38results about How to "Reduce contour error" patented technology

The invention relates to a servo system contour control method, in particular to a servo system contour control method based on a task polar coordinate system. The servo system contour control method based on the task polar coordinate system comprises the first step of establishing an XY motion platform kinetic equation, the second step of establishing the task polar coordinate system based on osculating circle proximity according to expected track information and calculating the corresponding coordinate transformation relation, the third step of converting a system kinetic equation under a Cartesian coordinate system into an error kinetic equation under a task polar coordinate, and the fourth step of designing a feedback PD controller based on the feedforward compensation and achieving the decoupling control on the error kinetics. The decoupling contour control method based on the task polar coordinate system has the advantage that the contour error caused during the high-speed and large-curvature contour machining process can be greatly reduced.

The invention discloses a contour control method for complex trajectories. The method combines a cross-coupling control frame with contour error pre-compensation function to establish an adaptive data model for each axis participating in the servo motion, according to the current target position point and several The historical position point value is used to determine the parameters of the servo controlled object to be identified, and the control parameters are adjusted in real time through the pole configuration algorithm. This method of adjusting the current control output according to the historical control quantity and the future control quantity effectively suppresses the disturbance of the bounded process and improves the precision of the contour control and the stability of the process.

The invention belongs to the technical field of precision and high-efficiency numerical control machining, and can effectively improve the accuracy of contour error estimation for free curves with different curvature changes, thereby reducing contour errors generated during contour tracking motion. It includes the following steps: Step 1: Calculate any reference point R on the desired machining contour of the H-type precision motion platform 1 Curvature ρ and curvature radius r at (t); Step 2: Calculate any reference point R on the expected machining contour of the H-type precision motion platform 1 (t) place tangent line and X-axis angle α; Step 3: calculate the circle center coordinate (O of the inscribed circle according to geometric relationship x o y ); Step 4: Use the area of ​​the triangle to calculate the central angle β and its corresponding arc length l; Step 5: Calculate R with the arc length l 2 (t) to R 1 (t) the motion time Δt; Step 6: use the second-order Taylor series expansion to calculate R 2 (t) coordinates (R 2x R 2y ); Step 7: Calculate the estimated contour error E of any trajectory by using the area of ​​the triangle c .

The invention belongs to the field of robot milling, and discloses a method for acquiring an optimal installation position of a workpiece based on contour errors. The method comprises the following steps of: (a) in a robot milling process, planning the machining track, feeding speed and main shaft rotating speed of a to-be-machined workpiece, and calculating the cutting force corresponding to eachcutter location point on the machining track in a base coordinate system of the robot; (b) calculating the contour error of each cutter location point and an average value of the contour errors of all the cutter location points; (c) building an optimization model enabling the average contour error to be minimum, calculating the optimal installation position of the workpiece according to the optimization model, thus acquiring the optimal installation position of the workpiece. By means of the method, the optimal installation position with the minimum contour error in the robot milling processcan be obtained, and the machining precision is improved.

The invention discloses a magneto-rheological polishing removal function deduction method, comprising the steps of: under given process parameters, respectively collect polishing spots with different immersion depths on spherical mirrors with different curvatures to obtain experimental removal functions; The spline magnetorheological polishing removal function parameterization model and the particle swarm optimization algorithm calculate the shape coefficients corresponding to each removal function; the corresponding relationship between the removal function shape coefficients under different curvatures and immersion depths relative to the reference spot shape coefficients is established, and the removal The normalized shape coefficient of the function; establish the change law function of the magnetorheological polishing removal function about the curvature and immersion depth; according to the change law function of the shape coefficient of the removal function, construct the reverse deductive model of the magnetorheological polishing removal function under the curvature effect, and solve the curvature and Removal function corresponding to immersion depth. The invention solves the problems of large error of the removal function model, high acquisition cost and low efficiency under the curvature effect of the current magneto-rheological polishing.

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 contour error cross-coupling control method based on interference observation sliding mode variable structure. The method provides a control strategy combining sliding mode variable structure control, a disturbance observer and cross-coupling control and comprises steps of: designing a single-axis servo sliding mode variable structure controller based on disturbance observation; performing stability analysis on a sliding mode variable structure control algorithm based on disturbance observation; designing a cross-coupling controller based on a PID control algorithm; and performing result simulation and analysis. The sliding mode variable structure control based on disturbance observation can eliminate the influence of disturbance, enhancs system robustness and achieves accurate tracking of single-axis motion. The cross-coupling control is configured to eliminate the influence of gain parameters and dynamic mismatch between axes, reduces the contour error to achieve multi-axis coordinated motion. Finally, the effectiveness and superiority of the control method are proved by a two-axis system simulation model, and the tracking error and contour error are effectively compensated.

The invention discloses a synchronous cross-coupling robot contour control method, comprising: acquiring a desired position x in a workspace d , y d , perform the kinematic inverse solution operation on it, and output the desired position θ in the joint space 1d , θ 2d ; Compare it with the actual joint space position θ 1a , θ 2a After the difference operation, output the x-axis tracking error E of the joint space 1 , joint space y-axis tracking error E 2 ;x-axis joint space tracking error E 1 , y-axis joint space tracking error E 2 After the PD controller operation, the motor is driven; at the same time, according to the x-axis joint space tracking error E 1 , y-axis joint space tracking error E 2 Calculate the contour error ε separately c , synchronization error ε s , the contour error ε c , synchronization error ε s After being calculated by the contour controller and the synchronous controller, respectively, the corresponding gains are compensated to the position loop of the workspace and the velocity loop of the joint space. It can further reduce the contour error, improve the control effect, and then ensure the tracking accuracy of the robot system.

The embodiment of the present invention discloses a method for NURBS reverse control point estimation, which is characterized in that it includes the following steps: Step 100, through the known tool position point and setting the error threshold value fitted to the NURBS curve profile, the tool calibration Simplify the position points, and select the tool position point representing the typical contour; step 200, determine the initial value of the control point by adding 2 to the simplified tool position point; step 300, use the initial value of the control point as the fitting initial value, and use Perform fitting, and calculate the fitted contour error; step 400 , compare each calculated contour error with an error threshold, and increase or decrease control points according to the comparison result until the error threshold is met with the least number of control points. The present invention breaks through the shortcomings of the traditional method, estimates more accurate control points according to the known contour threshold, and calculates the required control points after several iterations based on this, which can greatly improve the efficiency of reverse NURBS calculation.