73 results about "Static error" patented technology

The invention relates to the technical field of inclination angle measurement sensors, and provides a calibration method and system for a high-precision inclination angle measurement sensor, and the method comprises the steps: obtaining the original output data of the high-precision inclination angle measurement sensor at a plurality of known attitude angles, so as to construct a multi-dimensional attitude mapping table, carrying out the error gravity center vector analysis of the multi-dimensional attitude mapping table, and carrying out the calibration of the high-precision inclination angle measurement sensor. After an error mapping graph is generated, boundary deviation suppression is carried out, after a correction graph is obtained, an inclination angle residual error regulation and control mapping relation is constructed, multi-dimensional partition adjustment and optimization are carried out on the inclination angle residual error regulation and control mapping relation, a residual error calibration function set is constructed, and output data of the high-precision inclination angle measurement sensor are calibrated based on the residual error calibration function set. The calibration precision of the inclination angle measurement sensor is improved from multiple dimensions, the influence of static errors and dynamic errors is effectively eliminated, the use reliability and applicability of the sensor are enhanced, and the problems that in a high-precision scene, error modeling is not accurate enough and the anti-interference capability is insufficient in the prior art are solved.

The invention relates to the technical field of machine vision, in particular to a calibration method and device for an industrial machine vision measurement system, and the method comprises the following steps: collecting error data through a glass linear scale and a circular target, constructing a standardized calibration data set, obtaining a global error gradient field, a residual error trend map and a residual error weight coefficient table, and obtaining a standard calibration data set; and fusing the size compensation value and the directivity correction value, constructing a calibration matrix, and obtaining a system calibration result. According to the method, through fusion modeling of multi-source error data, the recognition precision of the system on error sources is improved, gradient field construction and trend graph extraction are combined, the directionality and spatial continuity of error compensation are enhanced, and a weight coefficient distribution mechanism is utilized, so that differential control on dynamic and static error influence is realized; and a calibration matrix with multi-dimensional parameter fusion is adopted to optimize the consistency and adaptability of the overall measurement precision, so that the system keeps stable error correction capability and calibration accuracy in a complex environment.

The invention relates to the technical field of intelligent construction, and discloses a construction steel structure fabricated building assembly method which comprises the steps that real-time pose data of a steel structure component is collected through a multi-source sensor array; performing multi-rate fusion processing on the pose data to generate six-dimensional state estimation containing position and pose errors; constructing an error matrix in the Lie group SE (3) space based on the state estimation, wherein the error matrix represents the deviation between the component pose and the target pose; and establishing a matrix differential equation model according to the error matrix, and solving an optimal compensation control quantity in a future time domain in a rolling manner through a model prediction control algorithm. Through combination of Lie group space error modeling and rolling time domain optimization, the system can sense the pose deviation of a component in real time and dynamically adjust a control strategy, limitation of traditional static error compensation and online parameter identification and disturbance suppression under complex working conditions are broken through, and uncertainty caused by dynamic changes of a construction environment is effectively dealt with.

The invention relates to the technical field of wind power generation. The invention provides a yaw static and dynamic error adaptive method based on big data backtesting, which comprises the following steps of: constructing a multi-dimensional feature vector through multi-source data fusion data, and establishing a dynamic feature data set; based on the dynamic characteristic data set, a space-time diagram convolutional network is adopted to establish a wind power plant dynamic error prediction model, and space-time evolution rules of wind shear, turbulent flow and wake flow effects are captured; constructing a variational self-coding reference model based on historical full wind speed section data, calculating a residual error between a current working condition and the variational self-coding reference model in real time, and taking the residual error as a static error prediction value; performing adaptive weight fusion on the static error prediction value and the dynamic error prediction value to obtain a fusion error; and the fusion error is converted into the yaw angle correction amount, and the wind facing action is executed. The problems that an existing yaw error recognition technology is high in data dependence, lack of dynamic analysis, poor in model adaptability and difficult in complex wind field processing are solved.

The invention discloses an MEMS and MHD combined gyroscope low-high frequency composite calibration method, which comprises the following steps: synchronously acquiring vibration response data of a combined gyroscope sensor, separating low-high frequency signals, calculating low-frequency static error parameters and high-frequency dynamic error parameters, constructing a static orthogonal matrix based on a mounting angle error, and calibrating the low-high frequency composite of the MEMS and MHD combined gyroscope. The method comprises the following steps: generating a normalized error transfer coefficient by utilizing a high-frequency dynamic error parameter cross response ratio and a rejection ratio, generating a dynamic error matrix according to the normalized error transfer coefficient, establishing an expression containing error output of a sensor by utilizing the dynamic error matrix, and inversing the dynamic error matrix to obtain a dynamic error transfer matrix, and the static orthogonal matrix and the dynamic error transfer matrix are combined to construct a composite error compensation model, error parameters after dynamic compensation are evaluated, a residual feedback signal is generated in combination with an error evaluation result, calibration error parameters are iteratively corrected until convergence, and the calibration parameters are output.

The invention discloses a lift force and torque direct closed-loop control and fault-tolerant operation method and device for a six-rotor aircraft. By using the controller obtained by the invention, an optimal current instruction can be directly obtained from a lift instruction and a torque instruction, and a traditional cascaded rotating speed calculation module and a plurality of rotating speed controllers are uniformly replaced; the obtained control system can realize direct closed-loop control of the lift force and the torque, not only significantly improves the dynamic performance of the lift force and the torque, but also integrates the rotating speed resolving process using the aerodynamic parameters into the controller, and can eliminate the steady-state static error caused by mismatch of the aerodynamic parameters by means of an auxiliary disturbance observer. The steady-state control precision and the system robustness of the lift force and the torque are enhanced; and finally, for different fault modes, reconstructing a fault prediction model, a fault controller and a fault-tolerant operation control system suitable for different faults, so that excellent fault-tolerant operation of the multi-rotor aircraft in some fault modes is ensured, and the safety and reliability of operation of the multi-rotor aircraft are improved.

The invention belongs to the field of analog integrated circuit design, and particularly relates to a miniaturized high-precision non-binary R-2R DAC with digital correction. Non-binary characteristics are introduced by setting resistance values of bridge resistors RBm and RBm + 1, so that an LSB section is a binary weight section, and ISB and MSB are non-binary weight sections; therefore, the width-to-length ratios of the MOS tubes of the switches SWm + 1-SWm + i + j and SW1 are equal and do not need to be increased proportionally, the non-binary characteristic is further introduced by setting the switch on-resistance, the selection of the unit resistance R only needs to meet the matching precision of the LSB section, and the area of the switch resistor array is greatly reduced. Static errors in the ISB segment and the MSB segment are respectively corrected by using an OEM correction technology, only digital code redundancy between adjacent segments of the LSB segment, the ISB segment and the MSB segment needs to be obtained through measurement, redundant digital codes are removed by adjusting digital input codes of corresponding segments, and the m + n + k-1 bit binary DAC is obtained through calibration, so that the memory of a digital calibration algorithm is efficient, and the algorithm complexity is effectively reduced. According to the invention, the area of the DAC is obviously reduced while high precision is realized.

The invention belongs to the technical field of robot error compensation, and particularly relates to a positioning error iterative nonparametric compensation method based on WGA-FDBN-DC and pose dependence, and the method comprises the steps: analyzing a robot positioning error source; constructing a three-in-one positioning error compensation model; based on WOA, performing wide area search to position an error extremal region generated by asymmetric hysteresis; training samples are created, an adaptive threshold value is constructed to dynamically remove abnormal samples, and filtering parameters are updated online in combination with the stochastic approximation theory to screen the training samples; a non-linear mapping relation between joint poses and static errors is constructed through a main network of cascade closed-loop suppression, static error prediction is carried out, a compensation network analyzes dynamic coupling errors of environmental disturbance and mechanical deformation in real time, and the main network and the compensation network form closed-loop control through error feedback. The method achieves the building of a mapping model from the joint motion amount to the joint compensation amount considering the pose dependence of the absolute positioning error, and achieves the direct iteration compensation of the error generated by the joint motion.

The invention discloses a numerical control machine tool synchronous evolution control method and system associated with dynamic and static errors, relates to the technical field of information processing management, and is used for solving the problem that a machine tool structure optimization method is poor in structural integrity, structural connectivity and dynamic response characteristic analysis. By monitoring and analyzing geometric structure parameter changes of all parts in the machine tool operation process, effective geometric structure parameters with the high influence degree are screened out, preliminary optimization is carried out, a geometric structure optimization evaluation model is established, and an optimization result is evaluated; the method comprises the following steps of: acquiring local rigidity and weight, establishing an optimization evaluation model, defining geometric structure parameters of a plurality of components as an integral assembly structure, constructing a parallel optimization model by utilizing a grid division and rigidity matrix calculation method, and finally obtaining optimization results of a macroscopic unit and a connecting unit by taking minimization of structural flexibility as a target. Key parameters can be accurately monitored and optimized, the structural connectivity is considered, and the overall performance and stability are improved.

The invention discloses a multichannel passive antenna array high-efficiency amplitude-phase test system, and relates to the technical field of amplitude-phase tests.According to the multichannel passive antenna array high-efficiency amplitude-phase test system, a robustness analysis and error modeling module is introduced, the influence of environmental disturbance factors on an antenna array is evaluated and compensated in real time, a global error model is constructed, static errors and time-varying errors can be effectively recognized, and the accuracy of amplitude-phase testing is improved. An error compensation strategy is dynamically adjusted, high precision can be kept in a dynamic environment, meanwhile, a deep learning auto-encoder is adopted to extract time-varying error features, a self-adaptive correction strategy is combined, real-time error compensation and dynamic adjustment are achieved, the system adjusts amplitude-phase data of each channel according to real-time feedback, and in various platform dynamic states, the real-time error compensation and dynamic adjustment are achieved. The test result is kept continuous and accurate, error compensation and correction can be automatically completed in the whole process through automatic error feature extraction, self-adaptive correction and a feedback mechanism, the requirement for human intervention is reduced, and a correction strategy is continuously optimized in the platform test process.

The invention discloses a PMSLM adaptive optimization harmonic current suppression method based on a multi-rotating coordinate system. According to the method, high-precision extraction of target harmonic waves is realized through a multi-rotating reference coordinate system and a complex coefficient filter; an adaptive moment estimation algorithm (AdamW) with weight attenuation is used to quickly solve an optimal harmonic reference current; and harmonic compensation voltage is output by combining the zero static error characteristic of the proportional resonance PR controller, so that the harmonic current is effectively suppressed. The harmonic current of the permanent magnet synchronous linear motor is quickly and effectively suppressed through a harmonic injection method adopting a multi-rotation reference coordinate system, a complex coefficient filter and an AdamW optimization algorithm. The inherent defects of large phase lag and slow dynamic response when a low-pass filter is used in a traditional harmonic current injection method can be effectively overcome by adopting a complex coefficient filter for current extraction; and an AdamW optimization algorithm is adopted to suppress overfitting through a weight attenuation strategy, and an optimal solution is efficiently and stably obtained.

The invention belongs to the technical field of atmospheric science, and discloses a set-variational hybrid assimilation system and method based on a meteorological large model, which adopts a physical constraint mode (RANDOMMV) to perform random disturbance on an atmospheric initial field, quickly generates set members based on the strong deduction capability of the artificial intelligence meteorological large model, and improves the set-variational hybrid assimilation efficiency. The member diversity is ensured; and the sampling error is reduced. On the basis, a set-variation hybrid assimilation method is adopted, and a set-variation hybrid assimilation system is constructed by combining a dynamic set background error covariance and a static background error estimated through an NMC method, so that effective assimilation of the multi-source observation data is realized. According to the method, the physical consistency and stability of the AI ensemble forecast members can be ensured. Long-term average static error information derived from a difference field of historical forecast data and flow dependent background error information of ensemble forecast are combined; and dynamic and static combination enhances the robustness of the hybrid assimilation system.

The invention discloses a dead-beat control method for a permanent magnet synchronous motor based on PSA algorithm parameter identification, and the method comprises the steps: firstly, providing an improved current prediction algorithm based on a mathematical model of the permanent magnet synchronous motor, so as to eliminate one-beat delay in current command calculation; then, current fluctuation and static errors are reduced by combining weight coefficients; and finally, on the basis, parameter identification is carried out by utilizing a PID search algorithm (PSA), and resistance, flux linkage and inductance parameters are accurately identified, so that current static errors caused by parameter mismatching are eliminated. According to the method, the problems that the traditional permanent magnet synchronous motor dead-beat current prediction control depends on the accuracy of motor parameters, current deviation is easy to generate and current fluctuation is large are solved, and the robustness and the control precision of the system are improved.

The invention relates to a cubic spline trajectory planning and MPC tracking control method for optimizing a hydraulic mechanical arm based on a genetic algorithm, and belongs to the field of trajectory gauges of hydraulic mechanical arms. According to the method, the minimum time of cubic spline trajectory planning is iteratively solved by taking the time of the whole trajectory as a target function and the kinematics constraint of the mechanical arm as a boundary condition through a genetic algorithm, so that the trajectory planning is optimized, and the grabbing efficiency is improved. Meanwhile, MPC control rates with constraints are designed according to the identification models of all the shafts of the hydraulic mechanical arm, corresponding constraints are designed according to the upper and lower limits of input signals of all the shafts and the upper and lower limits of input variable quantities, and accurate trajectory tracking is achieved. Compared with a traditional PID control rate and a composite PID-DOB control rate, the method has remarkable advantages in the aspects of static errors and dynamic errors, the debugging process is simpler, parameters are fewer, and application and popularization are easier.

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.

The application discloses a kind of super-long part bending front feeding positioning device and method, belong to metal sheet precision forming manufacturing field, method is through high-precision measurement acquisition feeding platform surface full field data, constructs and bending mould center line alignment digitization platform surface model, and generates height constant equal to mould center line global reference line and static platform compensation mapping function.In feeding process, the trajectory deviation of the part bottom surface relative to the reference line is detected in real time using a non-contact displacement sensor array, the static compensation value is combined with feedforward-feedback composite control to drive the active leveling mechanism for vertical adjustment, and the static error and dynamic disturbance of the platform are simultaneously offset.The system continuously monitors the actual trajectory and triggers the instant adjustment mechanism when the deviation exceeds the limit.The application solves the problem of error accumulation in super-long part feeding by establishing a global unified reference, integrating static pre-compensation and dynamic closed-loop control, and constructing multiple verification, achieving high-precision positioning.

The present invention discloses a method and device for direct closed-loop control of lift and moment and fault-tolerant operation of a six-rotor aircraft. The controller obtained by using the present invention can directly obtain the optimal current command from the lift command and the moment command, and uniformly replace the traditional cascaded speed calculation module and multiple speed controllers; the obtained control system can realize the direct closed-loop control of lift and moment, not only significantly improving the dynamic performance of lift and moment, but also integrating the speed calculation process using aerodynamic parameters into the controller, and can eliminate the steady-state static error caused by aerodynamic parameter mismatch with the help of an auxiliary disturbance observer, enhancing the steady-state control accuracy of lift and moment and the system robustness; finally, for different fault modes, fault prediction models, fault controllers and fault-tolerant operation control systems suitable for different faults are reconstructed to ensure the excellent fault-tolerant operation of the multi-rotor aircraft in some fault modes and improve the safety and reliability of the operation of the multi-rotor aircraft.

The invention discloses a roller way scale control method, relates to the technical field of electrical automation control, and solves the technical problems of low working efficiency, low accuracy, no weight early warning function and no automatic return-to-zero operation of manual recording of an existing roller way scale. The method comprises the following steps of: 1, acquiring a steel signal on a weighing roller way, judging whether the steel signal is a true value or not, and when the steel signal is the true value, controlling the weighing roller way to stop according to set positioning delay time, so that a raw material blank is parked right above a roller way scale; and 2, the weighing roller way is controlled to stop acting according to the set locking time, and the roller way scale is controlled to weigh the raw material blank. The invention further discloses a roller way scale control device. According to the invention, the problem of low efficiency during manual copying is solved, the equipment is ensured to be in a zero state before each raw steel billet is weighed, the static error is reduced, and the problem of low timeliness is solved.

The invention discloses a method and a device for realizing error processing of a five-axis machine tool, which are used for determining an error source through measurement and transmission calculation, providing a basis for optimization design and providing a technical guarantee for improving static and dynamic precision of the machine tool. Furthermore, multi-source errors are pre-compensated, various static errors and dynamic errors are processed at the same time, and the terminal precision of the machine tool is improved; compensation is carried out before errors occur, and the delay problem of real-time compensation is avoided; and through filtering, unstable factors in the compensation process are reduced.

This invention discloses a method, device, and medium for error prediction and self-repair in low-code applications, belonging to the field of low-code platform technology. It addresses the technical problems of existing low-code platforms, which rely heavily on manual testing, are prone to lag, have blind spots, and are difficult for non-professional developers to diagnose deep-seated logical errors. The method includes: classifying and configuring business scenarios in the low-code platform, collecting and obtaining scenario constraint data; performing error prediction detection on the low-code data at both dynamic and static levels to obtain dynamic and static error results; performing error prediction detection on the low-code data at the machine learning prediction layer to obtain machine learning layer error prediction results; classifying and repairing both dynamic / static error results and machine learning layer error prediction results to obtain repair result information; and blocking high-risk error results to obtain blocking result information; thereby completing error prediction and self-repair in the low-code application.

The invention discloses a motion platform positioning error compensation method and device, a medium and a program product, and relates to the technical field of semiconductor manufacturing. The method comprises the following steps: controlling a motion platform to move for multiple times, wherein different moving speeds are adopted for each time of movement. Aiming at each coordinate dimension, in each movement process, according to the obtained ideal coordinates and the read coordinates, determining the dynamic error of each preset sampling point passing through the movement on each coordinate dimension in the preset reference coordinate system, and according to the dynamic error and the movement speed, determining the movement speed of each preset sampling point; and determining a target mapping relation of each preset sampling point on the coordinate dimension. Based on the target mapping relation, static errors of the motion platform at all the preset sampling points in the static state are determined, then a static error curve of each coordinate dimension is determined according to the static errors of all the preset sampling points on all the coordinate dimensions, and the static error curves of all the coordinate dimensions are used for conducting positioning error compensation on the motion platform. And the positioning precision of the motion platform is improved.

The invention provides a single-phase motor control system, a self-adaptive adjustment module, a method and electrical equipment. The method comprises the following steps: acquiring a difference value between a positive pulse width and a negative pulse width of a Hall signal of a motor; performing low-pass filtering on the difference value to obtain an adjustment value; the pulse width of the driving signal is adjusted based on the adjustment value, and when the positive pulse width is larger than the negative pulse width, the pulse width of the upper-phase driving signal is adjusted to be N '= N-Vadj; and when the positive pulse width is smaller than the negative pulse width, adjusting the pulse width of the lower-phase driving signal to M '= M-Vadj. According to the self-adaptive adjusting module, the single-phase motor control system and the electrical equipment, complex peripheral circuits are not needed, and the system complexity and the product manufacturing cost are reduced; static errors caused by Hall position sensor machining and mounting processes are effectively filtered out, and the defects of the motor machining process are overcome. And system dynamic errors caused by motor jitter, temperature change and the like due to sampling point offset and environmental factors are effectively reduced, so that the control system has a self-adaptive adjustment function.

The invention relates to the technical field of loading control, and discloses an LQG control method and system for an integral configuration link, and the method comprises the steps: obtaining an actual measurement output vector, an expected output vector and a system state observation vector of a loading control system in a current control period, and constructing an integral type performance index functional; obtaining an augmented state space model and an augmented state estimation vector according to an original state space equation, a process noise covariance matrix, a measurement noise covariance matrix and a system state observation vector of the loading control system; based on the augmented state space model and the integral type performance index functional, establishing an extended Riccati differential equation to obtain an optimal feedback gain matrix; and performing linear feedback operation on the augmented state estimation vector based on the optimal feedback gain matrix, generating a control instruction of a loading control system, and realizing zero-static-error optimal tracking, independent and accurate setting of multi-channel integral intensity, adaptive optimization of controller parameters and robust stable operation under uncertainty.

The present invention provides a model-free control method for a permanent magnet synchronous motor based on disturbance observation. During the current predictive control process, only two observer control parameters need to be adjusted, and it does not depend on any motor parameters, overcoming the shortcomings of the prior art that are easily affected by parameter drift and model mismatch caused by factors such as temperature, magnetic field saturation, and operating conditions, reducing the harmonic content of current predictive control during parameter perturbation, avoiding oscillation and current static error, and improving the robustness of motor control, thereby achieving many beneficial effects that the prior art does not have.

The application discloses a kind of compilation methods for automatically mixed precision optimization procedure, first the preprocessing of the source code file of the program to be optimized is carried out based on the static error analysis technique of chain automatic differentiation, then the precision sensitivity of floating point variable in program is analyzed using the static error analysis technique based on the chain automatic differentiation, precision insensitive variable is determined, and variable information is stored in JSON file;Again, the source code file of the program to be optimized is used as input, the file is traversed by using variable information search tool, the information of all variables in the program is obtained to form a variable configuration file, and a configuration file of variable precision search space is formed according to the precision configuration scheme of the current program;Using the result of error analysis, the variable precision search space is reduced, and the optimized variable precision search space file is formed;The application can solve the technical problem that the execution efficiency of the optimized program cannot be improved by the automatic mixed precision optimization technology based on error analysis.

The invention discloses an intelligent ultrasonic volume correction instrument verification method and device, and the method comprises the steps: constructing a verification three-dimensional model according to the data type of detection data, and dividing the three-dimensional model into a plurality of regions; detecting the detected volume correction instrument, calculating a static error score and a first dynamic error score, analyzing the static error score, determining static detection data and first supplementary detection data, and performing supplementary detection through the first supplementary detection data; calculating a second dynamic error score of each region, and determining a to-be-verified region; performing supplementary detection through the second supplementary detection data; and calculating a first dynamic error score of the second supplementary detection data, determining a third dynamic error score in combination with the first dynamic error score of the detection data, performing analysis according to the third dynamic error score, and determining dynamic verification data. Static flow and dynamic flow are comprehensively detected, and the detection accuracy of the ultrasonic volume correction instrument is improved.

The invention discloses a method and a device for predicting the fatigue life of a low-temperature container. The method comprises the following steps: constructing a geometric model of a to-be-predicted low-temperature container; performing mesh generation on the geometric model, and performing finite element analysis and fluid mechanics calculation on the meshed model to obtain a multi-physical field simulation model of the low-temperature container; performing short-term real-time correction on model parameters of the simulation model based on the real-time data of the low-temperature container so as to eliminate static errors of the simulation model; in response to the fact that the static error of the simulation model exceeds a preset value, training a pre-constructed machine learning model based on the historical data of the low-temperature container to obtain the dynamic deviation of the simulation model; based on the dynamic deviation, correcting the simulation model after short-term and real-time correction to obtain a digital twinborn model of the low-temperature container; and predicting fatigue damage and residual life of the low-temperature container based on the digital twin model. According to the invention, the fatigue damage and residual life of the low-temperature container can be accurately predicted.

The invention relates to the technical field of motion module compensation positioning, in particular to a two-dimensional compensation algorithm based on vision, which comprises the following steps: S1, setting a calibration plate with a plurality of calibration points, and moving a camera to adjust the position of the calibration plate; s2, enabling the camera to move through a movement module, and recording the module coordinate of each calibration point in the reference coordinate system; s3, constructing a bivariate cubic polynomial according to the coordinates of the module to describe compensation values of all points in the working area of the camera, and constructing a module coordinate system; according to the method, after global compensation is carried out on the module coordinate system, compensation is carried out on the local position, compared with a common motion module compensation method, most of static errors are eliminated, part of dynamic disturbance is eliminated, and the method can adapt to changes of temperature and mechanical vibration; therefore, the compensation precision of the module coordinate system is higher, and more accurate positioning of the camera in the later period is facilitated.

The application provides a kind of permanent magnet synchronous motor deadbeat prediction control method based on super-spiral sliding mode extended observer, which first designs a sliding mode observer based on super-spiral theory to estimate unknown disturbances such as parameter perturbation, then designs an extended state observer to estimate disturbances twice, and compensates the estimated values of the two disturbances to the predicted current and output voltage, respectively, to achieve high-precision and robust current control and improve the dynamic and static performance of the control system. Compared with traditional deadbeat prediction control, the application has the advantages of high robustness, low parameter sensitivity, good dynamic performance and no static error.

The present invention relates to the field of machine vision technology, and specifically to a calibration method and device for an industrial machine vision measurement system, which includes the following steps: using a glass linear scale and a circular target, collecting error data to construct a standardized calibration data set, obtaining a global error gradient field, a residual trend map, and a residual weight coefficient table, fusing a size compensation value and a directional correction value, constructing a calibration matrix, and obtaining a system calibration result. In the present invention, through the fusion modeling of multi-source error data, the recognition accuracy of the error source of the system is improved. Combining the construction of the gradient field and the extraction of the trend map, the directionality and spatial continuity of error compensation are enhanced. Using the weight coefficient distribution mechanism, differential control of the influence of dynamic and static errors is achieved. A calibration matrix with multi-dimensional parameter fusion is adopted to optimize the consistency and adaptability of the overall measurement accuracy, enabling the system to maintain stable error correction ability and calibration accuracy in a complex environment.