345 results about "System error" patented technology

The invention discloses a self-adaptive safety control method of a nonlinear MIMO system under intermittent DoS attack, which comprises the following steps: establishing a nonlinear MIMO system model suffered from intermittent DoS attack, and the system model is in a strict feedback form and comprises an unknown nonlinear function and bounded external disturbance; the DoS attack causes periodic interruption of a communication link from a sensor to a controller, so that actual measurement data is unavailable in an attack activation period; designing a switching type adaptive state estimator; coordinate transformation is carried out by introducing a filter, and a system error is decomposed into a tracking error and a dynamic surface filtering error; a Lyapunov function is constructed; performing stability analysis in stages; designing an adaptive law to update unknown parameter estimation values of the FLS; and a final event triggering controller is designed, and the event triggering controller is combined with a virtual controller to track an error compensation term and an FLS approximation term. The problem that the state cannot be measured is solved.

The invention provides a mechanical arm predefined time trajectory tracking control method and system based on time delay estimation, and relates to the technical field of multi-degree-of-freedom mechanical arm trajectory tracking control. Constructing a predefined time error conversion function to define a system error and conversion error system, designing a barrier function and a feedback control rate based on the conversion error system, and designing a Lyapunov function to prove the stability of the system so as to track an expected trajectory; according to the method, time delay information is deeply fused, dependence on a complex model approximate structure is not needed, stable convergence of the mechanical arm system state within predefined time can be achieved when a mathematical model is not accurate, the system control performance and robustness are effectively improved, and the requirement of modern industry for mechanical arm high-performance control is met.

The invention relates to the technical field of spraying control, in particular to an anti-corrosion steel pipe inner spraying track self-adaptive control system based on multi-sensor fusion. The feed-forward prediction module generates a feed-forward correction signal through a model compensator and a self-adaptive compensator and predicts and compensates system errors, the feedback control module comprises a track generator and a disturbance observer, a feedback control instruction is generated by comparing a correction track with an original track, an execution mechanism is dynamically adjusted, and the system error is predicted and compensated. The signal driving module adopts a frequency domain decoupling fusion technology, combines a feedforward correction signal and a feedback control instruction, generates a composite control instruction, and ensures the accuracy of trajectory tracking control. According to the invention, through a double-loop control architecture combining feedforward prediction and feedback disturbance suppression, high-precision and strong-robustness self-adaptive control of a spraying track under a complex working condition is realized.

The invention relates to the technical field of semiconductor manufacturing, in particular to a wafer pre-alignment device and method, and the device comprises a mounting platform, an XY motion platform, a rotating platform, a suction cup, and an edge detection assembly. The method comprises the steps of device correction, coarse scanning and circle center positioning, fine scanning and notch accurate positioning and alignment execution. Through software and hardware cooperation, online self-correction is used for eliminating system errors, high-order fitting and feature screening algorithms are used for restraining random errors and model errors, the repeated positioning precision, notch orientation precision and equipment consistency of the wafer pre-alignment device are improved, and the high-precision requirement for a wafer transmission system under the advanced manufacturing process can be met.

The invention relates to a processor and a terminal for positioning a subway train, and the processor is in communication connection with an inertial measurement unit of the train, and is used for receiving multi-source data, collected by the inertial measurement unit, of the train; in the processor, an initial correction module performs state estimation on original acceleration and angular velocity data of a train acquired by an inertial measurement unit based on an error Kalman filtering algorithm, and dynamically corrects measurement noise and system errors in combination with a motion model of the system and an actual measurement value of the inertial measurement unit; the curve generation module constructs a time-mileage curve of the train and corrects the time-mileage curve based on the first correction proportion; the turning recognition module calculates the total mileage in the turning section and corrects the total mileage in the turning section based on the second correction proportion of the turning section; the abnormal vibration recognition module recognizes abnormal vibration features based on the high-order change rate of the acceleration and the angular speed of the train and marks the abnormal vibration features in a visual mode.

The invention relates to an information fusion method and device of a multi-source navigation system, computer equipment and a computer program product. The method comprises the following steps: constructing a preset number of sub-models according to sensor systems in the multi-source navigation system, taking the product of the expected credibility and the real-time credibility of the performance of each sensor system as the comprehensive credibility of each sensor system, and determining a state transition probability matrix of the sub-models according to the comprehensive credibility; state prediction updating and measurement updating are carried out on each sub-model, and a system error state and a system state covariance are calculated; and calculating a predicted posterior probability of each sub-model, determining an interactive weight between the sub-models according to the predicted posterior probability and the state transition probability matrix, and correcting and updating the system error state and the system state covariance according to the interactive weight to obtain a final system error state and a final system state covariance. By adopting the method, the robustness of information fusion can be effectively improved.

Providing issue resolution in a cluster system by monitoring system operation to detect occurrence of a system error, and automatically generating, upon detection of the error condition, a core file for a user node. The core file captures a current memory state of a respective node, where the current memory state comprises system statistics, system information, and logs. An intelligent core debugger extracts information from a core file to generate a core file report that is sent to a vendor for a quick determination of whether sufficient information is in the report to allow the vendor to recommend a fix, or whether further information from is required, including the core file itself, if necessary. This prevents the need to send an entire core file to a vendor in every instance of a system fault.

The invention discloses a PMSM (permanent magnet synchronous motor) control method for a mining electric locomotive. The method comprises a cooperative control framework of a fractional order sliding mode controller and a nonlinear extended state observer. Wherein the fractional order sliding mode controller constructs a novel sliding mode surface by introducing a terminal factor and a fractional order calculus theory, and introduces a state variable to design an adaptive fractional order reaching law, so that buffeting is effectively inhibited and controlled while system error convergence is accelerated; and the nonlinear extended state observer is used for estimating the uncertainty of a system model and the disturbance of an external load in real time, and introducing the uncertainty and the disturbance as feedforward compensation quantity into a control loop, so that the anti-interference capability of the system is remarkably enhanced. Through deep fusion of the fractional calculus theory, the sliding mode control and the nonlinear extended state observer, the problems of large buffeting, slow response, poor anti-interference capability and the like of a traditional control method of the mining electric locomotive under complex working conditions are solved, and the dynamic and steady state performance and the control precision of the system are remarkably improved.

The invention discloses an overlay error real-time correction system based on image recognition and dynamic fitting, and belongs to the field of semiconductor advanced packaging and manufacturing. The system comprises an image acquisition module, an error decoupling module and a dynamic compensation module to form closed-loop control. The image acquisition module adopts a high-resolution linear array CCD (Charge Coupled Device) and an AI (Artificial Intelligence) algorithm to realize high-speed and high-precision mark identification and error quantization; the error decoupling module performs decoupling and trend prediction on system errors and random errors by using PCA, a region weight matrix, LSTM and the like; and the dynamic compensation module realizes mu s-level partition graph compensation by a DMD optical system based on an error thermodynamic diagram through heterogeneous platform operation. The system supports the real-time processing of more than 100Hz, the average overlay error is less than or equal to 0.3 mu m and the response time is less than 5 seconds in the FOPLP and other processes, the problems of lag, low precision and the like of the traditional method are effectively solved, and the manufacturing yield and the production line efficiency are remarkably improved.

The invention relates to the technical field of multi-beam sounding calibration, and discloses a multi-beam sounding online real-time calibration method. The method comprises the following steps: acquiring original water depth data and corresponding sensor attitude data in real time; generating a data quality evaluation result containing a data credibility index and a data abnormal distribution feature based on the original water depth data; triggering a dynamic calibration mechanism containing a calibration period adaptive adjustment strategy and a calibration parameter optimization rule according to the data credibility index; optimizing the target calibration rule parameters in combination with the sensor attitude data to generate an optimized calibration parameter set, and correcting the original water depth data in real time by using the parameter set to generate primary calibration data; and performing topographic feature consistency check on the primary calibration data, if the primary calibration data does not pass the topographic feature consistency check, starting a re-calibration process containing a rule base updating mechanism and a parameter iteration mechanism, and analyzing a deviation trend based on historical calibration records to generate a system error prediction model.

The invention provides a laser ceilometer system error compensation method based on regression analysis, and belongs to the technical field of laser ceilometers. A measurement range is divided into four height intervals by constructing a layered height interval step regression equation set, and an independent nonlinear regression equation is established; designing a double-layer game optimization framework to realize collaborative optimization of global error minimization and local fitting precision maximization, executing historical data preprocessing and data set division, and implementing a double-layer game model collaborative optimization algorithm to determine a regression equation coefficient and a neural network parameter; a self-adaptive cloud height error correction model based on a Transform architecture is constructed to realize real-time error compensation, the optimal performance of the model is kept through sliding time window monitoring and automatic retraining, and the technical problem that the measurement precision of the laser ceilometer is affected by atmospheric environment parameters and equipment parameter changes, and consequently system errors are remarkable is solved.

Methods, systems, and devices for enhanced error handling in memory systems are described. A memory system may enter a read error handling procedure to recover data from a memory cell. For example, the memory system may perform multiple read operations at respective first read levels to identify a voltage valley associated with the data in the memory cell. Based on identifying the voltage valley, the memory system may read the data from the memory cell according to a second read level, where the second read level may be based on one of the first read levels, a first learning rate parameter, and a first momentum parameter. The memory system may determine whether to exit the error handling procedure or continue with the error handling procedure based on whether the data was successfully decoded in response to the read operation at the second read level.

The invention discloses a cable terminal crimping quality detection method, device and equipment and a storage medium, and relates to the technical field of cable testing, and the method comprises the steps: exciting a cable terminal through a current pin in the crimping process of the cable terminal, collecting the voltage of the cable terminal through a voltage pin, and obtaining a real-time voltage signal; and evaluating the crimping quality of the cable terminal based on the resistance change condition of the real-time resistance value in the crimping process. According to the invention, the detection behavior and the crimping process are carried out synchronously, and the real-time monitoring of the dynamic change of the resistance in the crimping process is realized, so that the method can be applied to the one-by-one full detection of a production line, and the measurement mode of separating current excitation and voltage collection is adopted. A system error caused by lead resistance introduced by a common lead of current excitation and voltage acquisition is avoided, and real-time performance, non-destructive performance and high precision are effectively considered when the crimping quality of the cable terminal is evaluated.

The invention relates to the technical field of stacking, in particular to a stacking regulation and control method, system and equipment of a stacking robot and a medium, and the stacking regulation and control method comprises the steps that system errors are eliminated by collecting and fusing data of multiple sensors, layered dynamic path planning is conducted to generate the optimal track of a mechanical arm, the posture of an end effector is updated, and stacking is executed through double-closed-loop control. The method comprises the steps of performing joint self-calibration and clamp self-adaptive adjustment, and realizing digital twin monitoring and group intelligent scheduling, and further comprises a corresponding system, electronic equipment and a computer readable storage medium. The effects of improving the cargo box stacking precision, stability and safety, adapting to the cargo boxes of different sizes, achieving state monitoring, optimizing task allocation and improving the overall operation efficiency and reliability of the stacking robot are achieved.

The application discloses a target direction finding method based on a short baseline unified model, which is realized by a computer and comprises the following steps: firstly, an improved polar coordinate representation (MPR) unified model is constructed; secondly, a closed-form initial solution of direction finding under the MPR model is obtained; then, an improved successive unconstrained minimization method based on the MPR is used to solve a quadratic constraint optimization problem to obtain the angle of the target source; thirdly, a direction finding initial solution is used to guide source deployment; fourthly, time-space reference system error calculation is performed; finally, target source TDOA measurement and time-space reference system error elimination and final solution solving are performed; the application effectively avoids the threshold effect of the short baseline positioning system based on the far-field direction finding unified model of the modified polar coordinates, so that the far-field target direction finding method of the unmanned aerial vehicle group based on the time difference of arrival measurement becomes possible; the calibration source and the target source are jointly monitored, the time-space reference system error is eliminated through the time difference measurement of the calibration source, and thus the direction finding precision is improved.

The invention provides a probe frequency response calibration parameter determining method, a probe frequency response calibration parameter measuring system and a storage medium, and the probe frequency response calibration parameter determining method introduces a composite test signal including a steady-state frequency sweep signal and a transient pulse signal. De-embedding calculation is carried out on a data set which is obtained under the two conditions that a probe is not connected to a calibration system and the probe is connected to the calibration system and responds to the same test signal, namely amplitude division is carried out to eliminate link gain deviation, phase subtraction is carried out to strip channel phase deviation, accurate extraction of the independent frequency response characteristic of the probe is achieved, and the accuracy of the independent frequency response characteristic of the probe is improved. Therefore, the frequency response calibration parameter of the probe is determined. According to the invention, system errors introduced by a test environment and a rear-end measurement link are eliminated, the calibration precision of the amplitude-frequency characteristic and the phase-frequency characteristic of the probe in a full working frequency band is improved, and a reliable basis is provided for implementation of accurate real-time anti-distortion compensation in actual signal acquisition of measurement equipment such as an oscilloscope and the like; and the reduction authenticity of the whole measurement system in the high-frequency and broadband signal test is ensured.

The invention provides a dam settlement monitoring pipeline three-dimensional shape reconstruction method and device, electronic equipment and a computer readable storage medium. According to the three-dimensional shape reconstruction method for the dam settlement monitoring pipeline, system errors caused by instrument deflection can be eliminated, and synchronous reconstruction of the full-depth high-precision three-dimensional shape and the section contour of the dam settlement monitoring pipeline is achieved.

The invention relates to the technical field of engine assembly testing, in particular to an error evaluation method of a complex measurement system. The invention provides an error evaluation method of a complex measurement system, which comprises the following steps of: S1, simplifying and customizing a standard sample piece of a complex object to be measured based on the critical dimension of the complex object to be measured; s2, performing calibration detection on the standard sample piece by adopting calibration equipment to obtain a calibration value of the standard sample piece; s3, detecting the standard sample piece by adopting the complex measurement system to be detected to obtain a detection value of the standard sample piece; and S4, according to the calibration value and the detection value, obtaining a precision evaluation value of the to-be-detected complex measurement system. According to the method, the measurement precision of the complex measurement system is evaluated through the standard sample piece, the accuracy of equipment precision evaluation is remarkably improved, the key assembly size of the to-be-detected complex object is detected, the detection precision of the to-be-detected complex object is remarkably improved, the assembly detection difficulty is reduced, and the assembly efficiency and quality are improved.

The invention relates to the technical field of intelligent manufacturing and digital twinning, and discloses an embossed plate production line virtual debugging system based on digital twinning. The system comprises a raw material data acquisition module, a digital twin construction module, an initial virtual debugging module, a physical world trial production module, a production quality analysis module, a deviation analysis module, a compensation adjustment module and a system self-optimization module. The main debugging and optimization work is completed in the virtual space, and a large amount of raw materials, energy and machine hours are saved; a system error between a theoretical model and physical reality can be effectively counteracted through the established compensation mapping model F; the period from product design to stable production is greatly shortened through virtual debugging; the compensation model can be updated online, so that the whole system is always kept near the optimal production state; data and models generated in the debugging and optimizing process are converted into core knowledge assets of an enterprise, and digital inheritance of knowledge is achieved.

The invention relates to the technical field of electronic measurement, and discloses a software instrument system-based short-wave broadcast equipment power automatic calibration system, which comprises a main control unit, a signal excitation unit and a measurement feedback unit. According to the method, an iterative adjustment process is controlled through a main control unit; a measurement feedback unit measures the actual output power of a measured device; and the main control unit directly takes the power difference value as the adjustment amount of the excitation level according to the power difference value between the actual output power and the preset target power, adds the adjustment amount with the current excitation level to obtain the next excitation level, and controls the output of the signal excitation unit until the preset precision is met. According to the method, test link loss calibration is executed before iterative adjustment so as to compensate system errors, a calibration lookup table can be automatically generated after calibration is completed, the problems that a traditional calibration method is low in efficiency and insufficient in precision are solved through an adaptive adjustment strategy and system error compensation, and the calibration accuracy is improved. The method has the beneficial effects of high convergence speed, accurate calibration result and high automation degree.

The invention discloses an overwater combined inertial navigation positioning method based on self-adaptive interactive multi-model, which comprises the following steps: S1, establishing SINS / DVL interactive multi-model according to an interactive multi-model algorithm; s2, according to the SINS / DVL interaction multi-model, firstly inputting interaction, then carrying out model filtering, then carrying out model probability updating and finally carrying out hybrid estimation, and taking an estimation result as combined navigation output; s3, feeding back an error term of updating feedback filtering calculation to inertial navigation; through the interactive multi-model algorithm, rapid adaptation can be achieved when the system state changes, the switching probability of each filtering model is adjusted in a self-adaptive mode, the matching precision between the SINS and the DVL is improved, and the challenges of DVL measurement abnormity and SINS noise fluctuation can be effectively coped with; meanwhile, the AIMM algorithm of the adaptive transition probability is adopted, and the optimal filtering model can be recognized in time in a fast changing environment, so that divergence of system errors is effectively inhibited, and the reliability and precision of a navigation result are improved.

The application discloses a radar plot and AIS track adaptive parallel matching method and system, and belongs to the technical field of radar and navigation information. In order to reduce the algorithm complexity and the dependence of AIS data, the application comprises the following steps: identifying the database arrival data, performing voting on the projected radar plot in a parameter space by a system error extraction module based on an error distribution function to obtain a plurality of counters and filtering the counters by a filter, finally accumulating the results of all the filters and performing peak value detection to extract the system error of the radar plot; performing speed correlation checking on the searched radar track point by a radar plot index module, and searching the radar track point with a speed parameter meeting the requirements; performing sum and optimization on an error function according to a PARZEN window based on the radar track point with the speed parameter meeting the requirements by an error function optimization module; and updating the membership ship number in the AIS table of the database by using the radar track point with the speed parameter meeting the requirements.

The invention provides an acquired data error compensation method for a small-sized thermohaline instrument, belongs to the technical field of electrical digital data processing, and realizes accurate error compensation by constructing a multi-stage neural network tree structure. According to the method, firstly, errors are classified into system errors, random errors and environment interference errors, and second-level and third-level subdivision is carried out to form a complete error classification system; based on the classification system, an optimal path selection function is adopted to dynamically determine a compensation strategy, and corresponding models are selected from a pre-trained miniature neural network library to form a compensation chain. All compensation model structures are subjected to optimization design, different network structures and parameter configurations are adopted for linear errors, nonlinear errors, noise errors, fluctuation errors, temperature errors and salinity mutual interference errors, the total parameter number is controlled to be at a low level, and efficient operation on small equipment is ensured. The technical problem that in the prior art, a small-sized salt thermometer is insufficient in measurement precision under the condition of low energy consumption is solved.

The invention discloses a satellite clock error resolving method considering signal distortion deviation, and belongs to the technical field of satellite navigation and positioning. According to the method, a signal distortion deviation parameterization model is constructed, and the satellite clock error and the signal distortion deviation are solved in a combined mode. The method specifically comprises the following steps: selecting a global or regional reference station network to obtain double-frequency observation data; classifying the receivers and unifying the distortion delay of the same kind of signals; and introducing signal distortion deviation modeling based on an ionosphere elimination combination observation equation, combining precise satellite orbit data, and resolving satellite clock correction and signal distortion deviation parameters through least square or Kalman filtering adjustment. When a terminal user uses a satellite clock error product for positioning, the terminal user can directly use or dynamically estimate the signal distortion deviation according to the type of a receiver, and the positioning precision is improved. By compensating the system error, the limitation that the signal distortion deviation is not modeled in the traditional method is solved, the satellite clock error is accurately estimated, and reliable support is provided for high-precision positioning, navigation and time service.

The invention discloses a landslide deformation prediction method and system combining multi-source data and residual optimization, and belongs to the technical field of landslide deformation monitoring. According to the method, multi-scale spatial-temporal characteristics are extracted through a CvT model to realize preliminary prediction, an xLSTM model with GNSS as external guidance is innovatively introduced to carry out dynamic time sequence modeling and compensation on prediction residual errors, and finally a high-precision displacement prediction value is output through residual error optimization. According to the method, dynamic deep fusion and closed-loop correction of InSAR large-range monitoring and GNSS high-precision data under a deep learning framework are realized, and the key technical bottlenecks of system error accumulation, insufficient multi-source data collaboration and limited nonlinear deformation modeling precision in the existing method are effectively solved; the accuracy, the stability and the physical credibility of landslide prediction are remarkably improved, and the method has outstanding technical advancement and practical value.

The invention provides a control instruction time sequence synchronization method and device of a multi-node industrial control system. The control instruction time sequence synchronization method comprises the following steps: a control node calculates an initial time offset through a calibration frame, loops back a test frame to measure link transmission delay, and compensates a local clock of an execution node to realize initial alignment; periodically broadcasting a reference clock, calculating an accumulated drift amount in real time by an execution node, and adjusting a local clock frequency when the accumulated drift amount exceeds a threshold value; sending a control instruction based on a synchronization period starting moment, synchronizing a trigger signal to enable an execution node to sample data at the same time, and reading the data by a period ending boundary. According to the control instruction time sequence synchronization method, the initial synchronization precision is + / -10ns, the accumulated drift distance is controlled within + / -10ns, the total time sequence deviation is smaller than 100ns, system errors are effectively eliminated, the problem of crystal oscillator deviation is solved, the method can be compatible with an industrial bus, the hardware cost is reduced, and the multi-axis cooperative control precision and stability are greatly improved.

The invention discloses a ship lift chamber control station debugging system, which comprises a flap gate debugging module used for monitoring flap gate action position signals in real time, obtaining telescopic synchronous state parameters of oil cylinders on the left side and the right side, and generating corresponding trimming parameters and feedback instructions according to the difference of the telescopic state parameters of the oil cylinders on the two sides; the anti-collision beam debugging module is used for detecting an action position signal of an anti-collision beam in real time, acquiring telescopic synchronous state parameters of oil cylinders on the left side and the right side, and generating a trimming parameter and a feedback instruction according to the parameter difference of the telescopic states of the oil cylinders; and a ship chamber jacking debugging module. According to the ship lift ship chamber control station debugging system provided by the invention, system errors and transmission machinery inherent errors possibly generated by long-term operation of the system are solved, and position error correction is carried out on an actual position curve of last operation by a speed given curve and a position given curve given by a virtual main driving point each time; and the system internal reference is consistent with the external fact reference.

The invention discloses a temperature control method and device for an IGBT module, and the method comprises the steps: carrying out the initial estimation of the junction temperature of key parameters, such as current, voltage, switching state, frequency, shell temperature and environment temperature, which are collected in real time based on a standard physical thermal network model, and introducing a pre-stored IGBT loss characteristic to improve the basic prediction accuracy; further, a machine learning model is used for mining a complex dynamic nonlinear relation between input variables from historical operation data, and system errors caused by simplification or hypothesis of a physical model are effectively corrected; and finally, taking the fused and corrected junction temperature result as an adjusting basis of a cooling device, and dynamically adjusting the cooling intensity through control algorithms such as PID and the like, thereby ensuring that the IGBT module is always in a safe and efficient operation interval. Therefore, not only are theoretical preciseness and practical applicability considered, but also the robustness and the intelligent self-adaption level of the system under factors such as working condition change, self-aging and external disturbance are remarkably improved.

The invention discloses an ultra-wideband double-difference indoor positioning method considering anchor node configuration and system errors. The method comprises the following steps: step 1, carrying out layout design on ultra-wideband anchor nodes; step 2, ultra-wideband ranging signal acquisition; step 3, preprocessing the ultra-wideband ranging signal data; step 4, performing prior quality control based on known baseline constraint; 5, ultra-wideband double-difference indoor positioning calculation is carried out; after multiple groups of ranging values are obtained, indoor positioning can be carried out after baseline constraint quality control and anchor node and label double difference. According to the invention, the problem of low range finding degree caused by the interference of a complex environment on an indoor range finding signal is solved, and gross error or incredible observation data are identified and eliminated through baseline constraint; double-difference elimination is carried out on systematic errors, the absolute distance measurement precision is further improved, and the reliability of ultra-wideband indoor positioning is improved.

The invention relates to the field of belt conveyor control model analysis, in particular to a multi-motor belt conveyor dynamic model analysis method, which comprises the following steps of: dispersing a belt conveyor system into a generation unit; establishing a system dynamics model; proposing constraint expectation; decomposing an uncertainty part in the kinetic model, and identifying matched and unmatched components in the uncertainty part; the influence of unmatched components on the belt conveyor system in the uncertainty part is verified; establishing a robustness control model based on the nominal part, the system error and the uncertainty part of the dynamic model of the belt conveyor; and the model is verified through dynamics simulation to achieve expected time and change trend. According to the method, modeling is carried out for the long-distance large-dip-angle belt conveyor, and the mismatching uncertainty of an under-actuated system is specifically decomposed; a self-adaptive robust controller is designed, and the speed of the conveyor is restrained by controlling the coordinated driving current of multiple motors; and the action effect of the controller is verified through dynamic simulation of dynamics.