98 results about "Fast tracking" patented technology

The invention provides a method for controlling the output power of a hybrid energy storage system, and the method comprises the steps: building a nonlinear state-space equation through a switching function model of a reconstruction type bidirectional Buck / Boost converter, and deducing a prediction model of the output power of the system. On the basis, a differential algebraic coupling model of output power and inductive current is constructed, and a power prediction problem is converted into an inductive current control problem. Aiming at the operation characteristics of the hybrid energy storage system, a cooperative control architecture in which a supercapacitor preferentially responds to transient power and a storage battery dominates steady-state power supply is designed, and a time-varying reference power track is generated by monitoring the operation state of the system in real time and fusing a target function curve. A model prediction control algorithm is introduced, rapid tracking of reference power is achieved in a rolling optimization mode, and power distribution time sequences of different energy storage units are effectively coordinated. According to the method, the operation economy optimization is realized while the system reliability is improved, and an innovative solution is provided for cooperative control of the energy storage system in the intelligent power grid.

The invention is suitable for the technical field of automatic driving vehicle control, and provides an automatic driving track rapid tracking control method based on online neural network learning, which comprises the following steps: firstly, designing an adaptive model prediction controller, then making a data set and training a fuzzy radial basis function neural network; then, online learning of the fuzzy radial basis function neural network is carried out; and finally, accelerated optimization of the training process of the fuzzy radial basis function neural network is carried out. The automatic driving track rapid tracking controller based on online neural network learning provided by the invention has the remarkable advantages that the neural network model is trained by using control data of MPC (model predictive control), and a nonlinear relation is fitted to approximate the MPC, so that the calculation efficiency is effectively improved, and the rapidity of the controller is improved; the controller can collect real-time data, update a data set and learn new neural network weight parameters online in the process of tracking a reference trajectory, and shows better adaptability and precision compared with a traditional model prediction controller.

The invention relates to the technical field of voltage control, and discloses an ESC voltage regulator voltage control method and system based on fuzzy adaptive PID, and the method comprises the steps: collecting the output voltage of an ESC voltage regulator and a preset target voltage in real time, calculating a voltage error and an error change rate after filtering, and carrying out the calculation of the error change rate; dividing fast tracking, precise adjustment and anti-interference stability maintenance stages according to errors and change rates and generating control signals, calling corresponding fuzzy rule subsets to deduce proportional, integral and differential gain adjustment amounts, generating real-time gains in combination with initial PID parameters, calculating control amounts by using position type PID based on the real-time gains, converting the control amounts into signals to drive power switch tubes, and controlling the power switch tubes. And closed-loop adjustment is formed. According to the method, the problem that a traditional control method is poor in performance under multiple working conditions is solved, cooperative control over rapid tracking, precise adjustment and anti-interference stability maintenance of the output voltage of the ESC voltage regulator is achieved, it is ensured that the ESC voltage regulator can output stable voltage under the working conditions of starting, steady-state operation and load sudden change, and the requirement for high voltage control precision and dynamic response is met.

The invention provides a reactive compensation optimization method and system for a mining frequency conversion system, and the method comprises the steps: collecting the multi-dimensional data of the mining frequency conversion system, and carrying out the feature extraction and preprocessing, and obtaining the preprocessing data; the phase fast tracking module accurately obtains phasor parameters according to the preprocessed data, and the phasor parameters serve as input signals and are used for a phase locking ring to achieve phase and frequency locking of the mining frequency conversion system; constructing a multi-parameter fitness function by adopting a particle swarm algorithm, and dynamically calculating and searching an optimal control parameter combination; instantaneous reactive power and harmonic current are detected and analyzed in real time by adopting an instantaneous reactive power detection technology; the instantaneous reactive power and the harmonic current are input into a fuzzy PI controller, and dynamic error compensation is carried out in combination with the optimal control parameter combination; the static synchronous compensator controls output compensation current to complete reactive compensation and harmonic current treatment; compensation verification and feedback are carried out, and the electric energy consumption condition of the mining device is monitored and predicted in real time.

The invention discloses an electric linear servo system control method based on cascade LESO-DISMC. The method comprises the following steps: firstly, establishing a complete mechanism model of a permanent magnet synchronous motor servo loading system; then designing DOB interference observer real-time compensation by adopting a LuGre friction model and a gap dead zone model; a feedforward control quantity is constructed by utilizing a measurable displacement signal, and redundant torque is inhibited; designing a dynamic integral sliding mode controller to ensure global stability; a high-low bandwidth LESO is constructed, and both fast tracking and smooth filtering are considered; and finally, trajectory optimization is carried out, a smooth trajectory is generated by adopting polynomial interpolation for the step and triangular wave signals, and mechanical vibration is inhibited. According to the method, a LuGre friction model is adopted to compensate nonlinear friction, cascade linear LESO and sliding mode control are combined, a track is optimized through an S-shaped curve, and the problem of'differential explosion 'is solved; according to the method, instruction smoothing, core control and friction compensation are fused, and the anti-interference capability and the loading precision of the system are improved.

The invention belongs to the technical field related to casting, and discloses a rapid tracking and predicting method and system for involved bubble movement in the casting and mold filling process. The method comprises the following steps: (1) carrying out grid division on a three-dimensional geometric model for casting and mold filling; (2) calculating the filling rate, the speed and the pressure intensity of each grid in a casting mold filling cavity at the moment i in the mold filling process; identifying bubbles in the cavity and grids contained in each bubble; and (3) repeating the step (2) until updating of the filling rates, the filling speeds and the pressure intensities of the grids in the bubbles at all moments is completed, so that tracking and prediction of bubble movement in the casting and mold filling process are realized. By means of the method, tracking and calculation of involved bubbles in the mold filling process are achieved, and the solving accuracy of casting numerical simulation software is enhanced.

The invention discloses a broadband harmonic type analysis and propagation path tracking method for a flexible DC power grid system, and the method comprises the following steps: determining the number and positions of DC network harmonic monitoring points according to an electrical main wiring diagram of the flexible DC power grid system, and the harmonic limit values of different types and frequencies in each DC network harmonic monitoring point; determining the sampling frequency and interval of each converter station harmonic monitoring point, and carrying out harmonic online monitoring on the DC side bus current of each converter station of the DC power grid; when a harmonic amplitude exceeding event occurs in the direct-current power grid, determining the type of the exceeding harmonic and the frequency or frequency band of the exceeding harmonic needing to be tracked, and issuing a monitoring instruction to all monitoring points; and according to the amplitude relation of the harmonic waves needing to be tracked by each harmonic wave monitoring point in the same time period, rapid tracking of the harmonic waves in a direct current transmission network propagation path is realized by taking the frequency as the characteristic. According to the invention, rapid tracking of propagation paths of harmonic waves with different frequencies or frequency bands in the flexible DC power grid system is realized.

The invention discloses a rapid power calculation method suitable for an electric energy meter and an acquisition terminal, the electric energy meter and the acquisition terminal, and relates to the technical field of electric power measurement. According to the method, voltage and current signals are sampled, direct-current components are removed, and harmonic interference is suppressed through band-pass filtering; estimating the frequency of the power grid in real time by using zero-cross detection and linear interpolation; processing the filtered voltage and current signals by adopting a delay cancellation model based on a rotation matrix, and eliminating a negative frequency component to generate a corresponding orthogonal vector; and synchronously calculating active power and reactive power through algebraic operation according to the orthogonal vector. According to the method, establishment time delay introduced by a traditional low-pass filter is avoided, rapid tracking of a power value can be achieved when the load power is subjected to step change, electric energy metering deviation in the transient process is effectively reduced, and meanwhile calculation accuracy and robustness under the power grid frequency fluctuation working condition are improved through a frequency self-adaption mechanism.

The invention discloses a non-singular fast terminal sliding mode observer based on a neural network phase-locked loop. A Sigmoid function is adopted to design a non-singular fast terminal sliding mode surface in the observer; a stator current error system is defined, an equivalent item of a sliding mode control law is obtained according to an equivalent sliding mode control principle, a switching control law is designed for control of the stator current error system state on a sliding mode surface, and the sliding mode control law in the observer is obtained according to the equivalent item and the switching control law; introducing a rapid tracking differentiator comprising a terminal attractor, wherein the rapid tracking differentiator is used for accurately tracking and filtering the back electromotive force; and a phase-locked loop in the observer is controlled through the BP neural network, and the phase-locked loop is used for extracting an electrical angle and an electrical angular velocity signal from the back electromotive force to obtain a final sliding-mode observer. According to the method, the convergence speed is effectively increased, high-frequency buffeting is reduced, phase delay is compensated, and the dynamic performance is improved.

The invention relates to the technical field of photovoltaic power generation system control, and provides an MPPT control method and system based on an adaptive fuzzy neural network, and the method comprises the steps: synchronously collecting voltage, current, illumination and temperature signals, and generating original sensing data; transmitting the generated original sensing data to a memory mapping area through a hardware channel; sensing data is obtained from the memory mapping area, calculation is executed, a power variation and an illumination variation are predicted, a fuzzy reasoning algorithm is operated based on the power variation and the illumination variation, and a power point decision scheme is obtained; a fuzzy rule is updated based on the predicted power variation and illumination variation, the updated fuzzy rule is fed back to the dual-core heterogeneous processor in real time, and fuzzy reasoning logic is optimized; and driving the four-phase interlaced power topological structure to work in an interlaced manner according to the power point decision scheme so as to realize maximum power point tracking. According to the invention, rapid tracking and high-precision stable control of the maximum power point of the photovoltaic array in a complex environment can be realized.

The invention discloses a model-free predictive current control method based on an improved observer, and belongs to the technical field of permanent magnet synchronous motor control. The control method comprises the following steps: firstly, by analyzing the frequency characteristic of ESO, selecting an extended state observer order for obtaining balance between the anti-interference capability and the noise suppression capability; secondly, designing a model-free predictive current loop controller, and calculating the observer gain through a bandwidth method; then, a judgment mechanism of a current loop controller is constructed, the mechanism judges whether the system is in a steady state or not at the moment according to the current deviation value in the current state, and therefore the observer order with the better control effect is selected. According to the model-free predictive current control method based on the improved observer, the anti-interference performance of the system and the noise suppression capability of the current are remarkably improved, it is guaranteed that the improved observer has rapid tracking response and excellent steady-state performance, and the robustness of the control system is enhanced.

The invention relates to an unmanned aerial vehicle real-time tracking planning method based on multi-trajectory optimization and evaluation, and the method comprises the steps: obtaining the position and speed of a target at a current moment, and generating a potential target point set and corresponding probability distribution; sampling the potential target point set to obtain candidate target points, and planning a collision-free candidate path for each candidate target point; performing dynamic feasibility processing to generate a time optimal candidate trajectory; and selecting the time optimal candidate trajectory with the highest score as the final execution trajectory at the current moment by using the comprehensive evaluation function. According to the method, a time-consuming trajectory planning process is preposed, so that the real-time performance of tracking is greatly improved; by exploring multiple possibilities of the future position of the target, the tracking continuity and robustness are ensured; the comprehensive evaluation function is used for comprehensive consideration, it is ensured that the unmanned aerial vehicle can avoid obstacles and keep a safe distance while fast tracking is conducted, and the success rate of a tracking task is increased.

The present invention discloses a method for fast target pursuit of fixed-wing aircraft that combines improved SiamFc and gimbal control. An improved SiamFc model is obtained by pre-training the improved SiamFc network with data; the ground end receives the image captured by the target detection module, selects the target and obtains the target features, and transmits them back to the target detection module; the target detection module runs the improved SiamFc model, and obtains the target pixel position based on the real-time image and target feature input; the gimbal control module uses the difference between the target pixel position and the center pixel position of the camera image as the error, and controls the gimbal movement to track the target; the gimbal obtains the gimbal attitude based on the gyroscope data, and transmits it to the fixed-wing control module; the fixed-wing control module adjusts the fixed-wing attitude based on the gimbal attitude to pursue the ground target. The present invention controls the flight attitude of the fixed-wing aircraft by controlling the gimbal camera attitude, thereby overcoming the shortcoming of poor flexibility of the fixed-wing UAV and achieving fast tracking of ground targets by the fixed-wing aircraft.

The application belongs to the cross field of electric power system and power electronics technology, and particularly relates to a regional power grid power quality treatment method for multi-type subject access. By introducing advanced phase compensation, the phase lag of the detection link is calculated and fully compensated in real time, so that the extracted harmonic component is instantaneously synchronized with the actual harmonic of the power grid. In combination with an adaptive hybrid modulation technology, the dominant harmonic frequency band can be focused on compensation. A fully decoupled control based on feedforward is adopted, which eliminates the cross coupling between the d and q axis currents, so that the inner loop controller can realize fast tracking with almost no overshoot. Meanwhile, the adaptive adjustment mechanism of the PLL bandwidth ensures that the synchronization signal is fast and robust when the power grid changes.

The invention provides a voltage stability margin monitoring method and device, a storage medium and computer equipment, and the method comprises the steps: obtaining the current state information of a power system, inputting the state information into a preset strategy network, and tracking a target P-V curve after an optimal action strategy is executed when the optimal action strategy corresponding to the state information is determined; as the strategy network is obtained by taking the state information of the power system as the state space and taking the increment of the active power as the action space to carry out optimization learning, the tracking speed of the P-V curve can be controlled by selecting the action strategy in the action space, and when the tracking speed is too high, the precision of the tracked P-V curve is reduced. Therefore, the optimal action strategy is sought based on the current state information of the power system, and the tracking speed and the positioning precision are balanced, so that the target P-V curve can be tracked as quickly as possible while the monitoring accuracy is maintained, and the real-time monitoring of the voltage stability margin is realized.

This application relates to an analog-to-digital conversion circuit and method with a fast tracking mechanism. An analog-to-digital conversion circuit with a fast tracking mechanism. The positive and negative terminal capacitor arrays receive positive and negative terminal input voltages and output positive and negative terminal output voltages. A first comparator compares the positive and negative terminal output voltages according to a reference voltage to generate a first comparison result. A second comparator compares the positive and negative terminal output voltages to generate a second comparison result. When the difference between the positive and negative terminal output voltages is outside a preset range according to the first comparison result, the control circuit does not perform level boosting. The control circuit sets the voltage drop and rise tracking directions of the positive and negative terminal capacitor arrays, and switches the capacitor enable combinations according to a set of digital codes according to the second comparison result in each switching stage, and outputs the corresponding digital code as a digital output signal when the positive and negative terminal output voltages are equal.

The invention discloses a tornado field unmanned aerial vehicle tracking method and system based on multi-mode perception and dynamic path planning and an unmanned aerial vehicle, and the method comprises the steps: integrating meteorological radar data, a satellite cloud picture and multivariate data collection equipment sensing information, combining reinforcement learning and a multi-target optimization algorithm, and planning an optimal tracking path; the unmanned aerial vehicle cluster works cooperatively with a self-organizing network through hierarchical formation, and realizes real-time measurement and minute-level data return of a three-dimensional wind field in a tornado core area by adopting local storage and satellite direct transmission dual channels. According to the tornado field unmanned aerial vehicle tracking method based on multi-modal sensing and dynamic path planning, the problems of low resolution, response lag and the like of a traditional detection means can be solved, and rapid tracking and accurate measurement of a tornado three-dimensional wind field are achieved.

The invention discloses an anisotropic well seismic ray shortest path fast tracking method comprising the following steps: S1, data preparation: S11, picking up a velocity gradient maximum value and a velocity gradient minimum value; s12, dividing the speed model into uniform grids at equal intervals; s13, initializing an observation system; s14, initializing a grid node; s2, processing a single grid obtained by subdivision, and constructing a distance table of a single grid node, an inclination angle table of ray paths of two grid nodes in the grid node and two trigonometric function tables of different ray inclination angles; determining an effective propagation range of the sub-wave source; and S3, carrying out anisotropic ray tracing. According to the method, the calculation speed of the in-well earthquake shortest path ray tracing algorithm of the anisotropic medium is greatly improved on the premise of ensuring that the precision is not influenced.

The application discloses a kind of secondary steam temperature process signal differential control method and system, utilize first subtracter to carry out subtraction operation to secondary steam temperature process signal and the second integrator output second integral signal, obtain feedback output signal;Utilize first integrator to integrate feedback output signal, obtain first integral signal;Utilize second integrator to integrate first integral signal, obtain second integral signal;Utilize first addition module to process first integral signal, obtain first superimposed signal;Second superimposed signal is obtained by using second addition module to process second integral signal;Utilize second subtracter to subtract first superimposed signal and second superimposed signal, obtain first subtraction signal, utilize fixed proportion controller to obtain fixed proportion control signal;Utilize third adder to superimpose secondary steam temperature process signal and fixed proportion control signal, obtain fixed proportion fastest tracking differential signal.The embodiment of the application provides a kind of secondary steam temperature process signal differential control method and system, improve the output tracking input differential tracking efficiency of secondary steam temperature process signal.

The invention relates to the technical field of permanent magnet synchronous motors, in particular to a multi-motor position cooperative control method for a robot, and the method comprises the steps: collecting the state information of multiple motors (taking double motors as an example), and building a discrete prediction model; calculating an unconstrained reference voltage based on model prediction position control; estimating load torque on line by using a Luenberger observer and introducing voltage calculation; performing one-step forward prediction based on the prediction model, and performing delay compensation and linear boundary amplitude limiting processing on the reference voltage; a target function containing a position deviation item is constructed, a deviation compensation item is obtained by solving partial derivative of the target function, and the compensation item is directly coupled to q-axis reference voltage; and finally, the processed voltage is subjected to SVPWM modulation to drive the double motors to operate, and high-precision synchronization and rapid tracking control of the double motors after reference voltage coupling deviation compensation are achieved.

The invention discloses a climate public opinion data analysis and system based on multi-agent collaboration. The technical problems that in information acquisition and analysis of public opinions related to global climate changes, the data processing capacity is insufficient, cross-language understanding is limited, the real-time performance is poor, and the prediction capacity is weak are solved. The core technology module comprises a cue word embedded neural network crawler information collection module which is used for realizing intelligent collection and analysis of public opinion data in a network space; the multi-agent collaborative instant text analysis and content generation module is used for rapidly tracking global climate policy evolution and public opinion information; and the energy climate public opinion AI report generation module based on construction information splicing is used for dynamically fusing the generated content to provide depth and breadth coexistence information support for climate negotiation.

The invention discloses a thermal power generating unit primary frequency modulation performance improvement method based on a fast tracking differentiator, and aims to improve the primary frequency modulation response speed and control precision of a thermal power generating unit under power grid frequency disturbance. The method comprises the following steps: acquiring a frequency deviation signal, and decomposing the frequency deviation signal into a low-frequency filtering signal and a high-frequency differential signal by using a rapid tracking differentiator; calculating a system working condition index based on a decomposition result, and dynamically adjusting a fast factor and a filtering factor; a short-term prediction feedforward compensation signal is constructed, and historical information is introduced through a gating mechanism; and superposing the feed-forward compensation signal and the PID feedback control signal, and outputting a frequency modulation control instruction. The method can be directly integrated on the basis of an original frequency modulation system structure, has the advantages of being high in response speed, high in adaptability, good in frequency difference fluctuation suppression effect and the like, and is suitable for a primary frequency modulation control scene of a thermal power generating unit under a new energy high-permeability background.

This invention relates to the field of computer vision technology, specifically to a method for fast tracking and fusion of image line segments based on multi-point optical flow. The method includes: acquiring an image sequence arranged in chronological order; verifying whether the image sequence is continuously captured; preprocessing all images in the continuously captured image sequence and calculating gradients; processing the images in the preprocessed image sequence one by one in sequence order; for the currently processed image, extracting multiple line segments from the currently processed image; fusing and filtering the multiple line segments to obtain a set of line segments to be tracked in the currently processed image; for each line segment to be tracked in the set of line segments to be tracked, using a multi-point optical flow method for tracking, obtaining a set of tracked line segments in the currently processed image as the result of fast line segment tracking and fusion. This invention can improve the accuracy and efficiency of image line segment tracking.

The application discloses a security and warning robot instruction execution system for quick tracking of a holder, which acquires continuous image frames, a current angle of the holder and a circumferential obstacle distance, extracts center coordinates, scale variation, a motion direction and confidence of a warning target, constructs a warning intention propagation graph containing a target, a warning sector, a holder margin, a chassis pass, an obstacle suppression and a loss risk node to obtain a tracking intention value, generates a boundary pressure value according to a distance from the target to a boundary of the image, an interframe displacement towards the boundary, a remaining rotation angle of the holder and a circumferential passable distance of the chassis, determines a current main tracking target, and generates a pre-rotation angle of the holder, a segmented rotation speed curve and a chassis compensation rotation angle, and generates a target residual sector and recaptures the target when the confidence is reduced, so that the tracking stability in a quick moving and short-time shielding scene is improved.

The invention relates to the technical field of well test interpretation, and discloses a bus current reconstruction method of an SPWM (sinusoidal pulse width modulation) modulated electric drive system, which is characterized in that a bus current value is reconstructed by sampling phase current and combining an algorithm, accurate estimation of a bus current instantaneous value can be realized by using detection values of two phase current sensors, and a bus current dynamic value can be accurately captured. The technology not only overcomes the limitation that a traditional estimation algorithm only pays attention to an average value and ignores dynamic change, but also can quickly track the dynamic fluctuation of the bus current under a complex working condition, is not influenced by the change of internal parameters of a driver, and effectively improves the dynamic performance and accuracy of bus current estimation. The simulation result verifies the reliability and accuracy of the reconstruction algorithm, expands the application boundary of the bus current control measurement technology of the electric drive system, and has important engineering significance for guaranteeing the stable operation of the electric drive system.

The present invention provides a fast tracking device applied to a gravity unloading system, aiming to improve the tracking accuracy of the servo system while avoiding the internal vibration and impact of the system caused by the sudden acceleration of the two-degree-of-freedom motion platform; the device comprises a two-degree-of-freedom tracking slide platform, an active constant force system and a three-degree-of-freedom motion system; the two-degree-of-freedom tracking slide platform realizes the sliding motion of the active constant force system along the x-axis and the y-axis; the active constant force system controls the motion distribution to reduce the acceleration of the two-degree-of-freedom tracking slide platform; the three-degree-of-freedom motion system is used to install a simulation object and realize the movement of the simulation object in the three-degree-of-freedom directions.

The invention provides a robot motor current prediction control method, device and equipment based on an extended Kalman filter, and a computer readable storage medium. The robot motor current prediction control method based on the extended Kalman filter comprises the steps that the extended Kalman filter is adopted to conduct state estimation and noise filtering on robot motor current, state estimation comprises a prediction stage and a correction stage, in the prediction stage, a prediction value at the current moment is calculated according to a state estimation value at the previous moment, and in the correction stage, the prediction value at the current moment is calculated; in the correction stage, the predicted value is corrected through the measured value; in combination with a model predictive control algorithm, based on an output result of an extended Kalman filter, rolling optimization is performed on a voltage control quantity at a next moment, and a correction control error is fed back in real time; and inputting the optimized voltage control quantity into a robot motor driving system to realize non-overshoot rapid tracking control of a current loop.

The invention discloses a built-in permanent magnet synchronous motor MTPA control method based on an improved EKF algorithm, and belongs to the field of permanent magnet synchronous motor high-performance control. According to the method, a dynamic forgetting factor multi-information extended Kalman filter algorithm is provided for solving the problems of MTPA trajectory offset and operation efficiency reduction caused by IPMSM key parameter time variation, and the algorithm adaptively adjusts historical data weight through a dynamic forgetting factor mechanism to realize rapid tracking when parameters suddenly change; and a multi-information theory is utilized to fuse historical information, so that noise is effectively suppressed, and the steady-state estimation precision is improved. The algorithm serves as an online identification module to be embedded into an MTPA control system, accurate quadrature-axis inductance and permanent magnet flux linkage can be obtained in real time, the current distribution angle is dynamically corrected, and therefore it is ensured that the motor stably operates along the optimal efficiency track under the full working condition. The method does not need extra signal injection, and has high precision, strong robustness and good engineering practicability.

The invention relates to a low-voltage fast-response digital linear voltage regulator with a self-adaptive adjustment two-dimensional shift register, which comprises a non-overlapping clock ring comparator RACMP, a two-dimensional shift register 2DCSR, a fast tracking mode detector, a successive approximation register SAR, a coarse adjustment PMOS array and a fine adjustment PMOS array, wherein the coarse adjustment PMOS array and the fine adjustment PMOS array are formed by adjusting tubes; the SAR comprises a binary search module; according to the invention, the two-dimensional shift register 2DCSR and the binary search module cooperatively adjust the output voltage VOUT, so that coarse adjustment and fine adjustment double-loop control is realized; a two-dimensional shift register 2DCSR is utilized to realize an adaptive adjustment function, and combinatorial logic and RAM storage are utilized to realize a coarse adjustment step length change function and fine adjustment binary search; the circuit can quickly adjust the output voltage VOUT under low voltage and realize high-precision voltage stabilization.

The invention provides a performance impact factor analysis method and device based on a distributed system, and relates to the technical field of data processing.The method comprises the steps that first monitoring data and second monitoring data of a data stream are collected in real time through a kernel mode probe and a user mode probe deployed on target equipment; on a transmission path of a data stream, when the data stream passes through one transmission node, a tracking identifier uniquely corresponding to the transmission node is injected, and the tracking identifier of each transmission node and the transmission path form a mapping relationship; constructing a causal network model based on the first monitoring data, the second monitoring data, and the mapping relation between the tracking identifier and the transmission path; and determining a target influence factor according to the causal network model and a preset micro-service topological graph. According to the method and the device, the tracking identifier is injected into the data stream, so that the aim of tracking each influence factor in a cross-protocol manner can be fulfilled, and the influence factors which influence the performance of the distributed system can be quickly tracked in a scene of supporting the multi-protocol distributed system.