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Runge-Kutta type periodic rhythm neural network method capable of resisting periodic noise

A neural network and periodic noise technology, applied to manipulators, program-controlled manipulators, manufacturing tools, etc., can solve problems such as numerical solutions deviating from ideal values, inability to overcome initial errors and error accumulation, and failure of manipulator motion planning

Active Publication Date: 2019-07-12
SOUTH CHINA UNIV OF TECH +1
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Problems solved by technology

However, the equality constraints in the existing quadratic programming-based methods are all directly substituted into the forward kinematics equation of the robot. Such equality constraints cannot overcome the initial error and error accumulation problems.
At the same time, if there is noise interference in the neural network model, the numerical solution may deviate greatly from the ideal value, or even have no solution so that the motion planning of the robot arm fails.

Method used

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  • Runge-Kutta type periodic rhythm neural network method capable of resisting periodic noise
  • Runge-Kutta type periodic rhythm neural network method capable of resisting periodic noise
  • Runge-Kutta type periodic rhythm neural network method capable of resisting periodic noise

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Embodiment Construction

[0065] The implementation of the present invention will be further described in detail below in conjunction with the embodiments and drawings, but the implementation of the present invention is not limited thereto.

[0066] Such as figure 1 and figure 2 A Runge-Kutta type periodic rhythmic neural network method that can resist periodic noise as shown, comprises the following steps:

[0067] S1. Given the terminal task, the quadratic optimization model uses the weighted sum of the mixed torque and the square of the square of the angle offset as the optimization index on the acceleration layer, and its function is to reduce the external force on the body during the tracking process Torque and joint angle offset, inverse kinematics analysis of the trajectory of the robot arm, the formula of the weighted sum is as follows:

[0068]

[0069]

[0070] Where t is time, σ=0.8 is the weight of torque in the optimization index, θ(t), The joint angle vector, joint angular velo...

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Abstract

The invention discloses a Runge-Kutta type periodic rhythm neural network method capable of resisting periodic noise. The Runge-Kutta type periodic rhythm neural network method comprises the followingsteps that a tail end task is given; inverse kinematics analysis is conducted on the track of a mechanical arm through doble-infex quadric form optimization, so that a quadric form optimization scheme of the weight sum and indicator of the minimum torque and the angular deflection two-norm square of the mechanical arm is converted into a standard quadratic programming problem; the Karush-Kuhn-Tucker optimality condition is solved through a continuous time periodic rhythm neural network, so that a continuous time model is obtained; a discrete periodic rhythm neural network is obtained througha Runge-Kutta method, and a discrete solution of an original quadratic programming problem is obtained through the neural network; and finally, a result is transmitted to a mechanical arm controller,and the mechanical arm is driven to trace the track. The discrete periodic rhythm neural network designed through the method has the capability of inhibiting the periodic noise in the network model; in addition, the influence of an initial error of the mechanical arm on the motion programming can be eliminated; and motion of the mechanism arm is programmed successfully.

Description

technical field [0001] The invention relates to the technical field of motion planning and control of a mechanical arm, in particular to a Runge-Kutta type periodic rhythmic neural network method capable of resisting periodic noise. Background technique [0002] Redundant manipulator refers to a special kind of manipulator whose number of active joints is greater than the absolute motion parameters of the end. Due to the particularity of the structure, this type of robot has the advantages of high flexibility, avoiding obstacles, overcoming singularity and realizing fault-tolerant operation, etc. . [0003] Since the inverse kinematics mapping equation of the redundant manipulator has nonlinear characteristics, it is difficult to obtain an analytical solution through the kinematics equation at the position layer. A commonly used method is to use the method of quadratic programming, which has great flexibility. In the framework based on quadratic programming methods, the n...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/161B25J9/1664
Inventor 张智军何铭震陈思远
Owner SOUTH CHINA UNIV OF TECH
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