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Improved SCARA robot kinetic parameter identification method

A dynamic parameter and identification method technology, applied in the field of improved SCARA robot dynamic parameter identification, can solve problems such as acceleration signal error and transmission error, and achieve the effect of avoiding transmission error.

Active Publication Date: 2018-02-09
WUXI XINJIE ELECTRICAL
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Problems solved by technology

[0005] In addition, when processing sampled data, in addition to taking the average value of multiple samples to improve the signal-to-noise ratio, how to obtain the effective angular acceleration signal is a difficult problem
Due to the noise in the velocity signal obtained by sampling, the velocity signal is directly differentiated, and the obtained acceleration signal has a large error
Therefore, the angular acceleration is generally obtained by reverse fitting the joint angles obtained by sampling, and then differentiated twice to obtain the angular acceleration, but the two times of differentiation are likely to cause transmission errors

Method used

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  • Improved SCARA robot kinetic parameter identification method

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Embodiment Construction

[0040] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and in conjunction with a specific SCARA robot.

[0041] Step (1): Establish a complete dynamic model of the first two joints of the SCARA robot using the Lagrange method.

[0042] attached by figure 2And attached image 3 It can be seen that joints 3 and 4 of the SCARA robot share a connecting rod, and the servo motors, timing belts, ball screws, and lifting tables of joints 2, 3, and 4 are all installed on the connecting rod of joint 2, so joints 1 and 4 2 determines the plane positioning accuracy and trajectory tracking accuracy of the SCARA robot, and joint 3 determines the vertical movement. Since joint 3 is perpendicular to the first two joints, the movement of the first two joints will not affect joint 3. Therefore, only joint 1 and joint 2 are used...

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Abstract

The invention relates to the field of SCARA robot kinetic parameter identification, and discloses an improved SCARA robot kinetic parameter identification method. A Lagrange method is adopted for establishing an SCARA robot integral kinetic model comprising a friction term, and the SCARA robot integral kinetic model is subjected to linearization. The five-order fourier series is adopted as the stimulation track basic form, the polynomial with 5 degree is used for replacing the constant term in the traditional fourier series, and the joint angular velocity and angular acceleration are zero at the track start and stop time; and the minimum observing matrix conditional number serves as the target, and to enhance the global optimization capability, various coefficients of the stimulation trackare optimized through the niched pareto genetic algorithm based on the crowding-out mechanism. To avoid the transmission error directly caused to the joint angle two-time differential, the sampled joint angular velocity data are fitted into the fourier series form, and a joint acceleration signal is obtained through the differential. Considering the measuring noise influence, the WLS is adopted as the parameter estimation method.

Description

technical field [0001] The invention belongs to the field of dynamic parameter identification of a SCARA robot, and in particular relates to an improved dynamic parameter identification method of a SCARA robot. Background technique [0002] With the application of industrial robots in high-precision fields such as life medicine, laser welding, and automotive electronics, robot technology is developing in the direction of high speed and high precision. The control strategies of industrial robots can be divided into two types: (1) Negative feedback control is performed according to the deviation between the actual trajectory and the expected trajectory of the robot. The control law of this control method is simple and easy to implement, which is called "motion control", such as PID control, fuzzy control, robust control, etc. (2) Fully consider the dynamic characteristics of the robot, and design a more refined nonlinear control law, that is, a model-based control strategy. T...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/163B25J9/1633B25J9/1653
Inventor 李新白瑞林严浩吉峰
Owner WUXI XINJIE ELECTRICAL
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