479results about How to "Improve tracking accuracy" patented technology

The invention discloses a flight control method and system of an unmanned aerial vehicle tracking technology, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the following steps: before an unmanned aerial vehicle takes off, starting an airborne sensor in advance, executing parameter initialization and calibration operation, and installing a magnetic marker on a tracking target; acquiring the body position of the unmanned aerial vehicle in the flight process, and sensing the target position of the tracking target in real time by adopting a multi-sensor data fusion algorithm; obstacles existing in the flight path are detected in real time, a three-dimensional environment model is integrated, and the motion state of a tracking target is captured in combination with a follow-up visual tracking algorithm; target tracking data are stored and fed back in real time, and the battery state and the energy consumption speed of the unmanned aerial vehicle are monitored. By combining the magnetic guidance technology, multi-sensor data fusion and a follow-up visual tracking algorithm, high-precision target tracking can be realized in a dynamic complex environment, meanwhile, obstacles are effectively avoided, and the flight stability and tracking precision of the unmanned aerial vehicle are ensured.

The invention discloses a virtual marshalling multi-train cooperative adaptive sliding mode control method based on an extended state observer, and the method comprises the steps: firstly constructing an urban rail multi-train tracking error dynamic model based on a unit train dynamic equation; secondly, establishing a nonsingular terminal sliding mode surface according to the urban rail multi-train tracking error dynamical model to obtain an equivalent control law, combining the equivalent control law with a switching control law to obtain a nonsingular terminal sliding mode control law, and introducing a gain adaptive law and a saturation function into the nonsingular terminal sliding mode control law to obtain an adaptive nonsingular terminal sliding mode control law; and finally, an extended state observer is adopted to estimate external interference, an observation value of the interference is added to the output of the adaptive nonsingular terminal sliding mode controller to serve as feed-forward compensation, and the adaptive nonsingular terminal sliding mode control method based on the extended state observer is constructed. According to the method, the multi-train cooperative operation tracking control precision and stability can be remarkably improved under the external interference condition.

The invention discloses an aero-engine control system and method based on self-adaptive specified interference cancellation, and belongs to the field of aero-engine control. A disturbance affine form nonlinear mathematical model of an aero-engine is obtained through system identification, a fixed-time disturbance observer is designed to estimate the lumped interference of the system in real time, and the disturbance of the aero-engine is estimated in real time; and a self-adaptive specified interference elimination composite controller is constructed based on a nonlinear backstepping method and a dynamic inverse method, so that accurate control on the rotating speed of the engine is realized. The system adjusts the control quantity in real time based on a backstepping method and a dynamic inverse method, and the controller adopts a non-smooth instruction filter and a self-adaptive dynamic weight distribution mechanism, so that the uncertainty of the system is effectively compensated. The method can effectively cope with uncertainty caused by system parameter perturbation, unmodeled dynamics and external load fluctuation, gives consideration to dynamic and static performance, has high control precision, good anti-interference capability and closed-loop stability, and is suitable for aeroengine rotating speed control under complex working conditions.

The invention discloses a Beidou satellite orbit determination method and system, a medium and equipment, and relates to the technical field of satellite geodetic survey, and the method comprises the steps: obtaining inter-satellite link distance measurement observation value data, and carrying out the preprocessing; according to the preprocessed observation value data, obtaining a clock-correction-free combined observation quantity and a clock-correction-free combined observation quantity at the same moment, and establishing a clock-correction-free combined observation model and a geometric-correction-free combined observation model; after the inter-satellite link observation residual error is fitted, a time domain is converted into a frequency domain through Fourier transform, and a periodic signal of the frequency domain is detected; establishing a link observation model, introducing a star-star pair deviation of an inter-satellite link, and adding a cosine term and a sine term of an orbital period parameter to obtain an improved link observation model; converting the refined link observation equation in the observation time period into a normal equation form, superposing all normal equations, and processing through a least square method to obtain to-be-estimated orbit parameters; and performing orbit fitting on the to-be-estimated orbit parameters to obtain orbit parameters, and further confirming a Beidou satellite orbit determination result.

The invention relates to an anti-interference control method and system for a hypersonic flight vehicle. The method comprises the following steps: constructing a control-oriented attitude system model of the hypersonic aircraft, and constructing a terminal function according to an acceleration convergence parameter, aircraft attitude system state information and error information based on the control-oriented attitude system model of the hypersonic aircraft; designing a dynamic sliding mode surface according to a terminal function and an adaptive law; a finite time controller is constructed by taking the dynamic sliding mode surface as a strategy, so that a tracking error is converged to a design value within a fixed time, and flight control input is obtained; the method comprises the following steps: constructing a fixed time fuzzy interference observer according to a fuzzy logic method and a fixed time control method based on a control-oriented attitude system model of a hypersonic aircraft, and obtaining an interference estimated value; and inputting the value into a finite time controller, and carrying out interference compensation on flight control input. The hypersonic flight vehicle attitude control method is used for hypersonic flight vehicle attitude control, and has the advantages of fast tracking speed, high tracking precision and strong robustness.

The invention discloses a high-speed train automatic driving prediction control method and device, equipment and a medium, and relates to the field of train automatic driving, and the method comprises the steps: carrying out the real-time updating of an edge-side digital twin model and a cloud-side digital twin model based on a distributed updating strategy under end-side cloud cooperation, and obtaining an edge return model and a cloud return model; the end-side digital twinning model is equivalent to the last updated edge backhaul model; and evaluating prediction errors of the end-side digital twin model, the edge-side digital twin model and the cloud-side digital twin model, and when the end-side digital twin model is not optimal, correcting the end-side digital twin model by using the edge-side digital twin model and the cloud-side return model by using a self-correction mechanism. The optimal control instruction sequence of the target high-speed train prediction time domain is determined according to the train prediction speed at the next moment so as to achieve uninterrupted control over the high-speed train without delay, and the tracking performance and the riding comfort of the high-speed train are improved.

The invention discloses a disc type permanent magnet motor control method and system with adaptive dead zone compensation, and the method comprises the steps: constructing a state equation, a state estimation equation and a state-space equation of a permanent magnet synchronous motor through the structure of a Luenberger observer, constructing an observable matrix through an output matrix and a system matrix, and verifying the output of an observable system; establishing a characteristic equation to enable the designed observer to be finally converged, reducing an error between an estimated value of the disturbance observer and an actual value of the system, and realizing digital control of an actual servo platform through a discrete observable matrix; a phase-A bridge arm of an inverter is analyzed, three-phase current is subjected to Fourier decomposition, and stator harmonic components are analyzed to obtain three-phase harmonic current of the motor; an adaptive filter is designed based on an NLMS algorithm, and an online dead-zone compensation strategy is improved for a dead-zone effect. According to the method, by introducing the Luenberger disturbance observer, real-time measurement and adjustment of a nonlinear system can be realized, so that the performance index of the system is effectively improved.

The invention discloses a cross-modal target tracking method based on a fully convolutional twin network. The method comprises the following steps: inputting a visible light image and a thermal infrared image into a cross-modal target tracking network model to obtain a tracking structure; the cross-modal target tracking network model comprises a feature extraction backbone network, a self-adaptive complementary fusion module and a target classification regression network, and the feature extraction backbone network comprises a visible light backbone network and a thermal infrared backbone network which are the same in structure; the visible light backbone network and the thermal infrared backbone network respectively extract features of a template and a search area through convolution and perform adaptive convolution to extract time sequence information; and the self-adaptive complementary fusion module performs channel attention enhancement and space attention enhancement on the visible light features and the thermal infrared features extracted by the feature extraction backbone network and fuses the visible light features and the thermal infrared features. The invention also discloses a cross-modal target tracking system based on the fully convolutional twin network for realizing the method. The method can improve the stability and robustness of tracking in different environments.

The invention relates to a four-rotor unmanned aerial vehicle anti-interference trajectory tracking control method based on an observer and a tracking differentiator, and belongs to the field of aerial robot control. According to the method, various aerodynamic disturbances in the environment are estimated in real time by using the nonlinear disturbance observer; then, external interference estimated in real time is used as an interference compensation item of a sliding mode controller to obtain control laws of a four-rotor position subsystem and a four-rotor attitude subsystem, and meanwhile, an improved tracking differentiator is used for providing a smoother expected attitude signal; and finally, proving accurate estimation of the nonlinear disturbance observer on external disturbance through a global consistent final bounded stability theory, and proving the stability of the four-rotor control system through a Lyapunov method. A novel high-frequency switching function established in a control law is combined with an improved tracking differentiator, so that the buffeting problem of sliding mode control is effectively suppressed, and a nonlinear interference observer improves the anti-interference capability of four rotors; the control input buffeting is reduced while the robustness of the four rotors is improved.

The invention discloses a photoelectric turntable servo tracking control method, a storage medium and a system, and relates to the technical field of servo control, and the method comprises the steps: receiving target deviation value information; caching the actual position information for a corresponding time length based on the target calculation and the transmission delay time length, and using the actual position before transmission and calculation when processing the target deviation information, so that the target deviation is consistent with the actual position information in time, and the target position is obtained; according to the target deviation and the actual position information, a predicted speed is calculated and output through feedforward control, the obtained target position is input into a position ring to obtain speed output, and the speed output and the predicted speed input are combined to a speed ring. According to the established data caching and feed-forward compensation model, the servo system compensates system predictive interference in advance, carrier motion and other interference factor influences are effectively restrained, response delay is reduced, the system tracking precision is improved, the dynamic response speed is increased, and real-time smooth tracking control is achieved.

The invention discloses an anti-counterfeiting verification tracking method and system based on an RFID technology, and relates to the technical field of anti-counterfeiting tracking. All unexpected nodes in a second sequence are identified, historical data of the unexpected nodes are analyzed, then a confidence score of each unexpected node is obtained, an influence weight of each unexpected node is obtained according to a correlation index, and the confidence score of each unexpected node is obtained; calculating confidence scores and influence weights of all unexpected nodes through a fusion algorithm, generating a verification coefficient for a product, generating a corresponding management strategy for the product according to a comparison result of the verification coefficient and a verification threshold value, and regularly obtaining an unexpected node identification number of all products in the same series. And analyzing whether the same series of products need to be managed in advance. The tracking system recognizes all unexpected nodes through sequence comparison and performs historical data analysis on the unexpected nodes, so that path abnormity can be effectively found, the recognition capability of the system on abnormal circulation is enhanced, and the tracking precision is improved.

The invention discloses a stability control system and method considering time varying and time lag of a steering mechanism, and the system comprises a rotation angle generation module, a reference model module, an error fusion module, a stability control module, and an EKF side slip angle observation module. Wherein the steering angle generation module adopts a model predictive control (MPC) algorithm to track an expected trajectory and generate a front wheel steering angle, and the stability control module adopts a Smith pre-estimation compensation method to design active front wheel steering (Smith-AFS) and direct yawing moment control (DYC) so as to realize the stability control of the intelligent vehicle under the condition that an execution mechanism has time-varying and time-lag. According to the stability control system and method considering the time-varying time-lag of the steering mechanism, the tracking precision of the side slip angle and the yaw velocity is greatly improved, and the time-lag interference problem of a stability controller can be solved.

The invention relates to a staged-based adaptive multi-target tracking method, and provides a staged association thought and an adaptive weight strategy, when a to-be-tracked target in a video sequence has complex conditions such as long-time shielding, deformation and illumination change, target trajectories are classified according to the target shielding degree, and the target tracking accuracy is improved. A reasonable track detection frame association sequence is set in combination with the actual situation, and meanwhile, different association strategies are designed for each association, so that the tracking accuracy is further improved; a confidence coefficient difference value and speed direction information are used as a weak clue to assist a strong clue in matching between a target track and a detection frame, so that the correlation success rate is further improved; and the appearance feature updating module designs different appearance feature updating strategies for the targets with different shielding degrees so as to improve the discrimination of the appearance features. The tracking method provided by the invention can still keep track continuity and tracking stability in a complex scene.

The invention discloses an inverter circuit, a maximum power tracking method thereof and energy storage inverter equipment, the inverter circuit comprises a full-bridge circuit, a transformer and a half-bridge circuit, the full-bridge circuit is connected to the half-bridge circuit through the transformer, the full-bridge circuit is connected with a photovoltaic module, and the half-bridge circuit is connected with an alternating current side; the maximum power tracking method comprises the following steps: acquiring the input power of the photovoltaic module in the current period and the input power of the photovoltaic module in the previous period, and the reference output voltage of the inverter in the first period; determining a voltage adjustment step length according to the power deviation and the voltage deviation, the power deviation being based on the input power of the current period and the previous period, and the voltage deviation being based on the input voltage of the photovoltaic module of the current period and the previous period; obtaining the reference output voltage of the current period according to the voltage adjustment step length and the reference output voltage of the previous period; and generating a driving signal according to the reference output voltage of the current period so as to control the inverter circuit. According to the invention, the maximum power point of the photovoltaic module can be tracked by the inverter circuit.

The invention provides an anti-interference tracking method and system based on target infrared imaging characteristics. The method comprises the following steps: acquiring a continuous infrared image sequence of a target object at different time points; determining a potential motion track of the target object in the infrared image sequence by using space-time correlation analysis; a dynamic weight map is generated based on the potential motion trail, and the dynamic weight map adaptively adjusts the importance of each pixel according to the change of background noise and target features; combining the dynamic weight map with the infrared image sequence to reinforce the target area and suppress the non-target area to obtain a reinforced infrared image sequence; and a multi-hypothesis tracking strategy is adopted, real-time positioning is performed on the target object in the enhanced infrared image sequence, and continuous tracking of the target object is kept by updating the dynamic weight map. According to the technical scheme provided by the invention, the tracking precision can be improved.

The invention discloses a path obstacle avoidance method based on a fuzzy matching camera video stream and probability cloud computing, and particularly relates to the technical field of path obstacle avoidance, and the method comprises the following steps: step 1, initial path planning, step 2, initial path obstacle probability prediction, step 3, video stream analysis to identify obstacles, and step 4, implementation of path obstacle avoidance response measures. According to the obstacle information on the historical initialized path, the risk area on the initialized path is divided, when the transport robot arrives at the risk area, finer image recognition is adopted, whether obstacles exist or not and the specific type are judged, path obstacle avoidance can be conveniently and timely carried out, the fuzzy recognition mode is adopted, and the obstacle avoidance efficiency is improved. Obstacle recognition, tracking and classification precision in a complex scene can be remarkably improved, the intelligence and high efficiency of a factory transportation robot are met, and the production efficiency of a factory is improved.

The invention relates to the technical field of holders, and discloses a self-stabilization holder searchlight tracking system, which comprises a holder autonomous stabilization subsystem, a tracking control subsystem and a searchlight subsystem, and is characterized in that the holder autonomous stabilization subsystem comprises a servo motor, a servo motor connecting arm, a servo controller and an attitude position sensor; one end of the servo motor connecting arm is fixedly connected with the servo motor, the other end of the servo motor connecting arm is fixedly provided with a fixing structure, and the top of the fixing structure is provided with a data transmission interface. According to the self-stabilizing pan-tilt searchlight tracking system, stable operation of a searchlight at different angles and in complex environments is achieved through the pan-tilt autonomous stabilizing system, the system can automatically adjust the direction and angle of the searchlight according to the position of a target, it is ensured that continuous tracking is conducted in the target moving process, and efficient illumination is provided; the design improves the precision of target tracking and the stability of illumination, and is suitable for various application scenes such as night monitoring, security patrol, search and rescue and the like.

The invention discloses a terminal sliding mode control method based on an arc tangent function and application of the terminal sliding mode control method. The traditional terminal sliding mode control is fast in convergence, but has a singular problem. The traditional nonsingular terminal sliding mode control solves the singular problem at the cost of sacrificing the convergence time. Therefore, the arc tangent function and the power function are introduced on the basis of the terminal sliding mode, the novel non-singular fast terminal sliding mode control method is constructed, and compared with a traditional terminal sliding mode control method, the method is continuous at a balance point, the singular problem is solved, and the method has the advantages that the method is simple and convenient to operate. Compared with the traditional linear sliding mode control, integral sliding mode control and nonsingular terminal sliding mode control, the method ensures that the speed regulation system has higher convergence speed, higher tracking precision and stronger anti-interference performance.

The invention discloses an AGV trajectory tracking method based on vision, and relates to the technical field of heavy-load AGVs, comprising the following steps: S1, the AGV is equipped with a vision acquisition and image processing unit; s2, obtaining a tracking algorithm based on a geometric method; s3, adjusting the visual distance and the planned path to obtain the position coordinates of a front view point; s4, outputting an AGV steering instruction by using the method; s5, a set speed is added, so that the AGV vehicle can realize a trajectory tracking effect; and S6, displaying the effect picture through communication. According to the AGV trajectory tracking method based on vision, the image provided by vision is analyzed and processed to obtain the next motion point, so that the AGV trajectory tracking precision is improved, manual operation of male and female head rotation butt joint is not needed, time and labor are saved, and harm of chemical engineering places to human bodies is reduced; the method can achieve the effects that the path is planned by using environmental information, and the system is controlled by using PID control and an advanced algorithm.

The invention discloses a sail-type ship wind power plant autonomous cruise control method based on performance optimization, and the method comprises the steps: obtaining a position displacement error and a heading displacement error of a drum sailboat through introducing a displacement function, and achieving the autonomous cruise control of the drum sailboat based on an error conversion technology; obtaining a position change error of the drum sailboat considering the preset performance of the drum sailboat and a heading change error of the drum sailboat; and a main engine rotating speed controller and a rudder angle controller of the drum sailboat are designed in combination with a dynamic surface technology, the main engine rotating speed and the rudder angle of the drum sailboat are obtained, and autonomous cruise control over the sail type ship wind power plant is achieved. The method can meet the high tracking precision requirement of a narrow channel or a multi-obstacle water area, greatly improves the ship tracking precision, and meets the high tracking precision requirement of a complex water area. Meanwhile, the autonomous cruise task of the ship under the severe sea condition can be effectively guaranteed, a powerful guarantee is provided for guaranteeing the transient performance and the steady-state performance of the ship, and a key technical support is provided for safe navigation of the drum sailboat in a complex water area.

The invention discloses a target tracking method and system based on visual identification and an underwater robot, and relates to the technical field of underwater robots. According to the invention, automatic tracking and monitoring of an underwater target are realized by using a visual identification technology, operations such as an image identification technology of YOLOv5, a motion tracking technology of an optical flow and a Kalman filter, a target re-identification algorithm of deep learning, image enhancement and the like are specifically combined, and the intelligent level and the working efficiency of underwater operation are comprehensively improved. According to the method, the diver can be efficiently tracked in a complex underwater environment, and high recognition and tracking precision is ensured under the condition that the diver disappears or the motion trail is complex.

The invention relates to the technical field of sensing data analysis, in particular to a situation sensing method and system based on an intelligent fan. The method comprises the following steps: obtaining human shape position change data of an intelligent fan user and human shape motion posture change data of the intelligent fan user, carrying out human shape motion interframe change identification analysis and Kalman filtering human shape tracking, and carrying out human shape motion range analysis at the same time; the dynamic change range of the human shape motion of the intelligent fan user is obtained; the intelligent sensing range of the intelligent fan is obtained, situation awareness cross judgment is carried out on the human shape motion dynamic change range of an intelligent fan user, and when it is determined that the intelligent fan user is in a close or away sensing state, a wind speed acceleration or deceleration control instruction is generated through response of the intelligent fan and acts on a built-in control system of the intelligent fan. The corresponding intelligent fan air speed automatic acceleration or deceleration work is executed; the method can focus on recognition and tracking of the whole human shape, and aims at optimizing the sensing state of the intelligent fan.

The invention provides an omni-directional all-drive robot trajectory tracking method based on constraint simplification, and belongs to the technical field of ground wheel type mobile robot trajectory tracking. According to the method, a robot kinematic model is established on the basis of rigid body dynamics, the transformation relation between each set of wheel speed vectors and robot speed information in a world coordinate system is represented, and multiple sets of hard constraint problems caused by motor physical characteristics are converted into soft constraint or unconstrained problems in a target function. And the program running speed and the solving success rate are improved. In addition, tracking errors caused by mechanical friction and noise interference are compensated for on the control outermost ring based on high-frequency speedometer information, and it is ensured that the robot accurately executes according to a control instruction. Through experimental verification, the solving speed of each frame of the method is within 50ms, and the tracking error evaluation of a reference trajectory is controlled within 5cm.

The invention discloses a PID (Proportion Integration Differentiation)-based hydraulic jumbolter rotating speed iterative learning control method, which belongs to the technical field of mining jumbolter rotating system control, and comprises the following steps: S1, considering internal and external disturbances of a system, and establishing a dynamical model of a jumbolter system; s2, performing state conversion according to the established mathematical model to obtain a state space expression of the system; s3, the optimal rotating speed of the jumbolter is estimated according to the hardness coefficient of the rock stratum characteristics; and S4, designing a PID iterative learning control law. According to the method, a system mechanism model does not need to be accurately known, the rotating speed can be self-adjusted according to the change of the rock hardness coefficient in the drilling process, and the controller is continuously corrected through feedback tracking errors by utilizing iterative learning, so that the purpose of rapid tracking is achieved. Compared with the traditional PID, the controller has the advantages that the response speed, the adjustment time, the tracking precision and other performances are remarkably improved, the excessive phenomenon is almost avoided, and the robustness is high.

The invention discloses a high-frequency ground wave radar formation target tracking method and system, and particularly relates to the technical field of target tracking. Comprising the following steps: constructing a position feature vector and an appearance feature vector of a formation target based on high-frequency ground wave radar echoes; constructing nodes by using the position feature vectors and the appearance feature vectors of the formation targets; screening adjacent nodes of the known node Node based on the position feature vector, and calculating a likelihood function; constructing a prototype network model based on the formation target appearance feature vector, and calculating the Euclidean distance between the appearance feature vector of a known node Node and the appearance feature vector of an adjacent node Adjacent; on the basis of a likelihood function Lsiran and an Euclidean distance Euddis, the correlation similarity between a known node Node and an adjacent node AdJacent is calculated, so that a connection edge is constructed; and training based on a graph neural network loss function to realize formation target matching tracking. By adopting the technical scheme of the invention, the problem that the formation target cannot be tracked in the prior art is solved, and accurate tracking of special targets such as formation is realized.

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 non-linear scene multi-target tracking method and system and a storage medium, and the method comprises the steps: constructing a non-linear motion model and a measurement model, and specifically, representing a non-linear state process and a measurement process through a non-linear model; according to multi-target tracking in a two-dimensional plane, determining a motion equation of each target, setting the motion equation as a collaborative turning model, and determining a motion equation of the target; constructing a system state transition matrix, a process noise distribution matrix and a measurement equation; according to the nonlinear motion model and the measurement model, extraction of multi-target state estimation is carried out through an FAUKF-PHD filter, a state vector of each target is obtained, and tracking of each target is completed; and verifying the tracking result of each target based on the multiple pieces of preset scene information. The method is high in tracking precision and low in cost, can improve the effectiveness of the method, and can be widely applied to the technical field of computers.

The invention discloses a photovoltaic power generation system maximum power point tracking control method considering time delay, and belongs to the technical field of photovoltaic cell maximum power point tracking control. The method solves the problems that a traditional maximum power point tracking control method is low in tracking precision and low in tracking speed and cannot deal with complex working environments, battery array parameter change and time delay in a system. An averaging method based on time delay is used for averaging a system to obtain an equivalent system, a constant variation formula method based on an ordinary differential equation is used for carrying out quantitative stability analysis on the equivalent system, a quantitative relation between system stability and controller parameters is established, a final controller form is obtained, and the stability of the system is improved. The MPPT tracking control of the photovoltaic cell is realized in a real sense, the tracking precision and the tracking speed are improved, and the power loss of the photovoltaic cell is effectively reduced. The method can be applied to maximum power point tracking control of the photovoltaic power generation system with time delay.

The invention relates to the technical field of power transmission line operation and maintenance, and discloses an ultra-high voltage line lead inspection method based on unmanned aerial vehicle line simulation inspection, which comprises the following steps of: taking a strand of ground lead between a starting tower and a target tower as an inspection unit, and performing line simulation inspection on the basis of each frame of image in a video stream acquired by an unmanned aerial vehicle in real time; distinguishing each power line in each strand of ground wire in the current frame image, combining every two detection frames corresponding to the two adjacent power lines into a candidate frame according to the positions of the plurality of power lines in the current frame image from top to bottom, and taking the candidate frame in the middle as a target frame; at the moment of each frame of image in a video stream acquired by the unmanned aerial vehicle in real time, taking the target frame of the current frame of image as a reference, calculating the height difference between the center of the target frame and the center of the current frame of image in real time, adjusting the working angle of the unmanned aerial vehicle, and keeping the height of the center of the target frame of the current frame of image consistent with the height of the center of the current frame of image; and inspecting the ground wire corresponding to the current inspection unit.

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.