440 results about "Position tracking" patented technology

The invention relates to the field of personnel action monitoring and recognition, and discloses an intelligent human shape trajectory prediction and alarm system and method based on multi-modal video analysis, and the system comprises a video collection module which is used for collecting video stream data of a monitoring scene; the data processing module is used for extracting motion state information of the target human shape; the trajectory modeling module is used for constructing a trajectory model of the target person; the risk assessment module is used for calculating a behavior risk value; the alarm module is used for triggering alarm; and the optimization module is used for optimizing the trajectory model. Target motion state information is extracted through the data processing module, high-precision input is provided for the trajectory modeling module, and the trajectory modeling module generates a prediction trajectory in combination with a dynamic optimization algorithm. Compared with a scheme depending on coarse-grained detection or simple position tracking in the prior art, the method has the advantages that fine modeling and dynamic prediction of the motion state are realized, the problem that complex behaviors cannot be accurately reflected is solved, and meanwhile, the track prediction precision and the system response capability are improved.

The invention relates to the technical field of smart bracelet positioning, and discloses a smart bracelet position tracking and navigation method, device and equipment and a storage medium, and the method comprises the steps: collecting multi-source positioning data through a built-in multi-sensor system of a smart bracelet, and carrying out the preprocessing, thereby obtaining the preprocessed multi-source data; performing feature extraction and space-time embedding processing to obtain an embedded multi-source feature sequence; inputting the embedded multi-source feature sequence into a multi-source information fusion model for processing to obtain an initial position estimation result and position uncertainty; constructing an adaptive pose map based on the initial position estimation result and the position uncertainty, and optimizing the adaptive pose map to obtain optimized position information; and a multi-level environment map is generated according to the optimized position information, and dynamic path planning is performed to obtain a navigation path and a navigation instruction, so that high-precision and low-power-consumption position tracking and navigation functions are realized, and smooth user experience is provided at the same time.

The invention belongs to the technical field of position tracking control of rigid multi-joint mechanical arms, and discloses a fuzzy self-adaptive visual servo control method and system for a multi-joint mechanical arm system for placing bobbins in a textile workshop, and the method comprises the steps: constructing an image error model according to the positions of feature points on an image plane; the fuzzy logic system is used for processing uncertain items in the system, the instruction filtering and fuzzy self-adaption technology is used for achieving tracking control over the expected trajectory of the system, the problem of calculation complexity is solved, and adverse effects caused by filtering errors are eliminated. In the process of changing the bobbins, the bobbins are placed on a creel through a multi-degree-of-freedom robotic arm, a clamping jaw at the tail end of the robotic arm is required to accurately grab the bobbins for feeding and discharging, and the requirement for accurate and rapid control of the robotic arm is met, so that research on visual servo control of the robotic arm is of great significance. The method has a good control effect, the problem of calculation complexity in the design process of the controller is solved, the trajectory tracking error is smaller, and the system robustness is higher.

The invention relates to the technical field of position tracking, in particular to an intelligent bracelet real-time position tracking visualization method and system. The method comprises the following steps: acquiring multi-dimensional sensing monitoring parameters of a user based on a smart bracelet, performing real-time motion state evaluation of the user, and performing adaptive adjustment of a position acquisition frequency to generate an adaptive position acquisition frequency; performing real-time position positioning acquisition based on the adaptive position acquisition frequency, and performing frequency-by-frequency spatial position positioning calculation to obtain a high-precision compensation reconstruction trajectory; the method comprises the following steps: acquiring public electronic map information, performing scene key element identification, and performing key attribute cognitive marking to obtain a plurality of scene attribute memory anchor points; and performing relative position distribution analysis on the high-precision compensation reconstruction trajectory based on a plurality of scene attribute memory anchor points, and constructing an anchor point space trajectory visual mapping graph. According to the invention, high-precision real-time position tracking of the user is realized, and clear and visual multi-level map information rendering is presented.

The invention discloses a multifunctional automatic space point location tracking measurement method and device, and relates to the technical field of tracking measurement, and the method comprises the steps: obtaining N monitoring points, carrying out the priority ranking, obtaining the monitoring point sequence information, presetting a monitoring collection frequency, and generating the monitoring region information according to the monitoring point sequence information; a built-in high-precision navigation module automatically navigates to monitoring area information, a target icon is fixed on a target monitoring point, and target monitoring image information of the monitoring area information is obtained; training and constructing a point location tracking module, performing target positioning and coordinate extraction, and determining target pixel coordinate information; and target coordinate calculation is carried out to obtain actual space coordinates of the target, the actual space coordinates of the target are stored in sequence, and N space point location measurement results are generated. The technical problems that the monitoring frequency is difficult to guarantee, the measurement efficiency is low and the positioning precision is insufficient in the prior art are solved, and the technical effect of improving the efficiency and precision of space point location tracking measurement is achieved.

The invention relates to the technical field of data calibration, in particular to a photovoltaic panel adaptive tracking data calibration system which comprises a data acquisition preprocessing module, a sun position tracking module, a calibration module, a data fusion module, a management support module, an energy optimization module, a tracking optimization module and an environment enhancement module. The data acquisition and preprocessing module is used for data acquisition and data preprocessing. According to the invention, data acquisition and preprocessing, sun position prediction and tracking strategy optimization, real-time calibration and adaptive control, data fusion and intelligent evaluation, intelligent management and decision support, energy management and optimization, tracking efficiency optimization and feedback regulation, and cooperative work of environmental adaptability enhancement and intelligent maintenance modules are carried out; adaptive tracking data calibration of tracking precision and power generation efficiency is realized, environmental adaptability and an intelligent maintenance mechanism are integrated, and support is provided for development of photovoltaic intelligent data management.

According to the innovative port cabin cleaning scheme, multi-machine cooperative operation of the unmanned excavator and the ship unloader is utilized, and the operation safety and efficiency are remarkably improved. The system integrates multi-sensor mapping, path planning, intelligent collision avoidance and real-time position tracking technologies, and elevation grid map modeling and vehicle positioning in a cabin are realized through a mapping sensing module. The task scheduling module intelligently selects an operation point and plans a path according to the coal pile layout, and the cooperative control module monitors cooperative work of the unmanned excavator and the ship unloader in real time to prevent the collision risk. The work control module is responsible for dynamically adjusting the equipment state and ensuring safe and efficient operation. The scheme flexibly adapts to various ship types and cargo hold layouts, not only improves the port operation efficiency, but also reduces the risk of manual operation errors, and is an important step for modern port automation and intelligent development.

The invention relates to the technical field of motor control, in particular to a control and parameter intelligent optimization method for an anti-impact high-precision PMSM (permanent magnet synchronous motor) feeding servo system, which comprises the following steps of: S1, establishing a physical structure and a dynamic model of a PMSM driving feeding system; s2, designing a variable gain fractional order super-spiral sliding mode controller VGFSTSMC, realizing finite time convergence of position tracking errors by dynamically adjusting and controlling gain coefficients, and inhibiting system jitter; s3, designing an adaptive sliding mode disturbance observer ASMDO, and estimating and compensating unknown disturbance in real time through adaptive gain adjustment and an integral sliding mode surface; s4, identifying a system Stribeck friction model based on a least square method, and inputting the system Stribeck friction model as a friction feedforward compensation FFC to a current loop to reduce the disturbance uncertainty of the system; s5, dynamically adjusting and optimizing control parameters of the VGFSTSMC and the ASMDO by adopting an optimization algorithm so as to minimize a root-mean-square value RMSE of a position tracking error and a maximum instantaneous error; and S6, VGFSTSMC, ASMDO and FFC are combined with an optimization algorithm, and the PMSM is driven to realize high-precision position control.

The invention discloses an underwater vehicle tracking control method with state constraint under input saturation. The method comprises the following steps: firstly, constructing an AUV control system containing model uncertainty and unknown interference based on a kinematics model and a dynamics model of the AUV, and obtaining a reference trajectory of a tracking target; establishing an error model of the AUV control system in combination with the error conversion function, and obtaining a design variable related to the position tracking error; meanwhile, deducing a design variable related to a speed tracking error; constructing a fixed time integral sliding mode lumped disturbance observer based on a design variable related to a position tracking error; and finally, combining a fixed time integral sliding mode lumped disturbance observer and design variables related to a speed tracking error to construct a trajectory tracking control system, and designing a fixed time convergence sliding mode controller by using a continuous input signal and a position and speed adaptive law. According to the invention, the tracking error is stabilized to zero in a fixed time; and continuous control input is realized.

A preset time robust sliding mode control method for a mechanical arm system comprises the steps that (1) under the condition that parameter perturbation, joint friction and external disturbance are considered, a dynamic model and a tracking error system model of the mechanical arm system are established; (2) a robust preset time controller is designed to ensure that the speed tracking error of the mechanical arm converges to zero within preset time; 3) designing a non-singular fast terminal sliding mode controller based on a preset time reaching law so as to ensure that a position tracking error can also converge to zero within the preset time; 4) the feasibility and effectiveness of the method are verified by using a Lyapunov stability analysis method; aiming at a mechanical arm system with parameter perturbation, joint friction and external disturbance, the invention develops a robust nonsingular fast terminal sliding mode control method in preset time so as to ensure that the mechanical arm system can accurately track an expected trajectory signal in the preset time, so that the tracking speed of a mechanical arm is improved, and the tracking precision is improved. And the tracking accuracy and safety of the mechanical arm are ensured.

The invention belongs to the technical field of force / position hybrid control of mechanical arm systems, and particularly discloses a finite-time self-adaptive impedance control method and system for a flexible joint mechanical arm system. In order to solve the problems that the control effect of a mechanical arm system is affected by nonlinear and unknown system model parameters at present and derivation is complex in backstepping design, the fuzzy self-adaptive finite time impedance controller is designed based on the impedance control technology so as to achieve hybrid control over the track and force of the tail end of the mechanical arm. In the design process of the controller, a real control law is constructed to realize finite time stability of the system; and meanwhile, command filtering and fuzzy self-adaptive technologies are introduced to solve the problems of calculation explosion in backstepping design and unmodeled dynamics of a mechanical arm system. By means of the control method, the influence caused by system uncertainty can be effectively overcome, the position tracking error of the mechanical arm system is reduced, and meanwhile it can be guaranteed that all signals in a closed-loop system are bounded within finite time.

The invention discloses an ancient building protection display method and system based on virtual reality, and the method comprises the steps: obtaining user position coordinates and orientation angle data collected by a high-precision position tracking sensor in real time, mapping the data to a corresponding position of a virtual scene, dynamically updating a visual angle in the virtual scene according to the movement and steering of a user, and displaying the visual angle in the virtual scene. The immersive experience of being personally on the scene is realized; a physical rendering technology is adopted to carry out vivid simulation on illumination, materials, textures and the like of the virtual scene, and through technologies of pre-calculation of an illumination map, environment shielding and the like, the real-time rendering calculation amount is reduced, and the rendering efficiency and the visual quality of the virtual scene are improved; various displacement interaction modes including traditional rocker movement, gesture control, body inclination and the like are designed, operation habits of different users are met, user interaction behaviors are analyzed and modeled through a machine learning algorithm, interaction parameters and response modes are adjusted in a self-adaptive mode, and personalized displacement interaction experience is provided.

The invention belongs to the technical field of computer vision and artificial intelligence, and particularly discloses a video target tracking method and device, a medium and equipment, and the method comprises the steps: synchronously obtaining an infrared image and a visible light image which comprise a to-be-detected target; the infrared image and the visible light image are preprocessed; constructing a to-be-detected target tracking model, and training the model; and inputting the preprocessed infrared image and visible light image into a trained to-be-detected target tracking model so as to carry out identification and position tracking on a to-be-detected target. According to the invention, high-precision, high-robustness and high-continuity position tracking of the to-be-measured target in a complex environment can be realized.

The invention discloses a grid-connected inverter complementary sliding mode control method based on a cascade generalized proportional-integral observer, and the method comprises the steps: firstly building a mathematical model of a grid-connected inverter, and enabling the mathematical model to be used for the design of a controller; and a cascade generalized proportional integral observer is introduced to estimate the lumped disturbance of the hyper-local model so as to improve the anti-disturbance capability and the noise suppression capability of the system. By introducing the complementary sliding mode controller, compared with a traditional sliding mode, the position tracking error is reduced by half. By introducing the improved reaching law, a large reaching speed can be kept when the system state is far away from the sliding mode surface, and the sliding mode reaching speed is weakened when the system state approaches the sliding mode surface, so that the chattering phenomenon of the sliding mode is reduced. According to the control method, the coupling influence of the d axis and the q axis can be obviously inhibited, the harmonic content of the three-phase current is reduced, and stable operation of the grid-connected inverter is facilitated.

The invention relates to the technical field of unmanned aerial vehicle flight control, and provides an unmanned aerial vehicle trajectory tracking control method and system based on self-adaptive dynamic programming, and the method comprises the steps: obtaining a position subsystem control input through a control law of a position subsystem based on a position loop expected value, an external interference estimated value and a position tracking error, and carrying out the control of the position subsystem; a position coordinate vector and a first-order derivative thereof are calculated by adopting a position subsystem so as to update a position tracking error, and an external interference estimated value is updated through an interference observer; based on an Euler angle vector reference signal, feedforward control input is obtained through calculation, attitude subsystem control input is obtained through calculation in combination with optimal feedback control input, an Euler angle vector and a first derivative of the Euler angle vector are calculated through an attitude subsystem, an optimal feedback controller is designed for a nominal error system by adopting a self-adaptive dynamic programming method, and the optimal feedback controller is used for controlling the nominal error system. And updating the optimal feedback control input. And the unmanned aerial vehicle system is ensured to have the optimal tracking performance while having relatively high robustness in finite time.

The invention discloses an anti-backlash control method and device for a single-inverter dual-motor parallel system based on an extended state observer. Comprising the following steps: acquiring mechanical angular speeds of two motors, direct-axis current feedback, quadrature-axis current feedback and position feedback of a first motor; obtaining an average angular velocity observation value and a disturbance observation value by using an extended state observer according to the mechanical angular velocities of the two motors and the quadrature-axis current feedback of the first motor; obtaining a rotating speed reference value according to the position feedback and a preset position reference; obtaining a quadrature-axis current reference according to the rotating speed reference value, the average angular speed observation value and the disturbance observation value; obtaining an alpha-axis voltage reference and a beta-axis voltage reference of the first motor according to the quadrature-axis current reference, the direct-axis current feedback and the quadrature-axis current feedback of the first motor and the position feedback; and controlling the three-phase input voltage of the two motors according to the alpha-axis voltage reference and the beta-axis voltage reference of the first motor. According to the method, stable speed control and accurate position tracking can be realized.

The invention discloses a finite time position tracking and synchronous control method and device and a medium, and belongs to the technical field of dual-motor drive servo system control. The method comprises the following steps: constructing a dynamic model of the dual-motor-driven servo system; position tracking errors, speed synchronization errors and acceleration synchronization errors are defined, speed and acceleration states serve as cross feedback variables to be input into the dynamic model, and error signals are generated; introducing a filter and a compensation item through a preset dynamic surface control algorithm to generate a virtual control signal; constructing a finite time adaptive controller based on the error signal and the virtual control signal, and generating a motor control input signal; and estimating and compensating parameter uncertainty and nonlinear gap disturbance of the dual-motor-driven servo system in real time so as to update parameters of the adaptive controller. By means of the method, the technical effects of high-precision position tracking, dynamic synchronization and high-robustness control can be achieved in the dual-motor drive servo system.

A bone pin position tracking method based on optical and electromagnetic localization and Kalman filtering, relating to the technical field of surgical navigation. In order to solve the problems that a single electromagnetic localization method has low precision and is affected by magnetic field interference, and in a single optical localization method, a tracked target is lost caused by an optical signal being easily blocked, designed is a bone pin position tracking method based on optical and electromagnetic localization and Kalman filtering, comprising: using an optical sensor and an electromagnetic sensor to track the position of a bone pin tip, so as to obtain position point sets of the bone pin tip in optical tracking and electromagnetic tracking, respectively; unifying the position point sets of the bone pin tip in optical tracking and electromagnetic tracking to a same coordinate system, and constructing a position observation vector of the bone pin tip; and then, substituting the position observation vector into a position observation equation of the bone pin tip to calculate a motion state vector of the bone pin tip, achieving real-time tracking of the position of the bone pin tip. The method is applicable to complex-path and heavy-load surgery.

A method for greatly reducing data storage requirements of autonomous robots capable of product inventory is described. Instead using high resolution images for label identification and position tracking, a lower resolution map can be searched. Human or machines can identify position of labels, and via a reverse mapping, the corresponding position of a label on the high resolution image can be identified. Except for those portions of the high resolution image showing a label, most of the high resolution image can be discarded. Further processing on the limited image subset can be used to read the labels.

The invention discloses a permanent magnet synchronous motor sensorless control method based on a dynamic position error. A transition stage is provided, per-unit estimation position errors between a first position error signal obtained based on a high-frequency signal injection method and a second position error signal obtained based on a sliding mode observer are compared, an optimal switching speed point is dynamically determined, smooth fusion is carried out on the two position errors by using a nonlinear weighting function, and the optimal switching speed point is obtained. And finally, the estimated position and rotating speed are obtained through a phase-locked loop. And finally, position tracking is carried out by adopting different error signals according to the estimated rotating speed. According to the method, the problem of estimation value pulsation and jump caused by the fact that a traditional method depends on fixed experience switching points is solved, smooth and self-adaptive switching of the two estimation methods in the full-speed domain range is achieved, the control precision and operation stability of the system are remarkably improved, the structure is simple, and engineering implementation is easy.

The invention discloses an electro-hydraulic system adaptive neural network preset time control method, which integrates a neural network real-time learning technology, innovatively introduces a preset time performance function, and designs an adaptive neural network preset time performance controller. For the electro-hydraulic system position tracking control problem, it can be ensured that system output transient performance and steady-state performance converge to a specified performance index range within a preset time, safe and reliable operation of the system is ensured, the unknown dynamic state of the system can be learned in real time through a neural network, high-precision motion control performance is achieved, and the control precision is improved. And the problem of differential explosion in traditional backstepping control of the electro-hydraulic system can be avoided, and the influence of measurement noise on the control precision is reduced.

The invention discloses an extruder moving beam position tracking control method based on adaptive iterative learning, and belongs to the technical field of position control. An extruding machine moving beam position tracking control method based on adaptive iterative learning comprises the following steps that according to the physical property of a moving beam, the motion mode of the moving beam is analyzed, and a kinetic model of a nonlinear parameterized moving beam system is constructed; establishing a fuzzy model for an unknown part in the dynamic model, and determining a position tracking error system of the moving beam; based on a self-adaptive iterative learning control theory, designing a finite-time high-precision position tracking control strategy of the movable beam of the extruding machine; and analyzing the stability of the controller. The invention relates to an extruder moving beam position tracking control method based on self-adaptive iterative learning, which realizes finite time high-precision position tracking control of a moving beam by combining a Fourier series-fuzzy approximation method based on a self-adaptive iterative learning control theory.

The bolt is an important connecting fastener in important equipment of a train, the intelligent detection method and system for the train bogie bolt are provided in consideration that the bolt is a small part and the tightness state of the bolt on the train needs to be detected, and a visual detection system and a position tracking system are constructed and carried on an inspection robot. The method is used for monitoring the train number of a train, monitoring the position of a bogie in real time, positioning a bolt and finally carrying out abnormity detection on the bolt based on the improved YOLOv8. The method comprises a system triggering module, a position tracking module, a visual positioning module, an image data acquisition module, a data storage and transmission module and a YOLOv8 improvement module. For the visual part, a binocular high-precision industrial camera is used for carrying out image data acquisition on the train bogie bolt, processing the image data, and transmitting the image data to the improved YOLOv8 for detection; the method is suitable for rail train bogie bolt anomaly detection, point cloud processing and image processing are combined, the detection efficiency is high, and the detection result is accurate.

The invention discloses an unmanned ship safety control method and system based on an adaptive neural network observer, and relates to the technical field of unmanned ship control, and the method comprises the steps: building a second-order dynamic model of an unmanned ship through a kinetic equation, and obtaining the actual position and speed state of the unmanned ship; designing an adaptive observer based on a neural network by using a neural network approximate nonlinear dynamic state so as to estimate a first-order system position state and a second-order system speed state under DoS attack and external interference; determining an actual and estimated position tracking error of the unmanned ship according to a preset expected trajectory in combination with the actual and estimated position states, and constructing a virtual controller; designing a nonlinear filter according to the virtual control signal to obtain a trajectory tracking signal of a second-order speed system, and constructing an adaptive controller in combination with the estimated speed state; based on a virtual controller and an adaptive controller, expected trajectory tracking of the unmanned ship under DoS attack and disturbance is realized.

The invention discloses an under-actuated unmanned ship trajectory tracking control method based on preset time error constraint. The method comprises the following steps: acquiring a three-degree-of-freedom kinematics and dynamics model of an actual underactuated unmanned ship; determining a position tracking error and an azimuth angle tracking error between the underactuated unmanned ship and the reference trajectory; designing a preset time virtual control law; setting a longitudinal speed error and a yawing angular speed error of the underactuated unmanned ship; and designing a time-varying gain auxiliary dynamic system, and designing a preset time controller by using an adaptive self-organizing neural network. According to the invention, through the asymmetric preset performance function constraint error, the self-organizing neural network dynamic approximation disturbance and the model uncertainty, the preset time filter suppression differential explosion and the auxiliary dynamic system compensation input saturation, the high-precision trajectory tracking in the preset time is realized; the method has the advantages of controllable convergence time, unconstrained initial error and high calculation efficiency, and is suitable for autonomous navigation of the underactuated unmanned ship in a complex marine environment.

The invention provides an unmanned underwater vehicle trajectory tracking control system based on preset time and performance, and aims to improve trajectory tracking precision and stability in underwater operation tasks. The method comprises the following steps: establishing an unmanned underwater vehicle mathematical model; designing a preset time preset performance function, and introducing an adjustable function changing along with time to enable the boundary function to have a smooth characteristic in a convergence process; a time-varying gain auxiliary system is adopted to process an input saturation problem; designing a disturbance observer to realize rapid attenuation of disturbance, and enhancing the robustness of the system by introducing a residual adjustment function based on a smooth nonlinear model; and finally, integrating the interference observer and an auxiliary system to deduce a trajectory tracking scheme. The result shows that the longitudinal speed fluctuation is reduced by 69.2%, and the swaying speed fluctuation is reduced by 32.7%; the north position tracking performance is improved by 30.8%, the east position tracking performance is improved by 16.7%, the speed fluctuation is effectively reduced, and the tracking performance, the system stability and the anti-interference capability are improved.

The invention discloses a permanent magnet synchronous motor sensorless system MTPA control method based on double-shaft injection, and belongs to the technical field of permanent magnet synchronous motor MTPA control. The method aims at solving the problem that in sensorless control, the optimal current vector angle tracking precision of MTPA control is reduced under the influence of position observation errors, motor saturation nonlinearity and a cross coupling effect. Comprising the following steps: injecting a high-frequency voltage signal into an observation shafting, obtaining a rotor position tracking error signal, and obtaining a rotor position observation signal and a rotating speed observation signal; introducing a current vector compensation angle on the basis of the rotor position observation signal to obtain a compensated rotor position signal, and establishing an MTPA shaft system; an auxiliary high-frequency voltage signal is injected into an MTPA shaft system; and constructing an MTPA shafting motor torque equation considering the position observation error and the cross coupling effect, constructing an MTPA shafting efficiency optimization operation control criterion, and adaptively calculating a current vector compensation angle. The method is used for motor sensorless system control.

The invention discloses a self-adaptive sliding mode ship trajectory tracking control method based on output redefinition, and the method comprises the steps: S1, building an under-actuated ship mathematical model, and redefining the position of the under-actuated ship mathematical model; s2, designing a position tracking error, and performing derivation on the position tracking error; s3, designing a first linear sliding mode surface and a second linear sliding mode surface according to the position tracking error and the tracking error after derivation; s4, designing longitudinal control force and yawing control torque of the ship based on the first linear sliding mode surface and the second linear sliding mode surface in combination with an adaptive technology; and S5, position tracking errors are adjusted through the longitudinal control force and the yawing control torque, convergence of the position tracking errors is achieved, and therefore trajectory tracking is achieved. According to the method, the under-actuated problem is solved by designing the ship longitudinal control force and the yawing control moment of the under-actuated ship mathematical model; and meanwhile, the position tracking error is adjusted through the longitudinal control force and the yawing control torque, so that the tracking error can be quickly converged, and trajectory tracking is realized.

The invention relates to the technical field of artificial intelligence, in particular to a multi-dimensional tennis action analysis system, which comprises a data acquisition module, a data preprocessing module, an evaluation analysis module and a feedback interaction module, and is characterized in that the data acquisition module comprises a posture data acquisition unit, a ball path and walking tracking unit and a motion parameter acquisition unit; the data preprocessing module carries out space-time calibration on posture, track and motion parameters based on a timestamp synchronization mechanism, a fusion data set is formed through data cleaning and standardization processing, and the evaluation analysis module is used for distinguishing action types, integrating scores of posture dimensions, power generation dimensions and drop point dimensions and generating a comprehensive evaluation report; and the feedback interaction module displays an evaluation result in real time on an interface based on characters and visual icons and outputs historical analysis. According to the invention, the data validity is guaranteed, the error interference is eliminated, the analysis efficiency and the professionality of the evaluation result are improved, the use threshold is reduced, and the universality and practicability of the system are improved.

The invention discloses a precise position tracking control algorithm based on real-time iterative compensation, and the algorithm comprises the following steps: taking a single axis of an X-Y motion platform as a research object, and obtaining a transfer function of the X-Y motion platform through parameter identification; the position tracker adopts a discrete PID (proportion integration differentiation) feedback control algorithm to obtain a feedback control output signal; an FIR (finite impulse filter) parameterization fixed structure controller is adopted to carry out feedforward control; a disturbance observer module is designed, disturbance observer output is compensated to control input, and a low-pass filter is introduced; and performing real-time iterative compensation control based on a Kalman filter. The Kalman filter is introduced into a real-time iterative compensation strategy provided by the invention, so that the noise influence of the system can be inhibited to a certain extent, and the anti-interference capability and the tracking precision of the system are further improved; in combination with a gating recursive unit prediction result and a model state space equation recursive prediction result, a better noise processing capability is provided by estimating a system state and a noise covariance.