31results about How to "Improve tracking accuracy" patented technology

This application discloses a method, apparatus, storage medium, and product for controlling the current of a charge-and-discharge power supply. The method includes acquiring a target adjustment command, which includes a target current increment. This target current increment is the difference between a first preset current and a second preset current. The first preset current is the target current of the previous adjustment cycle, and the second preset current is the target current of the current adjustment cycle. The method also includes acquiring a voltage increment based on multiple target parameters and the target current increment. These multiple target parameters include the battery electromotive force, battery internal resistance, and line impedance of the charge-and-discharge power supply when it was in a stable state in the previous adjustment cycle. Finally, the method includes acquiring an adjustment amount based on the voltage increment and adjusting the output current of the charge-and-discharge power supply based on the adjustment amount. This method can improve the response speed while ensuring the stability of the output current of the charge-and-discharge power supply.

The application discloses a kind of dual-frequency multi-component joint tracking method, equipment and medium of navigation satellite signal.The method comprises: according to the upper sideband carrier and the lower sideband carrier in dual-frequency navigation satellite signal as local carrier, tracking dual-frequency navigation satellite signal is respectively carried out, and the upper sideband and the lower sideband multi-component correlation value are obtained respectively, the carrier phase error, code phase error, subcarrier phase error of the upper sideband carrier and the lower sideband carrier obtained by jointing the upper sideband and the lower sideband multi-component correlation value obtained respectively are obtained, and the carrier phase, code phase, subcarrier phase of dual-frequency navigation satellite signal are obtained.The technical scheme of the embodiment of the application can improve the tracking precision of navigation satellite signal.

The application discloses an anti-unwinding flexible spacecraft attitude tracking composite control method, first, based on the quaternion method, a flexible spacecraft attitude tracking error kinematics and dynamics model is established; then, the flexible accessory vibration mode, external environmental disturbance and model uncertainty are regarded as a lumped disturbance, a generalized proportional integral observer is designed, and the lumped disturbance is observed and estimated; finally, a non-singular terminal sliding mode surface is constructed, the lumped disturbance observation and estimation compensation of the generalized proportional integral observer is taken as a feedforward signal, and a feedforward-feedback anti-unwinding attitude tracking composite controller is designed. Through determining appropriate control gain, the closed-loop attitude tracking error system is globally finite time stable, and the anti-unwinding effect can be realized. The application can realize finite time attitude tracking of the flexible spacecraft, has high attitude tracking precision and strong robustness.

This invention discloses a label-free real-time blood vessel tracking method driven by dynamic blood oxygenation features, relating to the fields of medical image processing and computer vision. The method includes: acquiring dynamic blood oxygenation signals from a target tissue region; preprocessing the blood oxygen concentration change data; constructing a spatiotemporal matrix of blood oxygenation features; performing adaptive feature extraction using an improved 3D convolutional neural network; establishing a multi-scale blood vessel contour prediction model; dynamically predicting and updating the blood vessel contour using a Kalman filter algorithm; outputting the real-time trajectory of the blood vessel center and boundary contours; and introducing a dynamic feedback mechanism to achieve continuous and stable blood vessel tracking. This invention achieves highly secure blood vessel tracking, significantly improving tracking accuracy, robustness, and real-time performance under tissue movement and complex background interference by utilizing dynamic blood oxygenation features.

This invention discloses an artificial intelligence-based photovoltaic (PV) tracking bracket method, relating to the field of solar photovoltaic power generation technology. The method includes: collecting multi-dimensional environmental perception data and uploading it to an edge computing node; predicting the irradiance distribution for the next 30 seconds using a convolutional neural network and a long short-term memory network; inputting the prediction results, solar angle, and atmospheric attenuation coefficient into a lightweight fully connected neural network to generate a dual-axis tracking angle command; dynamically correcting the angle using a gradient ascent algorithm in conjunction with PV output power feedback; and performing closed-loop regulation through a low-latency CAN bus-controlled servo drive unit. This invention aims to solve the problems of existing PV tracking systems, such as lag response, large control deviation, reliance on high-cost sensors, and lack of multi-dimensional environmental fusion perception capabilities under complex weather and unsteady illumination conditions. It achieves high-precision, robust real-time tracking with low-density sensor configuration, significantly improving power generation efficiency and system adaptability.

This application provides a target tracking method, apparatus, electronic device, and storage medium. The target tracking method includes: acquiring template image features of a template image, wherein the template image includes a target to be tracked, and the template image features include template target features of the target to be tracked; acquiring first image features of a target image to be detected; processing the first image features according to the template image features using a cross-attention mechanism to obtain second image features, wherein the second image features include target features of the target to be detected; and matching the template target features with the second image features to obtain a tracking result for the target to be tracked. By processing the template image features and the target image features using a cross-attention mechanism, the target features to be detected contain feature information of the template target features, improving the generalization ability of the features and achieving high-precision tracking.

This invention relates to the field of photovoltaic power generation technology, specifically to a photovoltaic-storage integrated power supply system and control method for a data center based on MPPT tracking. It includes: an MPPT intelligent tracking unit that works collaboratively with an improved perturbation observation method and a fuzzy control algorithm, and adaptively corrects the photovoltaic maximum power point reference voltage by combining a degradation compensation model established based on sunshine duration and the aging characteristics of photovoltaic modules; an energy storage adaptive management unit; and a data center load dynamic allocation unit. This invention uses the MPPT intelligent tracking unit to collect data such as the cumulative operating years and cumulative actual power generation of photovoltaic modules to calculate the module aging coefficient. It then dynamically corrects the perturbation step size of the improved perturbation observation method by combining real-time power changes of the photovoltaic array. Finally, through dual-algorithm collaborative scheduling and degradation compensation quantification, it integrates multiple parameters to adaptively correct the standard maximum power point reference voltage, effectively addressing the performance degradation problem of photovoltaic modules after long-term operation.

The application discloses an unmanned aerial vehicle obstacle avoidance method based on digital twinning in an unstructured scene, which comprises the following steps: S1, constructing a geometric perception digital twinning system; S2, collecting unknown obstacle information and performing geometric synchronization; S3, performing dynamic modeling and discretization on a virtual unmanned aerial vehicle; S4, constructing a pseudo-control input and a linear prediction model; S5, generating a safe flight corridor; S6, performing local re-planning; S7, establishing a disturbed system and an error system; S8, constructing a robust positive invariant set and performing constraint tightening; S9, constructing a space adaptive tube MPC optimization problem; S10, performing online space adaptive adjustment; and S11, outputting a control instruction and maintaining virtual-real synchronization. By mapping unknown obstacles in a physical space to a virtual space in real time, a safe flight corridor is constructed, local re-planning and space adaptive tube MPC are combined, and the unmanned aerial vehicle can realize safe obstacle avoidance, high-precision trajectory tracking and low control energy consumption in an unstructured environment.

The application discloses a non-singular fast terminal sliding mode vibration active control method based on a compensation function observer, 1) according to elastic dynamics, a fourth-order modal equation of a four-side fixed support plate structure driven by an electromagnetic inertial actuator is established; 2) in view of external unknown interference and modeling uncertainty existing in the system, a compensation function observer is designed to realize real-time estimation and compensation; 3) a non-singular fast terminal sliding mode surface is constructed, and a sliding mode control law is designed in combination with the observer output, so that the singularity problem of a traditional terminal sliding mode is solved, and the time for system state to reach a balance point is shortened through a fast convergence term; 4) a comparison experiment is designed, and the composite control method designed in the application can significantly reduce the vibration amplitude of the four-side fixed support plate while guaranteeing the finite time stability of the system, and has stronger anti-interference ability and higher vibration suppression precision compared with the traditional sliding mode control.

The present application relates to the technical field of integrated navigation, in particular to a positioning method and system based on optical angle measurement and astronomical-inertial integrated navigation. The method first acquires star and navigation satellite images by shooting a star map, and then calculates the attitude of the camera relative to the geocentric inertial coordinate system by identifying and processing the stars, and further determines the coordinates of the navigation satellite in the coordinate system. Through coordinate conversion, the angle information of the navigation satellite relative to the observer in the earth coordinate system is obtained. The optical angle measurement information is fused with the attitude, speed and position information output by the inertial navigation system, the Kalman filter state equation and observation equation are constructed, and finally the real-time high-precision solution and update of the observer's position are realized. The present application combines the accuracy of optical angle measurement, the limited distance reference of astronomical navigation and the autonomous continuity of inertial navigation, effectively improving the navigation and positioning accuracy and reliability under complex environment and satellite denial conditions.

The application provides a mobile robot self-learning robust control method based on a hybrid Kalman filter and belongs to the technical field of robots.The technical scheme comprises the following steps: step 1, a dynamic model of an uncertainty factor;step 2, real-time estimation of state parameters and model parameters of the mobile robot to optimize the original dynamic model;step 3, introduction of an adaptive forgetting factor recursive least square method to dynamically adjust filter parameters;step 4, design of a non-singular fast terminal sliding mode controller based on a saturation function as a system main controller;step 5, establishment of an error correction RBF neural network and introduction of an adaptive error learning strategy;step 6, completion of stability analysis and proof of the control system by means of Lyapunov stability theory and simulation experiment of the optimized model.The application effectively suppresses the chattering of the sliding mode control and significantly improves the control precision and robust performance of the four-wheel robot.

This application discloses a radar low-altitude target detection method and system based on least squares inversion, involving radar and data processing technology. The method includes: establishing the target's motion trajectory based on multipath echo signals received by the radar, and establishing a multipath observation model based on the motion trajectory; establishing residuals and a target function based on the multipath observation model; performing inversion iteration using least squares based on the established residuals and target function, solving the problem along the iteration direction based on the iteration step size; and outputting the inverted parameters for target tracking. This application achieves adaptive compensation for multipath effects by modeling multipath bias and jointly inverting parameters such as target range and elevation angle, thereby improving the accuracy of radar estimation of low-altitude target motion parameters.

This invention specifically relates to an optical target tracking method based on trajectory guidance and spatiotemporal joint decision-making, belonging to the field of computer vision and video information processing technology. The method first extracts image features through an anchor-free twin network architecture, outputting classification, centrality scores, and regression response maps; then, it constructs a sliding window weighted least squares trajectory prediction model, modeling target motion as locally uniformly accelerated motion to achieve target position prediction; subsequently, it generates an adaptive Gaussian heatmap based on trajectory prediction uncertainty, constructing a spatial attention mechanism for trajectory guidance; finally, it fuses visual features and prior trajectory information through a linear weighted fusion strategy to output the target position. This invention effectively utilizes temporal motion information, solving the problems of low tracking accuracy and poor robustness in existing technologies under occlusion and fast-moving scenarios, balancing real-time performance with low computational overhead, and is suitable for ordinary optical and infrared thermal imaging tracking scenarios.

This invention relates to the field of solar power generation technology, and particularly to a control method for a dish concentrator based on an I3-RPS tracking mechanism. The control method includes: establishing a solar direction vector calculation model; establishing a multi-coordinate system to describe the motion of the dish concentrator, and deriving the homogeneous transformation matrix between the coordinate systems; obtaining the pose of the moving platform based on the solar direction vector, and establishing a mapping relationship between the length, velocity, and acceleration of the telescopic rod and the pose of the moving platform through inverse kinematics; establishing an inverse dynamics model based on the principle of virtual work; designing a hierarchical composite control strategy; at the top level, using a parallel synchronous architecture to coordinate the motion of the I3-RPS tracking mechanism; at the bottom level, designing an RBF-FSMC controller for the I3-RPS tracking mechanism, replacing the switching function with a saturation function, dynamically adjusting the saturation function gain and boundary layer thickness through fuzzy rules, and introducing a radial basis function neural network to approximate system modeling errors and external disturbances online. This control method exhibits high tracking accuracy and strong anti-interference capability.

A photovoltaic tracking system with special cross section and eccentricity overcoming device, the main beam cross section is a rounded square tubular structure; the eccentricity overcoming device is installed between the common column and the main beam of the photovoltaic tracking system, and comprises a mechanism support, a mechanism body and a mechanism fixing seat which cooperate with each other; the mechanism support is fixed on the main beam, and the mechanism fixing seat is fixed below the common column of the photovoltaic tracking system; the mechanism body comprises a hydraulic cylinder and a cylinder barrel which cooperate with each other, the upper end of the cylinder barrel is hinged on the mechanism support and moves under the drive of the mechanism support on the main beam, the tail end of the hydraulic cylinder is hinged on the mechanism fixing seat and forms relative movement with the cylinder barrel, the limiting structure of the cylinder barrel and the two springs act on the springs respectively to compress the springs and generate a thrust on the mechanism support to overcome the gravity eccentricity of the rotation of the photovoltaic tracking system, the torsional performance of the main beam is improved and the torsional deflection is reduced, the damping effect is achieved, and the rotation eccentricity of the photovoltaic tracking is overcome.

This invention relates to the field of line marking construction technology, and in particular to a mobile construction method. The method includes acquiring image information of the line to be identified and identifying the deviation information of the line relative to a construction reference position; adjusting the travel direction of the mobile device according to the deviation information so that the mobile device travels along the path corresponding to the line to be identified; when the construction position deviation represented by the deviation information reaches a preset compensation condition, driving a follow-up mechanism to move the construction mechanism relative to the mobile device to compensate for the construction position of the construction mechanism; and controlling the construction mechanism to perform construction output along the adjusted construction path. This invention acquires image information of the line to be identified through an identification mechanism and adjusts the travel direction of the mobile device and the position of the construction mechanism according to the deviation information, enabling not only overall vehicle path correction but also local compensation of the construction mechanism during the construction process, thereby improving the accuracy of the construction path following.

This invention relates to a method for detecting violations by personnel at conveyor belt stations based on an improved S2ANet and trajectory tracking. The method includes acquiring video and segmenting it into images frame by frame; inputting the images into the S2ANet-CBAM algorithm for conveyor belt target detection to obtain conveyor belt data; inputting the images into the YOLOv5 algorithm for worker target detection to obtain worker data; determining whether the conveyor belt is horizontal by comparing the conveyor belt data and worker data; using a Kalman filter to predict the position information of the worker and conveyor belt in the next frame; and using the Hungarian association algorithm to match and track the trajectories of the worker and conveyor belt. Finally, trajectory correction is performed, and the worker's trajectory and the conveyor belt trajectory are drawn, and the existence of violations is determined. This invention solves the problem of overlapping horizontal target boxes between the conveyor belt and the person in industrial applications due to the large size of the conveyor belt target, avoiding trajectory mismatch problems caused by target occlusion and errors caused by camera shake.

This invention relates to the field of photovoltaic power generation technology and discloses a method and system for maximum power point tracking (MPPT) under complex lighting conditions. The method includes: setting several complex operating condition categories for the photovoltaic array and constructing a MPPT model based on all complex operating condition categories; acquiring real-time monitoring data, determining the real-time operating condition category, and generating a real-time tracking strategy in conjunction with the MPPT model; generating a feedback data packet, determining application difference characteristics based on the feedback data packet, and evaluating the application effect to obtain a real-time application evaluation value; generating a correction strategy for the real-time tracking strategy based on the real-time application evaluation value and a preset correction strategy library, and issuing correction instructions until the global maximum power point is located, thereby improving tracking accuracy and efficiency, and significantly improving the power generation efficiency and stability of the photovoltaic power generation system in complex environments.

This invention relates to a speed control method and electronic device for permanent magnet synchronous motors (PMSMs) based on singular perturbation theory. The method includes: establishing a singular perturbation model of the PMSM and decoupling it into a fast-changing subsystem and a slow-changing subsystem; constructing an amplitude control set model predictive controller to obtain a voltage amplitude candidate set and establishing a current prediction model; calculating a q-axis current reference value based on a deadbeat controller; constructing a cost function based on the q-axis current reference value; using the cost function and the current prediction model to traverse the voltage amplitude candidate set; selecting the voltage combination with the minimum cost function as the optimal voltage control signal; and driving the PMSM based on the optimal voltage control signal. Compared with existing technologies, this invention has advantages such as improved current tracking accuracy, suppression of harmonics and torque ripple, ensuring rapid tracking of speed commands, and simultaneously meeting the requirements of high dynamics, high precision, and robust control of motor speed.

The invention provides an intelligent electric control system and method of a new energy loader, and relates to the technical field of intelligent electric control, the operation parameters of a driving motor of a target new energy loader are collected, parameter identification is carried out according to the operation parameters, and a power parameter set is obtained; performing disturbance observation according to the historical measurement data and the power parameter set to obtain a load disturbance observation value, performing frequency spectrum extraction on the load disturbance observation value to obtain a power density spectrum, and determining driving operation characteristics according to the power density spectrum; performing working condition matching according to each historical working condition and the driving operation characteristics to obtain a current operation mode, and determining a compensation response moment according to the current operation mode and the load disturbance observation value; and generating a driving motor response torque instruction of the target new energy loader according to the compensation response torque. Accurate working condition identification and real-time compensation control can be realized based on the motor operation parameters and the load disturbance characteristics, and the response speed and the operation stability of the new energy loader driving motor are improved.

The application discloses a dynamic target tracking and ranging method and system based on fusion matching, relates to the technical field of target tracking and identification, and specifically comprises the following steps: collecting video image data of a to-be-measured target and preprocessing; constructing a self-attention enhanced YOLOv8 target detection model to detect the to-be-measured target; predicting a next frame target estimation box of the video image data by using Kalman filtering, updating the target detection box, and positioning the to-be-measured target position; matching the predicted target estimation box with the current target detection box by using the Hungarian algorithm to establish the motion trajectory of the to-be-measured target; converting the coordinates of the to-be-measured target into coordinates in a robot world coordinate system according to the coordinates of the to-be-measured target in a tracking box sequence and based on the internal and external parameters of a camera; and calculating the distance of the to-be-measured target according to the coordinates in the robot world coordinate system. The application realizes accurate target positioning and ranging by converting the target from a pixel coordinate system to a world coordinate system, and solves the problem of inaccurate target distance calculation in a real-time dynamic environment.

The application belongs to the field of robot motion planning and navigation technology, and provides an arbitrary shape object trajectory planning method and system based on space-time combined A-star, which comprises the following technical solutions: generating all discrete angle corresponding bounding boxes and robot contour mask information based on the constructed robot polygon model; defining a four-dimensional state space and initializing a starting state and a target state; in the four-dimensional state space, for the node with the minimum value, a predefined motion primitive is applied to generate a successor state candidate set; for each successor state candidate node, the discrete angle corresponding bounding box and robot contour mask information of the current node are extracted, and a bit operation is performed on the corresponding area of the environment grid map, and whether collision occurs is judged according to the operation result; when the search reaches the target state or meets the termination condition, a discrete space-time path is generated by backtracking, the discrete space-time path is interpolated and smoothed, and a final executable trajectory is output.

The application discloses a fuzzy PI PWM control method applied to a BOOST circuit and belongs to the technical field of power electronics. According to the method, the initial values of a group of proportional coefficients and integral coefficients with the highest boost efficiency are debugged in advance, fuzzy PI control parameters are generated, proportional coefficient correction amounts and integral coefficient correction amounts corresponding to different output voltage deviation amounts and output voltage change rates are generated and stored in a memory in a table form, then the output voltage is sampled at a fixed time, the output voltage deviation amount and the output voltage change rate are calculated, the proportional coefficient correction amount and the integral coefficient correction amount are quickly obtained by table lookup, and then the next round of proportional coefficient and integral coefficient are calculated and used for PI control of a voltage loop. The method improves the tracking precision of the output voltage, avoids the need for fuzzy PI recalculation each time, significantly reduces the number of floating point operations in adaptive fuzzy PI control, and reduces the operation burden of a single-chip microcomputer.

This invention discloses a Wi-Fi data-driven method for non-line-of-sight tracking in smart homes, belonging to the technical field of Wi-Fi data-driven methods. This invention applies Wi-Fi signal channel change feature extraction technology, hyperbolic region tracking technology, and general-purpose scenario training dataset self-generation technology. By analyzing the characteristic changes of CSI signals in non-line-of-sight scenarios, a new theoretical model is proposed to model the mapping relationship between user behavior and signal features in non-line-of-sight scenarios. The model is learned using a neural network method, and finally, non-line-of-sight tracking functionality is achieved based on the designed and trained model. Compared with existing technologies, this invention can achieve higher tracking accuracy than pure model methods, and has greater flexibility and environmental adaptability, meeting the needs of diverse smart home scenarios.

The application belongs to the technical field of unmanned aerial vehicle control. An unmanned aerial vehicle autonomous tracking method and system based on monocular vision are provided. The target unmanned aerial vehicle image captured by the monocular camera of the tracking unmanned aerial vehicle is obtained, and the three-dimensional space coordinates and the current relative speed of the target unmanned aerial vehicle are determined according to the target unmanned aerial vehicle image. The image error vector is calculated according to the three-dimensional space coordinates. According to the three-dimensional space coordinates and the current relative speed, the current relative speed is optimized by using the Kalman filtering algorithm to obtain the optimized current relative speed, and the position error vector is determined according to the optimized current relative speed. According to the image error vector and the position error vector, the fusion control input vector is determined, and according to the fusion control input vector and the current relative speed, the updated relative speed is determined for tracking the tracking unmanned aerial vehicle. The application greatly improves the control accuracy of the unmanned aerial vehicle autonomous tracking.

The present application relates to the technical field of vehicle-mounted lighting control, in particular to a kind of vehicle-mounted spotlight angle automatic control method based on driver line-of-sight identification, to solve the problem of existing spotlight manual adjustment unsafe, poor dynamic tracking effect.This patent method includes: installing vehicle-mounted camera in front of the driver, continuously capturing head face image and depth information;Through deep neural network extraction facial, eye features, calculate line-of-sight vector in camera coordinate system;Through rotation matrix and translation vector conversion to spotlight coordinate system, get operation vector;Accordingly calculate spotlight pitch and yaw target angle, through fixation point distance correction error, by controller drive motor to rotate to target angle.The present application perfectly realizes the automatic, fast, accurate tracking of spotlight beam to driver line-of-sight, can liberate the hands and energy of driver, avoid the safety risk brought by manual adjustment, significantly improve driving safety and dynamic lighting stability.

This invention discloses a deep learning-based target detection method and device for mechanized operations on power transmission lines, relating to the field of image detection technology. The method includes: performing dynamic scene modeling on the input video stream, extracting foreground moving target regions and newly emerging static target regions, and merging them to generate a candidate region of interest (ROI) set; performing feature enhancement on regions within the ROI set using temporal information from adjacent frames, and employing a deep learning model for target recognition and tracking, outputting detection results with an identity ID and target trajectory; performing behavioral semantic analysis based on the detection results, assessing risk levels according to predefined rules, and generating alarm information. This invention addresses the technical problems of inaccurate target detection and high false negative rates in existing mechanized operations by introducing dynamic scene modeling, temporal feature enhancement, and target association recognition mechanisms, thereby improving target detection and tracking accuracy and achieving automatic risk identification and early warning for operations.

The invention relates to the technical field of power system frequency modulation control, and discloses a boiler master control optimal advance control method and system. Extra coal quantity correction composed of the optimal advanced coal quantity increment and the compensation quantity is applied at a time during first change or trend direction switching; wherein the value of the compensation quantity is equal to the optimal advance coal quantity increment of the previous adjustment stage and is only started during direction switching; the system acquires instantaneous deviation after responding, and updates the optimal advance coal quantity increment according to the deviation only when the operation data comprises a continuous lifting and single lifting load conversion stage; according to the method, quick response, adaptive optimization and stable control are realized, and the AGC frequency modulation performance of the thermal power generating unit is remarkably improved.

The application provides a feedback and estimation method for dynamic response surface of a space tensioned membrane structure, relates to the technical field of dynamic response and state estimation, and comprises the following steps: collecting tensioning force of a rope of the membrane structure, inclination of the rope relative to a balance plane, swing angular velocity of the rope and frame strain through a boundary sensor array, filtering and normalizing the collected signals, and constructing a high-dimensional boundary dynamic observation vector; the application adopts an adaptive surface estimation mechanism without prior model driving, learns dynamic characteristics of the structure through real-time boundary data online, and corrects parameters, so that it is unnecessary to previously establish a finite element model or extract a fixed modal shape, thereby effectively avoiding model mismatch problems caused by factors such as temperature alternation, pre-tension relaxation and structural micro-damage in orbit, significantly improving long-term robustness of surface estimation in orbit, and meeting stable working requirements of the space large tensioned membrane structure under variable working conditions.

The application discloses a method for improving frequency accuracy of repetitive control, which comprises a repetitive control module, and the repetitive control module comprises a decimal delay module and utilizes Lagrange interpolation method to realize the decimal delay in a digital domain, so as to improve tracking accuracy of repetitive control on a periodic waveform with an arbitrary frequency. The decimal delay module is realized by an integer delay unit and a Lagrange interpolation filter. The decimal delay is adopted to replace the integer delay, and the decimal delay is realized in the digital domain with high accuracy by utilizing the Lagrange interpolation method, so that the tracking accuracy of repetitive control on the periodic waveform with the arbitrary frequency is significantly improved.