47 results about "Position error" patented technology

The invention discloses an air-drop and air-delivery large unmanned aerial vehicle ultra-low-altitude flight control system and method, and belongs to the field of flight control systems, and the system comprises a flight control module, a drop control module, an environment sensing module, a gravity center balance adjustment module and a data storage and interaction module. The flight control module is used for controlling the unmanned aerial vehicle to fly at an ultra-low altitude and ensuring that the flight attitude is stable, so that the position error is less than or equal to 10m, the height error is less than or equal to 2m and the flight path deviation is less than or equal to 10m when the unmanned aerial vehicle flies at the ultra-low altitude; the delivery control module is used for supporting a single delivery mode and a rapid continuous delivery mode, the maximum delivery of 1.2 tons of goods can be achieved, at most four pieces of goods can be delivered in a single flight, the delivery control module is compatible with parachute air delivery and non-parachute air delivery, and the delivery precision of the parachute air delivery at the high altitude of 300 meters is smaller than 100 meters. According to the invention, the unmanned aerial vehicle delivery precision can be improved, the stability is high, and material waste or incapability of accurately delivering to a target area is avoided.

A position error monitoring method and control system of a rotating mechanism, in the position error monitoring method of the rotating mechanism, angular position data of an encoder of a first motor and an encoder of a second motor are acquired as first position data during a process; then, during a non-process, the relative speed between the first motor and the second motor is adjusted while the rotating mechanism remains in a rotating state, so that the relative position of the first rotating part and the second rotating part is dynamically adjusted to a preset calibration phase, and second position data are acquired during operation at the calibration phase; the transition from the process phase to the calibration phase can be completed without stopping the rotating mechanism, time loss and mechanical impact caused by frequent start and stop are avoided, and the operation efficiency and productivity of the rotating mechanism are improved; in addition, whether there is a transmission error is determined by calculating the deviation value between the second position data and the first position data, which helps to find faults in time and improve the consistency and yield of the process.

The invention discloses a position error monitoring method and a control system of a rotating mechanism, and the method comprises the steps: obtaining the angular position data of an encoder of a first motor and an encoder of a second motor as first position data in a process processing period; then, in the non-process treatment period, the relative speed between the first motor and the second motor is adjusted in the rotating state of the rotating mechanism, the relative position of the first rotating component and the relative position of the second rotating component are dynamically adjusted to the preset calibration phase, and second position data are obtained in the calibration phase operation period; transition from a process phase to a calibration phase can be completed without stopping the rotating mechanism, so that time loss and mechanical impact caused by frequent start and stop are avoided, and the operation efficiency and the productivity of the rotating mechanism are improved; in addition, whether transmission errors exist or not is judged by calculating the deviation value between the second position data and the first position data, faults can be found in time, and the consistency and yield of process processing are improved.

Method for determining vehicle odometry, comprising: Receiving initial sensor data by a controller (34) of a vehicle (10); Receiving second sensor data by the controller (34) of the vehicle (10); Determining an initial longitudinal position, an initial lateral position and an initial heading of the vehicle (10) by the controller (34) of the vehicle (10) using the first sensor data, wherein the first sensor data are generated by an inertial measurement unit (IMU) of the vehicle (10), a wheel speed sensor (WSS) and a steering angle sensor (SAS) of the vehicle (10); Determining a longitudinal position error, a lateral position error and a course error of the vehicle (10) by the controller (34) of the vehicle (10) using the second sensor data, wherein the second sensor data are generated by a radar device of the vehicle (10); Determining a longitudinal speed of the vehicle (10) using the first sensor data and the second sensor data; Determining a lateral speed of the vehicle (10) using the first sensor data and the second sensor data; Determining a yaw rate of the vehicle (10) using the first sensor data and the second sensor data; Correcting the initial longitudinal position, initial lateral position, and initial heading of the vehicle (10) using the longitudinal position error, lateral position error, and heading error, respectively, thereby generating a corrected longitudinal position, a corrected lateral position, and a corrected heading of the vehicle (10), wherein the corrected longitudinal position, the corrected lateral position, and the corrected heading of the vehicle (10) are determined using an adaptive filter, wherein the corrected longitudinal position is based on the enhancement of a longitudinal position, the corrected lateral position is based on the enhancement of a lateral position, and the corrected heading is based on the enhancement of a heading. where the adaptive filter is implemented using a multitude of equations, and the multitude of equations includes: Δxk + 1 = Δxk + gk, xex, k Δ yk + 1 = Δ yk + gk , yey , k Δ ψ k + 1 = Δ ψ k + gk , ψ e ψ , k where: k is a time step; Δx k+1 is a filtered term for the initial longitudinal position of the vehicle (10); Δy k+1 is a filtered term for the initial lateral position of the vehicle (10); Δψ k+1 is a filtered term for the initial course of the vehicle (10); Δx k is a change in the longitudinal position of the vehicle (10) at time k; Δy k is a change in the lateral position of the vehicle (10) at time k; Δψ k is a change in the course of the vehicle (10) at time k; G k,x is the strengthening of the longitudinal position at time k; G k,y is the strengthening of the transverse position at time k; G k,ψ is the strengthening of the price at time k; ex,k is the error of the longitudinal position at time k; e y,k is the error of the transverse position at time k; and e ψ,k is the error of the course at time k; where the longitudinal position error, the transverse position error, and the course error are calculated using the following equations: ex = vs ( 1 ) . dt − Δ x ˜ ey = vs ( 2 ) . dt − Δ y ˜ e ψ = atan2 (vs (2) vs (1)) − Δ ψ ˜ where: v s is the scene speed of the vehicle as detected by the radar (10); e x is the error term for the x-position (i.e., the longitudinal position) of the vehicle (10); e y is the error term for the y-position (i.e., for the lateral position) of the vehicle (10); e ψ is the error term for the course of the vehicle (10); Δ x ˜ Delta x-position with uncertainty; Δ y ˜ Delta y-position with uncertainty; Δ ψ ˜ Delta price with uncertainty; and t is time; and Steering the vehicle (10) using the corrected longitudinal position, the corrected lateral position and the corrected course.

The invention discloses an aircraft control method and device, electronic equipment, an aircraft and a storage medium. The method comprises the following steps: acquiring a target position corresponding to the multi-rotor aircraft, wherein rotors of the multi-rotor aircraft are provided with mounting angles; determining a position error corresponding to the current moment based on the target position of the multi-rotor aircraft and an actually measured position corresponding to the current moment fed back by the multi-rotor aircraft; determining a target acceleration corresponding to the current moment based on the position error corresponding to the current moment and an actually measured speed corresponding to the current moment fed back by the multi-rotor aircraft; and determining a target rotating speed corresponding to the current moment based on the target acceleration corresponding to the current moment, and controlling the multi-rotor aircraft to work based on the target rotating speed corresponding to the current moment. The method can improve the response speed and control bandwidth of the aircraft controlled in the horizontal direction.

The application provides an aerial docking method and device based on a contact force-position neural network model. The method provided by the application comprises the following steps: building a ground data acquisition device, collecting training data of contact force and corresponding position parameters in three dimensions of horizontal direction, vertical direction and relative angle through the ground data acquisition device; constructing a contact force-position neural network model, training the contact force-position neural network model by using the training data; acquiring relative position and attitude information between a work unmanned aerial vehicle and a target, and predicting contact force based on the contact force-position neural network model; combining the predicted contact force, position error of the work unmanned aerial vehicle and the target, and preset expected docking force to generate a preliminary reference trajectory; introducing a control allocation method to optimize and adjust the preliminary reference trajectory, and performing aerial docking between the work unmanned aerial vehicle and the target based on the optimized trajectory.

The embodiment of the invention provides a control method of an airship hanging load, electronic equipment, a storage medium and a program product, and relates to the technical field of nonlinear control, the control method of the airship hanging load provided by the embodiment of the invention designs a component of a virtual control force along a cable direction in load trajectory tracking control and position error control, so that the control precision of the airship hanging load is improved; and driving the load to approach the expected trajectory. A cable direction error is introduced in cable swing angle suppression, a component perpendicular to a cable is designed, swing is suppressed, stability is guaranteed, in airship driving control implementation, according to the load control requirement, analog control force needed by the airship is solved, dynamic balance is achieved by adjusting a propelling system of the airship, the dynamic coupling effect of an airship speed ring is considered, and the airship swing angle is suppressed. The self-adaptive control of the attitude is realized, the problems of large deviation of load tracking expected trajectory, insufficient cable swing suppression and unstable airship attitude are solved, and the hoisting control precision of the airship hanging load is improved.

The present application relates to a kind of system level calibration method for correcting the zero offset of acceleration channel of inertial measuring device, belongs to the field of inertial measurement.The zero position error of acceleration channel is compensated, the method does not need to disassemble inertial measuring device, by the vertical direction of three axes of aircraft respectively, the zero position error of acceleration channel of inertial measuring device can be calculated.The present application proposes the system level calibration method for quickly correcting the zero offset of acceleration channel of inertial measuring device, by simple calibration path setting, the zero offset error of acceleration channel can be effectively calculated.When the change of accelerometer itself zero offset error occurs, it is no longer necessary to disassemble inertial measuring device from aircraft and re-performs discrete calibration, and the influence of installation error caused by repeated installation of inertial measuring device is avoided.

This invention provides a position control method and apparatus based on attitude control error feedforward compensation, relating to the field of rendezvous and docking technology. The method includes: calculating the orbital control error based on the attitude control error; determining the position error at the end of the long-range guidance segment under the influence of the orbital control error; calculating a corresponding compensation amount based on the position error at the end of the long-range guidance segment; and correcting the nominal position value based on the compensation amount, so as to use the corrected nominal position value for position control. This solution can achieve high-precision position control under large-pulse orbital control.

The invention provides a flight operation robot contact force tracking control method based on variable stiffness admittance. The method comprises the following steps: S1, establishing a dynamic model of a flight operation robot system; s2, designing a self-adaptive variable stiffness admittance model, generating an expected reference trajectory by dynamically adjusting a stiffness coefficient, and compensating the influence of unknown environmental parameters; s3, designing a nonlinear disturbance observer to estimate system disturbance, and providing disturbance compensation for the pose controller; s4, a pose controller is designed based on the obstacle Lyapunov function, reference trajectory tracking is achieved, and the position error is strictly restrained to be within a safe range; s5, the rotating speed of each rotor wing of the flying operation robot is calculated through control input; the flying operation robot is controlled to realize stable contact force tracking; according to the method, uncertainty and contact disturbance in an unknown dynamic environment can be effectively dealt with, and the contact force tracking precision and the operation safety of the flying operation robot are improved.

The application discloses a double-base radar space synchronization method based on clutter locking, which comprises the following steps: firstly, a double-base radar space synchronization model is established, model parameter initialization is completed, uniform sea clutter surface target echo is obtained, two-dimensional scanning is performed on the sea clutter area, echo filtering and uniformization processing are performed, the azimuth and pitch angle of the beam alignment moment are estimated, the irradiation target area is changed, multiple sets of alignment moment angles are obtained, a double-base relative position positioning equation is established, the position error of the transmitting station and the receiving station is introduced, the positioning equation is optimized and solved, the relative position of the double-base platform is obtained, the double-base beam angle is recalculated, and the double-base radar space synchronization is realized. Compared with the existing space synchronization method, the method does not depend on the precision of the aircraft platform inertial navigation system, effectively solves the problem that the double-base beam is difficult to realize space synchronization in the actual flight process in the actual working environment, and cannot use navigation information, and the inertial navigation system has a large cumulative error in the long-time flight process.

The invention relates to a method for calculating a north gradient of a vertical component of sea area disturbing gravity, and provides a method for calculating the north gradient of the vertical component of the sea area disturbing gravity aiming at the disturbing gravity vertical component auxiliary navigation requirement of an inertial navigation system under the constraint of a position error of a sea area moving carrier. And constructing a sea area disturbing gravity vertical component north gradient calculation model based on a completely normalized global gravitational potential coefficient by utilizing a physical geodetic boundary value theory, and realizing sea area disturbing gravity vertical component north gradient calculation. The invention aims to improve the disturbance gravity vertical component aided navigation capability of the inertial navigation system under the constraint of the position error of the motion carrier and improve the navigation precision of the inertial navigation system.

The application relates to a method for constructing an inertial navigation system parameter error model based on gravity disturbance. The method comprises the following steps: constructing an accelerometer error model and a gyro observation error model by using random constant zero bias of an accelerometer and random constant drift of a gyro and zero mean random white noise; decomposing measured gravity into gravity disturbance and gravity disturbance measurement error, and constructing velocity error by using the accelerometer error model, the gravity disturbance and the gravity disturbance measurement error; expanding the velocity error to obtain eastward velocity error and northward velocity error; equivalently setting the carrier height of the inertial navigation system to zero, and calculating position error by using the eastward velocity error and the northward velocity error; calculating attitude error by using the gyro observation error model and misalignment angle; and constructing a navigation system parameter error model according to the velocity error, the position error and the attitude error. The method can improve error compensation precision in the navigation process.

The invention relates to a method for calculating east gradient of a plumb line deviation prime component in a sea area, and provides a method for calculating east gradient of a plumb line deviation prime component in a sea area aiming at the plumb line deviation prime component compensation requirement of an inertial navigation system under the constraint of a position error of a motion carrier in the sea area. And based on the completely normalized global gravitational potential coefficient, constructing a sea area plumb line deviation prime component east gradient calculation model, and realizing sea area plumb line deviation prime component east gradient calculation. The invention aims at improving the vertical line deviation prime component compensation capability of the inertial navigation system under the constraint of the position error of the motion carrier and improving the navigation precision of the inertial navigation system.

The application discloses a hovercraft filtering backstepping trajectory tracking control method based on RLESO, and first establishes a three-degree-of-freedom mathematical model of hovercraft movement, compares actual trajectory information of the hovercraft with reference trajectory information to obtain a position error dynamics model of the hovercraft; designs RLESO estimation and compensation of unknown environmental disturbance of the hovercraft based on state information of the mathematical model of the hovercraft; combines the position error dynamics model to construct a time-varying BLF with a position error constraint function; then designs a position error constraint-based hovercraft command filter backstepping controller according to the BLF, backstepping technology and a second-order command filter, and completes a trajectory tracking control target of the hovercraft. The hovercraft filtering backstepping trajectory tracking control method based on RLESO can improve safety performance and controllability of the hovercraft, can make the hovercraft obtain better performance under the influence of external marine environment, and can improve tracking precision of the hovercraft.

The present disclosure provides a low-cost IMU zero bias suppression method and system based on rotation modulation, which combines zero velocity update (ZUPT) with IMU self-rotation, and the IMU rotates in both zero velocity interval and non-zero velocity interval. In order to solve the problem that the introduction of active rotation of the IMU in the zero velocity interval makes the z-axis gyroscope zero bias observability low during the zero velocity correction, resulting in high-order divergence of the heading angle cumulative drift and position error, the present application constructs a corresponding speed observation model, successfully modulates the z-axis gyroscope zero bias during ZUPT in the traditional PINS into a periodic signal that is easy to estimate by the Kalman filter, and fundamentally solves the problem of system heading drift. At the same time, by establishing a special rotating stationary phase detector to replace the failed traditional ZUPT, the reliable triggering of the filter update is ensured. The present application improves the long-time positioning accuracy and reliability of the system.

The invention belongs to the technical field of equipment detection, and particularly discloses an inertial navigation device performance test method and system and a program product, and the method comprises the steps: collecting a navigation standard data set of a carrier and an inertial navigation test data set of an inertial navigation device under a set inertial navigation test condition, and then determining a speed difference value and a position difference value of each sampling time point; calculating multi-dimensional test evaluation parameters in the aspects of speed difference and position difference, finally judging a speed error parameter and a position error parameter of the inertial navigation device under a set inertial navigation test condition by utilizing the multi-dimensional test evaluation parameters in the aspects of speed difference and position difference, and summarizing and outputting the speed error parameter and the position error parameter. According to the method, the speed error and the position error of the inertial navigation device during working can be evaluated more efficiently and comprehensively, the reliability and the accuracy of the performance test result of the inertial navigation device are ensured, and the performance test efficiency and the performance test quality of the inertial navigation device are improved.

The application discloses an inertial-based integrated navigation system error state model correction and optimization method and system, and belongs to the field of integrated navigation control. In a local integrated navigation coordinate system, the influence of misalignment angles and position error angles on the mismatch problem of a calculated navigation coordinate system and a real navigation coordinate system is comprehensively considered, a nonlinear velocity error state corrected by misalignment angles and position error angles is redefined, and a new inertial-based integrated navigation system error state model is derived and established. Compared with the ST-EKF, the application not only considers the influence of linearization errors caused by misalignment angles, but also adds a correction term of the position error angles, further perfects the inertial-based integrated navigation system error state model optimization theory, effectively improves the performance and environmental applicability of state estimation of the inertial-based integrated navigation system, and the superiority is more significant especially in the case that the initial state error is large.

The invention discloses a synchronous event trigger path tracking control method considering an actuator fault, and the method comprises the steps: building a fault-tolerant virtual controller through a position coordinate and a heading angle of a dynamic virtual ship, obtaining a heading angle error and a position error of an under-actuated water surface ship, introducing an acceleration function, and carrying out the tracking of a synchronous event trigger path. Obtaining a new error variable after acceleration function transformation, further obtaining measurement errors of a propeller channel and a steering engine channel, and establishing a synchronization event triggering mechanism; according to a fault model of an actuator and a non-linear mathematical model of an under-actuated water surface ship based on synchronous event triggering fault tolerance, acquiring instruction signals calculated by a controller for a propeller and a steering engine at an event triggering moment; and obtaining a final controller of the propeller and a final controller of the steering engine on the basis of a synchronous event triggering mechanism according to the new error variable subjected to acceleration function transformation and instruction signals calculated by the controller for the propeller and the steering engine at the event triggering moment.

The application belongs to the technical field of motor control, and particularly relates to a position determination method and device for an aviation permanent magnet synchronous motor at low speed. The method comprises the following steps: S1, calculating a partial derivative of an electromagnetic torque to a current vector angle at an MTPA operating point, and determining an MTPA operating point at which the partial derivative is zero; S2, determining an injection angle for high-frequency square-wave voltage injection according to a current vector angle corresponding to the MTPA operating point; S3, obtaining a high-frequency response current variation of the permanent magnet synchronous motor after high-frequency square-wave voltage is injected according to the injection angle; S4, calculating a motor position error based on the high-frequency response current variation and the injection angle; and S5, calculating the motor position error through a phase-locked loop to obtain a real-time motor position. The application improves the position identification accuracy of the aviation permanent magnet synchronous motor under complex working conditions, thereby improving the control performance of the aviation permanent magnet synchronous motor.

The invention relates to a sea area vertical line deviation meridian component vertical gradient calculation method, and provides a sea area vertical line deviation meridian component vertical gradient calculation method aiming at inertial navigation system vertical line deviation meridian component compensation requirements under sea area motion carrier position error constraint. And based on the completely normalized global gravitational potential coefficient, constructing a sea area plumb line deviation meridian component vertical gradient calculation model, and realizing sea area plumb line deviation meridian component vertical gradient calculation. The invention aims to improve the meridian component compensation capability of the vertical line deviation of the inertial navigation system under the constraint of the position error of the motion carrier and improve the navigation precision of the inertial navigation system.

The application provides a multi-degree-of-freedom AGV trolley high-precision positioning control system and method, relates to the technical field of positioning control, generates a moving guide line of the trolley in environmental map information; determines the speed fluctuation scale of the trolley in each direction of the free moving path, tracks and matches all the speed fluctuation scales and the positioning estimation value in the local moving path to obtain the displacement tracking point of the trolley when the trolley travels along the target travel path; if the trolley deviates from the target travel path, the path tracking trajectory of the trolley is determined through the calculated position coordinates and the displacement tracking point, the actual position error of the trolley is self-calibrated according to the path tracking trajectory, and the map beacon corresponding to the path navigation instruction of the trolley in the target travel path is reset according to the self-calibrated actual position. The application can dynamically calibrate the positioning error of the multi-degree-of-freedom AGV trolley, so that the navigation stability of the multi-degree-of-freedom AGV trolley is improved.

The invention discloses a posture adjusting method of a long cantilever movement mechanism, which solves the problem that the position error of a tail end executing mechanism is difficult to control due to the uncertain parking posture of an airplane, the manufacturing error of an adjusting mechanism and the large deflection of a long cantilever, and ensures that the theoretical axis of the movement track planning of the long cantilever movement mechanism is matched with the actual axis of an air inlet channel. The long cantilever mechanism is prevented from colliding with the air inlet channel in the spraying operation process of the air inlet channel; the position adjustment amount is calculated based on the kinematic pair axis actually measured by the adjusting mechanism, the tail end pose error caused by the theoretical kinematic pair axis position and angle error is avoided, and the tail end precision is improved; according to the method, the axis of the long cantilever is fitted in the extending state of the long cantilever, the flexible deformation of the long cantilever caused by gravity is calculated, and the tail end precision is further improved.

One or more embodiments of the invention provide an unmanned aerial vehicle navigation speed error correction method and device. The method comprises the following steps: acquiring visual navigation information and inertial navigation information; wherein the visual navigation information comprises first position information, and the inertial navigation information comprises second position information; evaluating the quality of the visual navigation information; if the evaluation result is available, performing filtering calculation by taking a position error between the first position information and the second position information as an observed quantity based on a preset navigation state vector of inertial navigation, and taking an estimated value of a speed error in a navigation state estimation vector obtained by calculation as a correction result of the speed error; wherein the navigation state vector comprises the position error and the speed error; and if the evaluation result is unavailable, obtaining a differential speed error based on historical first position information in the historical visual navigation information, and calculating by taking the differential speed error as a constraint to obtain a correction result of the speed error.

The invention relates to a method for calculating a northbound gradient of a plumb line deviation prime component in a sea area, and provides the method for calculating the northbound gradient of the plumb line deviation prime component in the sea area aiming at the plumb line deviation prime component compensation requirement of an inertial navigation system under the constraint of a position error of a motion carrier in the sea area. And based on the completely normalized global gravitational potential coefficient, a sea area plumb line deviation prime component northbound gradient calculation model is constructed, and sea area plumb line deviation prime component northbound gradient calculation is realized. The invention aims at improving the vertical line deviation prime component compensation capability of the inertial navigation system under the constraint of the position error of the motion carrier and improving the navigation precision of the inertial navigation system.