48 results about "Error coefficient" patented technology

The invention belongs to the technical field of phase control cabinet phase regulation and control, and particularly relates to a phase control cabinet regulation and control system and method based on multistage phase compensation. According to the method, the voltage waveform and the current waveform output by the phase control cabinet are preliminarily compensated so as to reduce the initial phase deviation, environmental parameters are matched with a pre-stored interference feature library, the type of an interference source can be identified, and the interference source is quantified as a thermal noise contribution value to calculate an interference intensity prediction value in a prediction window, so that the prediction accuracy is improved. And then providing data support for secondary compensation through a phase residual error output by an interference intensity predicted value, determining a compensation gain parameter according to a dynamic error coefficient during secondary compensation, performing secondary compensation on a voltage waveform and a current waveform to enable a phase deviation to be converged to a preset range, and according to the phase convergence information after secondary compensation, determining the interference intensity predicted value according to the phase convergence information after secondary compensation. And the sampling frequency and the compensation weight factor of the sensor array are reversely adjusted to form a closed-loop compensation control link, so that continuous optimization and improvement of the compensation process are realized.

The invention discloses a pressurized water reactor primary loop boron concentration prediction and control method and system, and the method comprises the steps: obtaining an original helium flow sequence of a pressurized water reactor primary loop, and obtaining M boron concentration IMF components IMF1,..., IMFM; the M boron concentration IMF components IMF1,..., IMFM are put into a trained LSTM model for prediction, predicted values Y1, Y2,..., YM of the IMF components are obtained, and error coefficients delta Y1, delta Y2,..., delta YM corresponding to the boron concentration IMF components are calculated according to the predicted values Y1, Y2,..., YM of the IMF components; and inputting error coefficients delta Y1, delta Y2,..., delta YM corresponding to each boron concentration IMF component into the trained DenseNet prediction model to obtain an optimal IMF component predicted value # imgabs0 # of the boron concentration signal sequence, based on a DEM-DAC algorithm, controlling the boron concentration of the pressurized water reactor primary loop according to the optimal IMF component predicted value # imgabs1 # of the boron concentration signal sequence, and calculating the boron concentration of the pressurized water reactor primary loop according to the optimal IMF component predicted value # imgabs0 # of the boron concentration signal sequence. The method and the system can solve the technical problems that the boron concentration fluctuation of the primary loop is large and the unit load regulation performance is poor during the reactor variable load operation period.

The invention provides an intelligent phase control vacuum circuit breaker health degree assessment method and device and a circuit breaker, and relates to the technical field of circuit breaker health assessment, and the method comprises the steps: carrying out the vacuum degree detection of an arc extinguish chamber in an intelligent phase control vacuum circuit breaker, and obtaining the vacuum degree; performing heating analysis on the vacuum circuit breaker according to the vacuum degree to obtain a heating parameter, and performing zero crossing point monitoring error analysis to obtain a zero crossing point error coefficient; according to the operation time parameter of the vacuum circuit breaker, mapping to obtain a mapping zero-crossing point error coefficient, calculating to obtain a zero-crossing deviation coefficient, and according to the zero-crossing deviation coefficient and an analysis deviation coefficient of heating analysis and zero-crossing point monitoring error analysis, carrying out confidence degree processing to obtain a zero-crossing confidence degree; and distributing a weight according to the zero-crossing confidence coefficient, and performing health degree calculation based on the vacuum degree and the zero-crossing point error coefficient to obtain the health degree of the vacuum circuit breaker. The technical problem of inaccurate health degree evaluation of the intelligent phase-controlled vacuum circuit breaker in the prior art is solved.

A calibration circuit for correcting timing errors introduced by a DAC in a signal path of an ADC, the calibration circuit comprising: an input subtraction module configured to subtract an estimated error from an output of the ADC and provide a corrected output; a filter module configured to approximate an error transfer function corresponding to the DAC timing errors; a correlation module configured to correlate the corrected output with an output from the filter module to extract an error term; an integrator module configured to integrate the error term to provide an updated error coefficient; and a correction module configured to correlate the updated error coefficient with the output from the filter module to provide the estimated error to the input subtraction module.

The invention discloses a reactor control rod position control method and a related device, and the method comprises the steps: obtaining an original rod position sequence of a reactor control rod, decomposing the original rod position sequence, and obtaining M IMF components; inputting the M IMF components into a trained long short-term memory network model to obtain predicted values X1, X2,..., XM of the M IMF components, establishing an error evaluation index D-SMAPE according to the predicted values X1, X2,..., XM of the M IMF components and actual values thereof, and obtaining error coefficients delta Y1, delta Y2,..., delta YM corresponding to SWT-LMD subsequences; inputting the error coefficients delta Y1, delta Y2,..., and delta YM into a trained ResNet prediction model to obtain final IMF component prediction values Y1, Y2,..., and YM of the original rod position sequence; and controlling the control rod to act according to the final IMF component predicted values Y1, Y2,..., YM of the original rod position sequence. According to the method and the related device, the rod position of the reactor control rod can be accurately controlled.

The invention discloses a gyro accelerometer dynamic error modeling and calibration method considering angular motion of a base, and belongs to the field of dynamics and control. The implementation method comprises the following steps: establishing kinematics and dynamics equations of the PIGA under the triaxial angular motion of the base, and deducing a complete error model comprising a static error term, a dynamic error term and a nonlinear error term; constructing a kinetic equation including inertia tensor, a moment balance equation and servo loop influence; quantitatively analyzing the influence of the angular motion parameters of the base on PIGA output errors; based on three-axis turntable experimental design, dynamic response of each axis of the PIGA is excited through single-axis, double-axis and three-axis angular velocity input, and error model coefficients are separated and calibrated; error model parameters are calibrated by adopting a mode of combining a least square method and other data fitting algorithms; angular velocity and angular acceleration terms are separated based on direction cosine matrix transformation, and error coefficient aliasing is avoided; dynamic response data are fitted through a least square method, and all error coefficients are calibrated at a time.

This invention discloses a method for improving the accuracy of inertial guidance based on polynomial recursive least squares, comprising: constructing a guidance tool error model based on the difference between inertial guidance telemetry observations and a flight environment function, wherein the guidance tool error model satisfies a linear relationship; constructing a recursive formula based on polynomial recursive least squares based on the guidance tool error model; determining the estimated value of the guidance tool error coefficient at the current recursive time based on the difference between guidance telemetry observations at the current recursive time and the recursive formula of least squares, and using the estimated value of the guidance tool error coefficient to compensate for the guidance telemetry observations at the current recursive time. This invention can significantly improve estimation accuracy and efficiency, and has a wider range of applications and higher engineering value.

The invention belongs to the field of two-dimensional thrust vectoring nozzle control, and particularly relates to a cooperative control method and system for multiple control loops. The method comprises the following steps: step 1, determining a virtual saturation processing mode; step 2, determining a collaborative error processing mode, including acquiring displacement deviation of each execution mechanism; calculating a collaborative error coefficient of each execution mechanism according to the displacement deviation; superposing the control signal after the virtual saturation processing with the collaborative error coefficient; and step 3, realizing cooperative control of a plurality of control loops based on the virtual saturation processing mode and the cooperative error processing mode. According to the cooperative control method of the multiple control loops, the control current of the nozzle controller is corrected by using the cooperative error coefficient, the transition state matching among the multiple loops is adjusted, and meanwhile, the steady-state control quality is not influenced.

The invention discloses a noise and non-ideal calibration-based uncertainty hybrid propagation model construction method, which comprises the following steps of: determining two uncertainty sources of noise and a non-ideal calibration standard, namely the uncertainty of the noise and a self-defined value of the non-ideal calibration standard in a measurement system; determining an error model and a calibration method, measuring system noise according to a calibration standard required by the calibration method and spreading the system noise to a measurement value, and calculating uncertainty of a non-ideal calibration standard; jointly coupling the non-ideal calibration standard uncertainty and the measured value uncertainty caused by the noise to an error coefficient obtained by solving through an error model to obtain an error term; and re-coupling the synthetic uncertainty carried by the error term and the noise in the measurement of the to-be-measured device through an error model, and jointly transmitting to a final calibrated scattering parameter result.

The application provides a wheel hub motor MTPA control method, device, equipment and storage medium, and belongs to the motor control technical field, wherein the method comprises the following steps: constructing an MTPA calculation model; when a torque reference value changes, calculating an axle current reference value of a next control period through the MTPA calculation model; taking the next control period as a current control period, calculating a partial derivative error and an error coefficient of the current control period; comparing the error coefficient of the current control period with a preset limit value, when the error coefficient of the current control period is greater than the preset limit value, iteratively correcting the MTPA calculation model; and when the error coefficient of the current control period is less than or equal to the preset limit value, finally correcting the MTPA calculation model. The wheel hub motor MTPA control method, device, equipment and storage medium can improve the control precision of the motor and improve the dynamic performance.

The present invention provides a method, device, storage medium and terminal for calculating the inclination angle of a near-bit, including: obtaining the past data of the near-bit, and establishing a correction model according to the past data; obtaining the initial measured inclination angle value of the near-bit at the current moment; obtaining the relevant parameter information of the near-bit at the current moment and the previous moment, and calculating the error coefficient of the inclination angle measuring tool according to the relevant parameter information at the current moment; calculating the current angle change ratio of the near-bit; inputting the relevant parameter information of the near-bit at the current moment and the previous moment into the correction model to obtain a primary output result and a secondary output result, and performing correction processing on the primary output result, the initial measured inclination angle value and the secondary output result according to the error coefficient and the angle change ratio to obtain the target inclination angle. Without changing the hardware conditions, the present invention effectively improves the accuracy of the inclination angle measurement result inside the near-bit.

The invention provides a power grid multi-energy data acquisition frequency control method considering a load prediction error, and belongs to the technical field of prediction control. The method comprises the steps of determining energy types of multiple energy sources of a research power grid, collecting original data of the energy sources according to energy characteristics of any energy type, and standardizing the original data to obtain standard power generation data; building a load prediction model, taking the standard power generation data of all energy types as the input of the load prediction model, and outputting a load prediction result; performing error analysis on the load prediction result and the actual load result to obtain an error coefficient of the corresponding energy type; based on a control algorithm, combining the error coefficient of the energy type and standard power generation data, and adjusting the collection frequency of the energy; and evaluating the frequency control result, and reversely optimizing the control algorithm and the load prediction model based on the evaluation result. And the load prediction precision and scheduling efficiency of the multi-energy power grid are improved.

The invention relates to the technical field of silicon controlled rectifier testing, in particular to a silicon controlled rectifier impact resistance testing method and system. The method comprises the following steps: acquiring a zero-crossing signal monitoring moment and a driving signal monitoring moment, acquiring delay duration controlled by a relay each time, and synchronously acquiring environment monitoring data at the monitoring moments; calculating a time extension error coefficient based on the delay duration, calculating an environment error coefficient based on the environment monitoring data, and forming a coefficient vector; collecting all coefficient vectors, calculating a time delay controllable coefficient of each time of relay control, constructing a two-dimensional sample space, and calculating error influence expressions corresponding to different time delays; carrying out statistical analysis on the error influence performance data of all the silicon controlled elements, and determining an error influence performance threshold value; and comparing the error influence performance at each monitoring moment with an error influence performance threshold value, and evaluating the impact resistance of the silicon controlled element. The accuracy of the impact resistance test result of the silicon controlled rectifier is remarkably improved.

The present application relates to thyristor testing technical field, specifically to a kind of thyristor impact resistance test method and system.The method includes the following steps: obtaining zero-crossing signal monitoring moment and driving signal monitoring moment, obtain the delay length of each relay control, and synchronously obtain the environmental monitoring data of monitoring moment;Based on the delay length calculation time extension error coefficient, based on environmental monitoring data calculation environmental error coefficient, and form coefficient vector;Collect all coefficient vectors, calculate the time delay controllable coefficient of each relay control, construct two-dimensional sample space, calculate the error influence performance corresponding to different time delay;Statistical analysis is carried out to the error influence performance data of all thyristor elements, and the threshold of error influence performance is determined;The error influence performance of each monitoring moment is compared with error influence performance threshold, and the impact resistance of thyristor element is evaluated.The present application realizes the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of

The invention discloses a heat pump air conditioning system with dynamic adjustment starting return difference control. The heat pump air conditioning system comprises a first temperature sensor, a compressor and a controller in communication connection with a reversing four-way valve, wherein the first temperature sensor is used for obtaining the temperature of an external heat source exchanging heat with a first heat exchanger; the controller comprises a temperature difference calculation unit used for obtaining the temperature of an external heat source, the set temperature of the external heat source and the communication state of the reversing four-way valve and calculating the actual temperature difference according to the communication state of the reversing four-way valve. The error acquisition unit is used for acquiring a first error, a second error and a third error; the return difference calculation unit is used for calculating a target return difference according to the initial return difference, the first error, the second error, the third error, the first error coefficient, the second error coefficient and the third error coefficient; and the system starting control unit is used for controlling the system to start according to the system starting times. Operation stability can be improved, and energy conservation, noise reduction and prolonging of the service life of equipment are both considered.

A kind of double-axis frame inertial navigation system error self-calibration and compensation method, under static base condition, in 8 frame angle position locking platform, acquisition accelerometer measurement value, calculate the specific force measurement value of inertial navigation system in each locking position platform coordinate system, and calculate the attitude matrix of inertial navigation system in each locking position platform coordinate system to local horizontal coordinate system, obtain the acceleration of inertial navigation system in each locking position local horizontal coordinate system, as error observation quantity.Using total least squares algorithm to obtain the residual of error coefficient, correct the estimated value of measured parameter, carry out iterative calculation until meeting iteration convergence criterion, obtain the self-calibration result of each error coefficient;Through the self-calibration and compensation of error coefficient, the influence of shaft system non-orthogonal error on the attitude measurement precision of double-axis frame inertial navigation system carrier or base can be improved.

The present application relates to the technical field of machine intelligence, in particular to a control method of a multi-station manipulator for stamping of a washing machine shell, which constructs a synchronization error matrix to determine an error transmission station sequence and a disturbance source station by using a station cooperative calibration experiment; in the working process of the station manipulator, the end load error coefficient of each station is determined, and the cumulative error weight of each station is determined in combination with the sequence number difference of each station and the disturbance source station in the error transmission station sequence; based on the cumulative error weight and the real-time position error of the manipulator of the disturbance source station, and in combination with the synchronization error matrix, the cumulative error amount of each station is determined; finally, according to the real-time position error and the cumulative error amount of the manipulator of each station, the error compensation value of each station is determined and compensation control is performed. The present application improves the accuracy of manipulator error compensation by determining the cumulative error amount of each station.

The invention discloses a thorium-based molten salt reactor primary loop molten salt flow prediction and control method and system, and the method comprises the steps: obtaining an original molten salt flow signal of each node in a thorium-based molten salt reactor primary loop, and obtaining a multi-scale molten salt flow component; inputting the multi-scale fused salt flow component into an LSTM network adaptive gating mechanism network model to obtain a fused salt flow initial prediction value of each node; obtaining an error coefficient of the fused salt flow based on D-SMAPE according to the initial predicted value of the fused salt flow of each node; the error coefficient of the fused salt flow is input into the trained ResNet prediction model, and an optimal fused salt flow prediction value is obtained; according to the optimal fused salt flow predicted value, the fused salt flow of the thorium-based fused salt reactor primary loop is controlled based on the DEM-DAC algorithm, and the method and system can solve the technical problems that during reactor variable-load operation, the fused salt flow fluctuation is large, and the unit load adjusting performance is poor.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an injector time calibration method, device and equipment and a medium, the method is applied to an MCU of an injector, and the method comprises the steps that whether a PPS IN signal exists or not is detected, and a detection result is obtained; based on a detection result, determining a timing condition; obtaining an error coefficient, wherein the error coefficient is a first time difference expanded by the equipment per second; based on the error coefficient and the timing condition, total error time needing to be compensated is calculated; and based on the total error time, a compensation mechanism is executed, so that the synchronization precision and the travel time precision can be improved.

The present application provides a health assessment method, device, and circuit breaker for an intelligent phase-controlled vacuum circuit breaker, and relates to the technical field of circuit breaker health assessment. The method comprises: performing vacuum detection on the arc extinguishing chamber in the intelligent phase-controlled vacuum circuit breaker to obtain the vacuum degree; performing a heat analysis of the vacuum circuit breaker based on the vacuum degree to obtain a heat parameter, performing a zero-crossing monitoring error analysis, and obtaining a zero-crossing error coefficient; mapping the zero-crossing error coefficient based on the operating time parameter of the vacuum circuit breaker, calculating a zero-crossing deviation coefficient, performing confidence processing based on the zero-crossing deviation coefficient and the analysis deviation coefficient of the heat analysis and the zero-crossing monitoring error analysis to obtain a zero-crossing confidence degree; assigning a weight based on the zero-crossing confidence degree, performing a health calculation based on the vacuum degree and the zero-crossing error coefficient, and obtaining the health degree of the vacuum circuit breaker. The method solves the technical problem of inaccurate health assessment of intelligent phase-controlled vacuum circuit breakers in the prior art.

This invention discloses a method for processing error data of smart energy meters based on edge computing, belonging to the technical field of error data processing methods. The invention includes: S1, calculating the mean and standard deviation of the total energy increment sequence within a sliding window, defining a first-order autoregressive hysteresis correction term, setting an adaptive threshold, defining the state machine system state, and finding the computer increment sequence during inactive periods by constructing an inactive period criterion; S2, storing the filtered effective data increments, calculating the energy increment of each sub-meter, defining a continuous zero increment detection function, collecting effective rearranged data points by setting the meter failure detection window and parameters, and constructing an observation matrix X and an observation vector Y; S3, using an improved genetic optimization algorithm framework, calculating eigenvalues ​​and condition numbers, and iteratively obtaining optimal and distinct individuals; S4, determining the optimal regularization parameters using the L-curve method, and calculating the error coefficients of each energy meter using improved Tikhonov regularization.

A horizontal five-axis turning plate milling parallel head geometric error identification method based on R-test comprises the steps that firstly, analyzed parallel head geometric errors are defined, and an inverse kinematics model is solved in combination with the structure of a parallel head; then, a linkage track of a numerical control machine tool is designed, after the RTCP function is started, the 3-PRS parallel main shaft head needs to traverse all controllable freedom degrees, namely, the A axis, the B axis and the Z axis, and measurement data is the actual tool nose position error; according to a solving result of the inverse kinematics model, solving of an error coefficient matrix is completed; and finally, an actual tool nose position error and a matrix related to an error matrix coefficient matrix and a Jacobian matrix are substituted through an identification equation set, and geometric error identification of the horizontal five-axis turning plate milling parallel head is completed. According to the method, the geometric error of the horizontal five-axis turning plate milling parallel head can be quickly identified, and the method has the advantages of high efficiency, accuracy, completeness, simplicity and convenience.

The present invention provides a method for real-time calibration of the error of a wheel displacement meter. S1, obtaining a first displacement positioning result of laser positioning when the robot moves forward normally and / or obtaining a second displacement positioning result of laser positioning when the robot moves backward normally; S2, optimizing the forward optimization cost function and / or the backward optimization cost function by using the Gaussian-Newton method according to the first displacement positioning result and / or the second displacement positioning result, and obtaining the error coefficient in the measurement model of the wheel displacement meter with error parameters; S3, correcting the positioning result of the wheel displacement meter according to the error coefficient to obtain the final positioning result given by the wheel displacement meter. The present invention uses the positioning result of laser positioning to estimate two error parameters in the measurement model of the wheel displacement meter with error parameters, thereby improving the accuracy of the wheel displacement meter of the patrol robot.

The invention provides a hub motor MTPA control method, device and equipment and a storage medium, and belongs to the technical field of motor control, and the method comprises the steps: constructing an MTPA calculation model; when the torque reference value changes, the shaft current reference value of the next control period is calculated through an MTPA calculation model; taking the next control period as a current control period, and calculating a partial derivative error and an error coefficient of the current control period; comparing the error coefficient of the current control period with a preset limit value, and performing iterative correction on the MTPA calculation model when the error coefficient of the current control period is greater than the preset limit value; and when the error coefficient of the current control period is smaller than or equal to a preset limit value, carrying out final correction on the MTPA calculation model. According to the hub motor MTPA control method, device and equipment and the storage medium, the control precision of the motor can be improved, and the dynamic performance can be improved.

The application discloses a circulating error improved wind speed prediction super-capacity energy storage grid-connected method and related products, and belongs to the technical field of wind power generation. The method is characterized in that: the original wind speed sequence of a wind farm is obtained and is divided into a training set and a test set; a prediction model is inputted with the training set to obtain a predicted value, and an error coefficient is calculated accordingly; the original wind speed sequence is corrected by using the error coefficient, a wind speed correction sequence and a first-order residual sequence are generated, and the residual sequence is iteratively corrected until the residual error coefficient is less than a preset value; the wind speed correction sequence and all-order residual sequences are inputted into the prediction model to be superimposed to obtain a final wind speed prediction value; and finally, the prediction value is used to determine the shortage of the super-capacity energy storage system, and a charging and discharging plan is formulated to realize efficient dispatching of the power grid. The application continuously optimizes the wind speed prediction result through the circulating error correction mechanism, and provides a reliable basis for accurate grid-connected dispatching of the super-capacity energy storage system.

The present invention discloses a multi-dimensional dynamic motor testing system, which relates to the field of motor testing technology and includes: establishing a digital model of the motor, performing simulated motor testing, and obtaining motor simulation parameters; inputting the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain simulated operation error coefficients; performing actual testing on the motor to obtain actual motor operation parameters, which are input into a pre-built parameter error analysis model to obtain actual operation error coefficients; performing error correction on the motor simulation parameters and the actual motor operation parameters based on the simulated operation error coefficients and the actual operation error coefficients to obtain correction calculation results; performing motor performance verification based on the correction calculation results and outputting motor test results. The present invention solves the technical problems that the prior art cannot comprehensively and accurately evaluate motor performance and the test results are greatly interfered with by environmental factors, thereby achieving the technical effect of comprehensively evaluating motor performance.

A self-calibration method for frame non-orthogonality error and accelerometer error in a dual-axis frame inertial system is proposed. Under static base conditions, the platform is locked at 10 frame angular positions, accelerometer measurements are collected, and the specific force measurement of the inertial system in the platform coordinate system at each locked position is calculated. The attitude matrix of the inertial system from the platform coordinate system to the local horizontal coordinate system at each locked position is also calculated, yielding the acceleration of the inertial system in the local horizontal coordinate system at each locked position, which is used as the error observation. The residuals of the error coefficients are calculated using a total least squares algorithm, and the estimated values ​​of the measured parameters are corrected. Iterative calculations are performed until the iterative convergence criterion is met, obtaining the self-calibration results for each error coefficient. Through the self-calibration and compensation of the error coefficients, the accuracy of attitude measurement of the dual-axis frame inertial system carrier or base affected by the non-orthogonality error of the axis system can be improved.

The invention relates to the technical field of machine intelligence, in particular to a control method of a multi-station manipulator for stamping a washing machine shell, which comprises the following steps of: constructing a synchronous error matrix by utilizing a station collaborative calibration experiment to determine an error transmission station sequence and an interference source station; in the working process of the station manipulator, the tail end load error coefficient of each station is determined, and the accumulative error weight of each station is determined by combining the serial number difference of each station and the interference source station in the error transmission station sequence; based on the accumulative error weight and the real-time position error of the manipulator of the interference source station, the accumulative error amount of each station is determined in combination with a synchronous error matrix; and finally, according to the real-time position error and the accumulated error amount of the manipulator of each station, an error compensation value of each station is determined, and compensation control is carried out. By determining the accumulated error amount of each station, the error compensation accuracy of the manipulator is improved.

The invention provides a direct current buck converter constant value steady-state error convergence control method and device. The method comprises the following steps: acquiring the input voltage, the output voltage and the inductive current of each stage of direct current buck converter; setting a corresponding output voltage target value, an error coefficient and a convergence factor; calculating an error function of each stage according to a difference value between an output voltage target value and an actual output voltage in combination with an error coefficient; carrying out convergence operation on the error function to enable the error function to converge in finite time; calculating an actual voltage gain according to the result of the convergence operation in combination with the dynamic change of the input voltage and the inductive current; and comparing the actual voltage gain serving as a modulation signal with a carrier wave to generate a pulse width modulation signal, and driving a power switch tube of the direct-current buck converter with the corresponding series. Based on the method, the invention further provides a control device. According to the invention, the change of the output voltage of the DC buck converter in the error convergence approximation process can be dynamically compensated, and a good control effect is realized.

The invention discloses a multi-task cooperative intelligent progress management method based on artificial intelligence, and relates to the technical field of bridge engineering data management and analysis. The method comprises the following steps: carrying out the first adjustment of the bridge measurement radar; performing bridge engineering intelligent progress first management; carrying out second adjustment on the bridge measurement radar; performing bridge engineering intelligent progress second management; and self-updating the intelligent progress management model of the bridge engineering. According to the invention, single radar parameter evaluation is carried out and then error coefficient calculation and first adjustment are carried out; performing radar composite influence evaluation, model correction and second adjustment; and finally, model self-updating is retrained through actual and target time error data, so that the effect of improving the robustness of collaborative progress management in bridge construction is achieved, and the problem of insufficient robustness of collaborative progress management in bridge construction in the prior art is solved.