling optimization;Adopting stepwise dynamic matrix control, the control increment sequence is constrained to equal ratio change form, combined with Nash optimal strategy iteration solution, the Nash optimal control increment sequence of each temperature zone is obtained and the first item is implemented.The application avoids single point failure and communication delay through distributed architecture, uses stepwise control increment constraint to suppress thermal coupling oscillation between temperature zones, introduces uncertain parameter matrix to enhance robustness, realizes the high reliability, high-precision coordinated control of multi-temperature zone quartz tube type furnace temperature.

The invention provides a collaborative optimization method and device for control parameters of network construction type equipment, and the method comprises the steps: S1, determining an identification sequence of to-be-identified control parameters according to a dual-loop control strategy of the network construction type equipment; s2, according to the identification sequence, the control parameters are identified in a field test and laboratory simulation cooperation mode; s3, on the basis of the identified control parameters, adjusting the identified control parameters by performing step response tests for multiple times until the response characteristics of the equipment meet preset requirements; s4, the optimized control parameters are synchronized to a laboratory simulation platform, multiple preset working conditions are simulated in the laboratory simulation platform, and the adaptability of the optimized control parameters under different preset working conditions is verified; and S5, if the verification result of the adaptability shows that the preset requirements are not met under the partial preset working conditions, repeatedly executing the step S3 and the step S4 until the adaptability verification is passed under all the preset working conditions.

The invention discloses a fishery environment dynamic monitoring-based water flow control optimization method, which belongs to the technical field of control optimization and mainly comprises the steps of constructing a fishery water flow PID (Proportion Integration Differentiation) control system, setting parameters by adopting an improved ash butterfly brooding parasitic optimization algorithm and finally applying optimal parameters obtained by optimization to a flow controller. According to the method, the initial solution set coverage rate is improved through reverse learning initialization, the capacity of jumping out of the local extreme value is given to an individual through the Levy flight strategy, the physical quantity outline is corrected through the vector difference strategy, convergence is accelerated, and iterative stagnation is cracked through spatial symmetry by applying a reverse defense restart mechanism. The algorithm is applied to water flow PID parameter setting, the overshoot and steady-state error of system step response are reduced, the adjusting time is shortened, and accurate dynamic control over the fishery environment water flow is achieved.

The invention discloses a self-adaptive composite high-precision pressure control algorithm and an implementation system, and belongs to the technical field of pressure control. According to the algorithm, a composite framework of adaptive segmentation PID + feedforward-feedback composite compensation + fuzzy logic dynamic correction is adopted, PID parameters are adaptively adjusted through range segmentation and deviation, and dynamic response and steady-state precision are balanced; the gas source pressure and temperature interference are pre-judged through feedforward compensation, and overshoot is suppressed through Kalman filtering noise reduction and integral separation in feedback compensation; pID parameters are corrected in real time through fuzzy logic, and load sudden change is adapted. The system for realizing the algorithm comprises an upper computer, an STM32H743 main control unit, a high-precision sensor, an actuating mechanism driving module and a proportional valve. The steady-state error is less than or equal to + / -0.001 MPa in the range of 0-1MPa, the step response time is less than or equal to 3ms, the anti-interference capability is high, parameters do not need to be manually adjusted, and the method is suitable for high-precision pressure control scenes such as semiconductor manufacturing, precise instruments, aerospace and the like.

The application discloses a system identification method based on subspace band constraint, and steps are as follows: collecting input and output dynamic data of a system and preprocessing; based on the preprocessed input and output dynamic data, a black box state space model containing the input and output dynamic data is identified through a subspace system identification method, and a state space matrix is obtained, the state space matrix comprises a state matrix, an input matrix and an output matrix; a constraint about the state space matrix is constructed through prior knowledge; the state matrix and the input matrix in the state space matrix are kept unchanged, and the output matrix satisfying the constraint is calculated, or the state matrix and the output matrix are kept unchanged, and the input matrix satisfying the constraint is calculated; a step response model of the system is calculated based on the state space matrix satisfying the constraint; and the step response model is fitted into a low-order transfer function model. Through the constraint using the prior knowledge in the subspace identification method, the identification accuracy is improved.

The present application belongs to the field of automation control technology, and particularly relates to a control parameter optimization method and system for a multi-stage reaction kettle, which comprises the following steps: collecting key operation data of a series multi-stage reaction kettle at each moment in real time, constructing an initial temperature sequence and an initial valve opening sequence after standardization and adaptive filtering denoising; calculating temperature fluctuation standard deviation and other indexes based on the initial temperature sequence, obtaining temperature deviation degree through normalized weighted fusion, and constructing a reaction nonlinearity strength index by combining the measured temperature and other parameters according to the Arrhenius law; coupling the initial valve opening sequence change rate based on the index, and obtaining a model vector adaptive correction coefficient by combining a smoothing factor and other parameters; correcting the basic step response vector of dynamic matrix control by using the coefficient, solving the optimal valve opening adjustment amount and calculating the execution value, and outputting to the actuator to complete the regulation and control, so as to realize the whole cycle optimization of the control parameters. The present application improves the control accuracy of the multi-stage reaction kettle.

The application provides a kind of adaptive deep learning predictive control method and device suitable for process industry.It includes: according to the historical control information of process industry, based on deep learning technology, the full-condition dynamic model of target control variable is constructed, based on the adaptive segmented algorithm of threshold, the change gain curve of full-condition dynamic model is segmented, and the segmented linear gain model is obtained;Determine the segmented linear variable constraint of segmented linear gain model, and determine the optimization goal of target control variable based on segmented linear variable constraint;Based on segmented linear gain model, the step response sequence of target control variable at the current working point is obtained, and the future control execution sequence of target control variable is predicted according to step response sequence and optimization goal.Solve the problem that the mapping relationship between control variable and controlled variable is usually constructed based on linear model in existing predictive control method, which cannot accurately reflect the nonlinear characteristics of control variable, and further leads to the problem of low accuracy of predictive control.

The application discloses a thermal power unit AGC load regulation method based on boiler thermodynamic characteristic modeling, relates to the technical field of thermal power generation, and comprises the following steps: collecting and preprocessing unit operation data, establishing a dynamic fouling heat resistance soft measurement model based on heat accumulation balance, and outputting a fouling heat resistance factor; a first-order inertia plus pure delay transfer function model is established in response to a main steam pressure to a boiler combustion rate instruction, the fouling heat resistance factor obtained in the first step is coupled into real-time calculation of an inertia time constant, and a time-varying dynamic inertia time constant driven by a fouling state is obtained; the time-varying inertia time constant is embedded into a dynamic matrix, a time-varying step response column vector is constructed, an AGC instruction is inversely solved to generate a heat accumulation compensation feedforward control sequence, a boiler combustion rate instruction is obtained by superimposing a current step of the feedforward sequence and a feedback regulation amount, coal and air volume are adjusted, a governing valve on a steam turbine side is adjusted in response to the AGC instruction, and the previous steps are executed on line and are rolled over to update the time-varying inertia time constant and the feedforward sequence in real time.