Flexible mechanical arm composite control method based on intelligent learning evaluation

A flexible manipulator and compound control technology, applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve the problems of poor control accuracy and achieve the effect of improving control accuracy and comprehensive feedback information

Active Publication Date: 2017-05-31
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0004] In order to overcome the deficiencies of poor control accuracy of existing flexible manipulator control methods,

Method used

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  • Flexible mechanical arm composite control method based on intelligent learning evaluation
  • Flexible mechanical arm composite control method based on intelligent learning evaluation
  • Flexible mechanical arm composite control method based on intelligent learning evaluation

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Experimental program
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Effect test

Embodiment Construction

[0042] refer to figure 1 . The specific steps of the compound control method of the flexible manipulator based on intelligent learning evaluation of the present invention are as follows:

[0043] (a) Consider the dynamic model of a 2-DOF flexible manipulator:

[0044]

[0045] Among them, M is a positive definite symmetric inertia matrix, is a term related to Coriolis force and centripetal force, D 1 、D 2 is the damping matrix, K 2 is the stiffness matrix, and u is the joint input moment. is a generalized vector composed of the joint angle of the manipulator and the flexible mode, where θ i is the i-th joint angle variable, δ i,j is the jth modal variable of the ith link.

[0046] Connecting rod length l 1 = l 2 =0.5m, connecting rod mass m 1 =m 2 =0.1kg, connecting rod bending stiffness EI 1 =EI 2 =10N·m 2 , the terminal equivalent mass m p = 0.1 kg. deduced from this

[0047]

[0048]

[0049] i takes 1, 2, and the modal order m=2.

[0050] (b...

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Abstract

The invention discloses a flexible mechanical arm composite control method based on intelligent learning evaluation. A technical problem of poor control precision of the current flexible mechanical arm control method is solved. The method comprises steps that linear processing is performed on the existing flexible mechanical arm model; nondeterminacy of lumping of the system is considered by a controller; nondeterminacy of a neural network approximate system is introduced; modeling errors are further considered; a system prediction model is designed; and the modeling errors are introduced into neural network weight self-adaption updating rule. Thus, feedback information is quire comprehensive, control precision is improved and engineering requirements are met.

Description

technical field [0001] The invention relates to a method for controlling a flexible manipulator, in particular to a compound control method for a flexible manipulator based on intelligent learning evaluation. Background technique [0002] Due to its structural elasticity, flexible manipulators will deform and vibrate during motion, which is not conducive to high-precision control. Many control theories have been applied in the control of flexible manipulators. Proportional-derivative control is less robust; both adaptive control and robust control algorithms have a certain ability to adapt to the parameter changes of the flexible manipulator, but require accurate models and parameter variation ranges; singular perturbation control methods require perturbation parameters Small, the application has certain limitations. [0003] The paper "Collision dynamics analysis of satellite capture by flexible manipulator, neural network control for stabilizing motion and vibration supp...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/048
Inventor 许斌张琪杨代朋程怡新韩毅
Owner NORTHWESTERN POLYTECHNICAL UNIV
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