330results about How to "Reduce tracking error" patented technology

A magnetic tape including: a nonmagnetic support; a substantially nonmagnetic layer containing nonmagnetic powder and a binder; and a magnetic layer containing ferromagnetic powder and a binder, in this order, wherein the magnetic tape has a coefficient of temperature expansion of from 0 to 10×10−6 / ° C. and a coefficient of humidity expansion of 0 to 7×10−6 / % RH each in a transverse direction of the magnetic tape, and the magnetic tape has a dimensional deformation amount of from 0.01 to 0.06% in the transverse direction in case of applying a tensile stress of 1N to the magnetic tape at 60° C. for 50 hours in a longitudinal direction of the magnetic tape.

The invention discloses a target tracking system and a target tracking method for an underwater sensor network. The target tracking system comprises a land network and a water area network, wherein the water area network comprises multiple underwater target tracking clusters and a water surface treatment center; and the underwater target tracking clusters comprise multiple underwater sensor nodes and a cluster head node. A target state is tracked in combination with an adaptive UKF (Unscented Kalman Filter) and a PF (Particle Filter) on the basis of correcting signal acquisition time delays of the sensor nodes. The tracking error caused by different sources of signals acquired by the sensor nodes at the same moment is reduced by correcting the time delays, so that a target can be more reliably tracked; and the adaptive UFK automatically adjusts a system noise weighing coefficient according to target maneuvering situation to more properly describe a practical target motion state, so that the shortcoming of inaccuracy of target maneuvering of a target motion model is overcome, an important function with more posteriori information is provided for the particle filter, the particle degeneracy is reduced, and the tracking precision is improved.

The invention provides a servo system control method for a five-shaft linked numerically controlled machine tool. The method comprises: a five-shaft linked numerically controlled machine tool servo system obtains ideal position signals of five feed shafts; the ideal position signals of the five feed shafts are processed by feedforward control and feedback control to obtain input control signals of all feed shafts; error compensation control signals of an A shaft and a B shaft and two groups of error compensation control signals of an X shaft, a Y shaft, and a Z shaft are calculated; control signals of the A shaft and the B shaft as well as control signals of the X shaft, the Y shaft, and the Z shaft are calculated; with the obtained control signals of the A shaft, the B shaft, the X shaft, the Y shaft, and the Z shaft, five-shaft linked numerically controlled machine tool servo system controlli9ng is carried out, thereby outputting a practical position signal. According to the invention, feedback control and feedforward control of a single-shaft system as well as multi-shaft cross-coupled control and interference compensation control on linear motion by rotation motion are integrated to realize excellent tracking and contour performances, thereby forming integrated multi-shaft precise linked servo control.

A catheter system allows for percutaneous intervention on the fast-moving structures inside the heart. The device consists of a steerable catheter sheath, an actuated, multi-degree of freedom moving catheter, and a catheter end effector, such as a fixation device. An actuator controls the motion of the catheter guide-wire in the catheter sheath to follow the motion of the target tissue. A control system controls the actuator and compensates for mechanical characteristics of the system including friction and backlash. A 3-D imaging system can be used to view the motion of the target tissue and the catheter end effector and produce 3-D imaging data. The 3-D imaging data can be used by the control system to track the target tissue and accurately position the end effector with respect to the moving target tissue allowing a clinician to repair the target tissue while it is moving. The system can be used to perform mitral valve annuloplasty wherein the actuated catheter compensates for the heart valve motion and an end effector fixation device is used to place fixation items, like anchors or staples, into the heart valve tissue to fix the annulus.

The invention discloses a control method for motion stability and outline machining precision of a multi-shaft linkage numerical control system. The control method achieves control on the motion stability and outline machining errors of the multi-shaft linkage numerical control system by using a compound control mode of multi-shaft parameter module predictive control and non-linear self-adaptive fuzzy proportional-integral-derivative (PID) control. Simultaneously, error module calculating efficiency is improved by building an outline error module, a speed error module and an acceleration error module. By means of performance optimization indexes, tracking errors, outline errors, speed errors and acceleration errors of the system are minimum, and control performance of a multi-shaft servo control system is improved. Multi-shaft parameter module predicative control increment is solved through a simplified calculating module so as to meet real-time requirements of the control system. Robust property of the multi-shaft linkage numerical control system is improved by adopting the non-linear self-adaptive fuzzy PID control method. The control method effectively improves the motion stability and outline machining precision of the multi-shaft linkage numerical control system.

The invention discloses a cervical-vertebra-simulated cradle head mechanism and a motor control method of the cervical-vertebra-simulated cradle head. The mechanical structure of the cervical-vertebra-simulated cradle head mechanism is designed by simulating a series of specific motions when a person tracks an observation target. The cervical-vertebra-simulated cradle head mechanism comprises a vertical lifting assembly, a horizontal rotating assembly and an angle adjusting assembly. The vertical lifting motion of the cradle head mechanism is achieved through the adoption of a ball screw, the horizontal rotating motion is completed in the mode that a pair of reduction gear mechanisms are driven by a direct current servo motor, and the pitching motion and the left-and-right fine adjustment motion are achieved through direct driving of the direct current servo motor. The control method that the PID algorithm is adopted in the motor is adopted and is characterized in that the tracking precision is improved through composite control, the dynamic lag problem is solved, and tracking errors are reduced. The cervical-vertebra-simulated cradle head mechanism is reasonable in structure, light in weight, large in view field, stable in imaging and suitable for machine visual tracking and aviation shooting occasions.

The invention belongs to related technical field of intelligent sensing, and discloses a high-compliance method for guiding a robot to cooperatively work by people. The method comprises the followingsteps: (1) a human-computer cooperation system is provided; (2) the robot is towed for demonstration; a six-dimensional force sensor and a motor encoder of the human-computer cooperation system respectively measure information of force applied by operators and the angle and the angle speed of each joint of the robot; and a computer obtains the terminal speed and pose of the robot through robot kinematics calculation; and (3) the robot motion position and pose desired by the operators at the next time are predicted by adopting a sparse bayesian learning algorithm based on the information obtained in the step (2); and the torque of each joint is compensated through online adjustment of impedance parameters of an impedance controller according to the predicting result and design of a linear secondary adjuster. The method improves the compliance and the demonstration precision of the robot, and reduces the demonstration difficulty of the operators.

The invention discloses an image guiding and tracking method based on prediction, which comprises the following steps: 1, inputting image sequences and a breathing status feature set of a tumor anatomical structure; 2, establishing a status association database; 3, acquiring real-time images and breathing status features; 4, predicting the delayed breathing status features, and determining the image sequences in a corresponding tumor shape varying section; 5, registering the real-time images with the image sequences in the tumor shape varying section one by one in an interested area; 6, selecting an optimal tumor shape image from registration results; and 7, outputting the image of the tumor anatomical structure. The image guiding and tracking method based on the prediction establishes the correlation between breath and tumor movement by the quantification and analysis on the breathing statuses, predicts the breath and tracks the movement according to the correlation, and improves the efficiency and the accuracy of tracking a dynamic tumor in real time.

The invention mainly relates to a design method of a reinforcement learning based optimal tracking controller for a model unknown servo system. The design method of the reinforcement learning based optimal tracking controller for the model unknown servo system is introduced mainly on the basis of a simplified reinforcement learning evaluation-execution structure with a high-order neural network approach method, and the optimal tracking control solution speed of a motor is increased. As for the model unknown servo system, firstly, homeostatic control is solved with a multilayer neutral networkintelligent identification system model; performance indexes are given, and a high-order neutral network approach optimal performance index function is applied; an HJB (Hamilton-Jacobi-Bellman) equation is established according to an approximate performance index function and the identification system model, and the optimal feedback control of the servo system is solved. The optimal tracking control is calculated according to the solved homeostatic control and optimal feedback control, so that tracking error accumulation values and system energy consumption are minimized simultaneously while load rotation angle and rotation speed rapidly track given signals.

The invention discloses a permanent magnet linear synchronous motor slip form control system based on a linear expansion state observer, and belongs to the technical field of linear motor control. The system comprises the following steps that: firstly, establishing the dynamic equation of a permanent magnet linear synchronous motor on a two-phase synchronous rotation orthogonal coordinate system; secondly, simplifying the dynamic equation into a special two-order integral series type mathematical model; thirdly, designing the linear expansion state observer to obtain a disturbance estimated value, and considering the estimated value in the design of a slip form control law to eliminate a chattering phenomenon; and finally, applying a Lyapunov stability theory to analyze the stability of the system. The system has the most important characteristics that the state and the disturbance of the system can be accurately estimated by the linear expansion state observer. In addition, the control system is high in robustness, and a given displacement signal can be accurately tracked. In addition, the chattering phenomenon of slip form control can be greatly improved so as to be suitable for designing the permanent magnet linear synchronous motor servo control system.

The present invention discloses a cross-lens multi-target tracking method and a device based on space-time constraint. The method includes: performing image preprocessing on different color spaces so that the images are consistent in color temperature and hue to obtain the photographing information of multiple photographing devices; establishing a corresponding relationship between 2D points through the projection matrix of the photographing devices to obtain geometric information among the multiple photographing devices, wherein the projection matrix is a projection matrix about the 3D world; and performing human body characteristics matching among the multiple cameras according to the photographing information and the geometric information to take advantage of the apparent and temporal characteristics of the tracking target to obtain the pictures and the real time tracking result of each photographing device. By combining the current multi-target tracking algorithm with the multi-camera processing method and using the attitude and posture matrix of the camera network, the method can achieve multi-target tracking based on multiple cameras. This improves the robustness of target tracking but reduces the tracking error, therefore, increasing the tracking accuracy.

The invention discloses a target tracking method based on target template updating. A target template base is established based on particle filtering principles under characteristic fusing and employing a video block multi-task means. The information of the next frame and target information in the target template base are matched and sorted by using color and edge characteristics. Template memory criteria are used to update the target template base, thereby realizing target long-term memory under different states. The target tracking method overcomes the defect that conventional video target tracking technology is likely to be influenced by external interference. Targets can be accurately positioned, and tracking errors can be effectively reduced.

The invention provides an unmanned vehicle-side longitudinal coupling tracking control method based on a rapid terminal sliding mode principle. The method comprises the following steps: 1) selecting an input parameter and an output parameter of an unmanned vehicle-side longitudinal coupling tracking controller; 2) defining a tracking control error and a state equation; 3) using the tracking control error as a state variable and establishing a rapid terminal sliding mode; 4) taking a rapid terminal tendency rate as a sliding mode tendency rate of the tracking control; 5) according to a vehicle dynamics model and the above content, deriving a coupling relation between an expected driving force or a braking force and an expected side force; 6) calculating an expected front-wheel turning angle; 7) according to positive or negative of obtained reverse longitudinal force model output, determining whether an expected throttle percentage or an expected braking torque should be calculated currently; 8) calculating the expected throttle percentage or the braking torque. From a simulation result, by using the method in the invention, error precision of position tracking control is increased and good error precision of speed tracking control is possessed.

The invention provides a direct-driven XY table profile control method based on predictive control and cross coupling, and belongs to the technical field of automatic control. The device comprises a signal collector, a position setter, a predicating controller, a cross coupling controller and a driving device, wherein the cross coupling controller comprises a profile error estimating device and a profile error compensating device. The direct-driven XY table profile control device and method based on predictive control and cross coupling are provided by the invention according to the characteristics of a direct-driven XY platform; the predicating controller is adopted to control a single shaft, so that the tracking error in the system can be reduced, and the precision in positioning of double shafts can be indirectly improved; and the cross coupling controller is adopted on the dual-shaft for decoupling, so that the profile error of the system can be directly compensated, and the precision in processing can be improved.

The invention relates to an inertial navigation platform and Beidou satellite-based high-precision and ultra-tightly coupled navigation method. According to the method, a stochastic linear time-invariant discrete system mechanical model is established according to a moving object state equation and a measurement equation; statistic analysis is performed on the first-order difference sequence and second-order difference sequence of redundancy measurement values of a system, so that a redundancy measurement-based adaptive Kalman filtering algorithm can be realized, and therefore, the measurement noises of the system can be estimated accurately, and noise variance R can be adjusted adaptively; according to a traditional ultra-tightly coupled structure, a neural network prediction module is introduced so as to be used for assisting a Beidou satellite carrier tracking loop and a code tracking loop under a lock loss state; a time delay filter is adopted for a Beidou satellite receiver, and therefore, the correlation between loop tracking errors and update time in the ultra-tightly coupled system can be significantly improved. The method of the invention belongs to the navigation control technical field and can be applied to high-precision navigation of carriers carrying strapdown inertial navigation platforms.

A method for correcting track errors generated during iterative learning of an industrial robot comprises the following steps that firstly, a specific controlled object is determined, an electric current loop or a speed closed loop is adopted as the controlled object, and optimizing and setting of control parameters are carried out on a whole control loop; and secondly, according to the formula (please see the specification), the learning gain phi is changed, the position of the starting point of a N(z) Nyquist curve and the amplitude of the curve are adjusted, introduced offline lead compensation factors enable the N(z) Nyquist curve to achieve translation, more curves fall into a unit circle, gamma=1,2,3...n, and in the formula, q is the feedback gain, and gamma is the number of samplingperiods. According to the method, the design of a robot iterative learning controller is provided according to the characteristic that the industrial robot operates on the same track multiple times,the robot has the self correction capacity, the experience in the previous operating track process is gained to guide operating of subsequent tracks, the more the robot operates, the higher the accuracy is, following errors are reduced greatly, and the accuracy of track operating is improved.

The invention provides a self-adaptive radar antenna position oscillation treating method and aims to provide a method capable of detecting characteristics of a radar antenna position automatically and eliminating position oscillation when the radar antenna position is found out. The technical scheme includes that in a tracking radar servo control system, motor current of a servo controller is taken as negative feedback of an electric current ring, motor speed is taken as negative feedback of a speed ring, a position ring is designed to be controlled proportionally and integrally, and the current ring and the speed ring are designed into servo system loops which are controlled proportionally, integrally and differentially; an operation processor arranged inside the servo controller is used for receiving and executing control commands transmitted by a radar terminal system and error information transmitted by a radar information processing system and regularly detecting errors of tracking positions of a radar antenna. When oscillation of the radar antenna position is detected, the proportionality coefficient and the integration coefficient of a servo control position loop are gradually decreased during every calculation period, and output voltage is lowered to eliminate the oscillation.

The invention discloses an adaptive tracking method for a receiver in a high-dynamic environment. According to the adaptive tracking method, bandwidths of loop filters for a frequency-locked loop, a phase-locked loop and an auxiliary phase-locked loop of the frequency-locked loop are adjusted by detecting the dynamic property and the signal-to-noise property of tracking signals of the receiver in real time, so that optimum values of the bandwidths are kept; meanwhile, a dynamic application range of a tracking loop is widened by adjusting an auxiliary coefficient of the auxiliary phase-locked loop of the frequency-locked loop, so that stability of the tracking loop in the high-dynamic environment is improved. The adaptive tracking method for the receiver in the high-dynamic environment has the advantages that the adaptive tracking method is capable of enabling the receiver to adjust own parameters timely in a dynamic change environment, errors of tracking satellite navigation signals are kept within a small range, and the shortcomings of large tracking errors and proneness to lock loss of the receiver in the prior art are overcome.

The invention discloses a reentry vehicle PID (proportion, integration and differentiation) type sliding mode posture control method based on self-adaptive fuzziness, relates to a PID type sliding mode posture control method of reentry vehicles and belongs to the technical field of vehicle control. Aiming at parameter adjusting characteristics of a PID type sliding mode function, PID type sliding mode parameters are enabled to have time-variant characteristics, so that a system is ensured to output tracking instruction information quickly while the problems of system overshoot and control input saturation of the system are avoided. A global sliding mode algorithm is introduced to improve a PID type sliding mode dynamic equation, so that robustness of a conventional PD sliding mode is enhanced. By applying a self-adaptive fuzzy logic system, the system is ensured to output the tracking instruction information quickly, response overshoot and control input saturation of the system are avoided, tracking errors can be reduced, and robustness of the conventional PD sliding mode can be improved.

The invention discloses a distributed cooperative adaptive cruise control (CACC) method near an intersection based on wireless communication, and aims to provide an optimal route proposal for each vehicle so that the vehicle can pass through the intersection without being interrupted, and minimize an intersection delay so that as many vehicles as possible can pass through the intersection. The method is characterized by fully utilizing the V2X communication technology and an ACC system to establish a distributed CACC vehicle motion model suitable for a road intersection; utilizing a fleet control method based on a particle swarm optimization algorithm to effectively reduce the tracking error of the vehicle; using a trajectory planning method and a space management method to provide convenience for a sub-fleet or an individual vehicle to accelerate through the intersection or decelerate to wait for a next opportunity; and reorganizing the fleet to increase the throughput of the intersection in consideration of vehicle safety, fuel consumption, speed limit, different characteristics of the vehicle and passenger comfort.

The invention relates to a high-frequency angular vibration rotary table sliding-mode control method based on iterative learning and belongs to the technical field of measurement and control. The method comprises the steps of conducting mathematical modeling on a permanent magnet synchronous motor, designing a sliding-mode variable structure control law and an iterative learning control law, and conducting sliding-mode control based on the iterative learning control law. Due to the fact that the sliding-mode control arrival process is replaced with the iterative learning control law learning process, the frequency response bandwidth of an angular vibration rotary table is increased, high-frequency inertial navigation device testing precision is improved, high-band periodic signal tracking precision of the angular vibration rotary table is improved, the influence of periodic disturbance and stochastic disturbance on a system is effectively restrained, the responding speed of the system is high, the tracking error is small, and robustness is higher.

A path tracking control method of an intelligent vehicle comprises the following steps that 1) a two-freedom-degree planar movement model of the vehicle is established and simplified according to control demands to obtain a nonlinear vehicle path tracking control model; 2) an expected yaw angle function psid is constructed so that the yaw angle function psid satisfies that the lateral displacementdeviation Ye of the vehicle is converged to 0 when the yaw angle of the vehicle approaches an expected yaw angle; 3) a yaw angle tracking control problem is converted into a yaw angle calming problem; 4) a nonlinear control including an expected yaw angle module, an expanded state observer and a nonlinear error feedback control law of a non-singular terminal sliding-mode is designed; and 5) pathtracking control is carried out on the vehicle on the basis of the nonlinear controller.

The invention discloses a loop self-regulation method of a satellite navigation receiver. Judgment and steps for optimizing loop parameters are increased on the basis of keeping original tracking loop structures of the receiver, and loop orders and noise bandwidth can be automatically adjusted according to carrier dynamic information. The method does not need to add a complete inertial navigationsystem additionally.

A multi-leaf collimator for a radiotherapy apparatus comprises a plurality of elongate leaves mounted in a carriage, the carriage being mounted on a substrate, wherein the leaves are independently moveable relative to the carriage in a longitudinal direction, and the carriage is moveable in that direction relative to the substrate, and a control apparatus arranged to receive a signal representing leaf positions relative to the substrate and being arranged to control the leaf positions relative to the carriage and the carriage positions relative to the substrate so as to achieve those leaf positions relative to the substrate. By allowing the carriage to be driven concurrently with the leaves, the speed of movement of the carriage can be added to that of the leaves. In this way, where leaves are required to make a long traverse they can do so more quickly. Most MLCs have a means for sensing the current positions of the leaves relative to the substrate, such as an optical or mechanical positional feedback system. The control apparatus can therefore compare the current leaf positions to the signalled leaf positions, and move the leaves and the carriage accordingly. Each leaf can be moved according to a difference between the current leaf position and the signalled leaf position, and the carriage can be moved according to an average difference between the current leaf positions and the signalled leaf positions. A corresponding method is also disclosed.

The invention discloses a control method achieving tension feedback and joint position feedback and used for a flexibility driving unit for a robot joint and belongs to the field of robot application and control. The invention aims to realize the tension feedback and the joint full-closed loop control of the flexibility driving unit for the robot joint so as to reduce flexibility driving joint control errors and improve system frequency response. The method discloses a control strategy based on viscoelasticity kinetic model compensation and gives the design of the flexibility driving unit controller. A front feed controller is designed according to a steel wire elastic deformation formula and a feedback controller is designed according to a motor angle estimate value formula. The design method is suitable for the design of a controller of the flexibility driving unit for the robot joint. Hardware of a flexibility driving unit control system is constructed, joint position feedback is performed through a joint encoder and motor position feedback is performed by utilizing motor position estimated values, so that full closed-loop position control of the control system of the driving unit is realized. Compared with a classic PID(Proportion Integration Differentiation) control method, servo control precision can be improved distinctively, tracking errors can be reduced and system frequency response can be improved.

The invention discloses a Bezier curve control method and system for an AGV. The method comprises the following steps: drawing all preset paths by using a Bezier curve; forming scheduling informationaccording to the task information and the AGV terminal position information and state information, and performing task path planning; using the AGV terminal for issuing the scheduling information andthe task path to execute the task; obtaining a task path and reading geometrical information of each task path section; and performing trajectory tracking on a single task path segment. The method isbased on Bezier curve tracking and fixed-point parking. On the basis of a traditional scheme, optimization is carried out from three aspects of speed, precision and driving posture smoothness; compared with an AGV trajectory tracking method adopting straight lines and arcs, the invention has the advantages that the problem of path irregularity during path planning is solved, an improved pure tracking strategy is adopted, and the method is suitable for various different AGV driving mechanism types, so that the AGV can smoothly operate at a higher speed on the basis of ensuring the precision, and the single-machine operation efficiency is greatly improved.

The present invention provides a tracking apparatus for tracking a target designated on an image which is captured by an image sensing element, including a calculation unit configured to calculate, for each of feature candidate colors, a first area of a pixel group which includes a pixel of a feature candidate color of interest and in which pixels of colors similar to the feature candidate color of interest continuously appear, a second area of pixels of colors similar to the feature candidate color of interest in the plurality of pixels, and a ratio of the first area to the second area, and an extraction unit configured to extract a feature candidate color having the smallest first area as a feature color of the target from feature candidate colors for each of which the ratio of the first area to the second area is higher than a predetermined reference ratio.

The invention discloses a spacecraft automatic rendezvous obstacle avoidance method and system. The method comprise the steps of solving the shortest Euler distance under the ellipsoid, constructing atarget attraction potential function, constructing an obstacle avoidance potential function under the sigmoid function, designing a controller based on a speed artificial potential function, and designing a suboptimal speed artificial function controller based on the state dependent Riccati equation. The method is applicable to spacecraft automatic rendezvous obstacle avoidance control, and can calculate the distance between the spacecraft and a target spacecraft or an obstacle more accurately through determining the shortest Euler distance under the ellipsoid, thereby being capable of more accurately controlling the trajectory of the spacecraft, and reducing unnecessary fuel consumption; and meanwhile, the sigmoid function is introduced into the aerospace field for the first time to define the obstacle avoidance potential function so as to form the overall potential function and thus design appropriate control laws, thereby being capable o more accurately controlling the trajectory of the spacecraft when being away from or getting close to the obstacle, and having more accurate flight trajectory and higher response speed.

The invention relates to an improved Kalman filtering method used for target tracking. The method comprises the following steps that S1, the motion equation of the observation target is established, the motion equation includes the dynamic equation and the observation equation, and the observation value of the target is obtained according to the observation equation; S2, the filtering value of thetarget position information after Kalman filtering is obtained; S3, the threshold is set and the residual error of the filtering value and the observation value is calculated, and the step S4a or S4bis performed according to the relationship between the threshold and the residual error; S4a, if the residual error is not greater than the threshold, the filtering value is directly used as the prediction value and the prediction position of the target at the next moment is obtained; S4b, if the residual error is greater than the threshold, weighted summation is performed on the filtering valueand the observation so as to obtain the updated prediction, and the prediction position of the target at the next moment is obtained according to the updated prediction value; and S5, the steps are repeated so as to obtain the prediction motion tracks of the target. The accuracy of target tracking can be enhanced and the tracking error of maneuvering of the target can be reduced.

The invention discloses an intelligent path tracking control method of an unmanned surface vehicle, and belongs to the field of navigation control of unmanned surface vehicles. In the path tracking control process of the unmanned surface vehicle, firstly, an expected course angle of the unmanned surface vehicle is solved through an expected path point position and real-time positions of the unmanned surface vehicle according to a proposed adaptive radius sight line method, and then the solved expected angle is subjected to angle compensation according to a course deviation and an off-course distance, so that the unmanned surface vehicle obtains the optimal expected course angle. In a course control link, an adaptive intelligent fuzzy controller is designed, in a navigational speed controllink, a navigational speed resolver is designed firstly, the optimal navigation speed is solved in real time, and then a navigational speed controller based on integral S surface control is designed.According to the path tracking method, the optimal expected angle can be effectively solved, the expected angle can also be tracked at the optimal navigational speed, thus the unmanned surface vehiclegradually converges to an expected path, and path tracking performance of the unmanned surface vehicle is greatly improved.