Improved Bouc-Wen model hysteresis modeling method

A hysteresis modeling and model technology, applied in the field of control, can solve problems such as insufficient descriptiveness, and achieve the effect of improving the modeling effect

Active Publication Date: 2019-09-17
JILIN UNIV
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Problems solved by technology

However, the classical Bouc-Wen model is suitable for describing rate-independent and symmetric hysteresis loops, but it is not descriptive enough for frequency-dependent and amplitude-dependent asymmetric hysteresis loops that appear in piezoelectric and other smart materials

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  • Improved Bouc-Wen model hysteresis modeling method
  • Improved Bouc-Wen model hysteresis modeling method
  • Improved Bouc-Wen model hysteresis modeling method

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Embodiment Construction

[0049] Concrete steps of the present invention are as follows:

[0050] Step 1: Based on the Bouc-Wen model and the fuzzy neural network, the discretized Bouc-Wen parameter model is used as the aftermath of the fuzzy neural network to obtain an improved Bouc-Wen model. Such as figure 1 , figure 2 shown.

[0051] The differential equation of the Bouc-Wen model is discretized to obtain the discretized Bouc-Wen model:

[0052] The Bouc-Wen model expression is:

[0053]

[0054] Among them, y represents the hysteretic output displacement of the system, u represents the input voltage of the system, α, β, γ, η represent the parameters of the Bouc-Wen model, and h represents the hysteretic nonlinear term of the system.

[0055] The discretized Bouc-Wen parameter model is:

[0056]

[0057] Step 2: According to the discretized Bouc-Wen parameter model, use it as the aftermath network part in the fuzzy neural network to construct an improved Bouc-Wen model.

[0058] The disc...

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Abstract

The invention discloses an improved Bouc-Wen model hysteresis modeling method, and belongs to the technical field of control. In the method, the Bouc-Wen model is taken as a back-end network part of a fuzzy neural network, parameters of a Bouc-Wen model can be adaptively adjusted according to a neural network, and asymmetric hysteresis loops related to frequency and amplitude of a piezoelectric ceramic micro-positioning platform are enabled, so that high-precision hysteresis modeling is realized. The method comprises the following steps of: deriving a discretized Bouc-Wen parameter model equation; constructing an improved Bouc-Wen model; measuring and obtaining data required by modeling according to the piezoelectric ceramic micro-positioning platform; and using a gradient descent method to obtain input and output data pairs. According to the method, the modeling effect of the model on the frequency-dependent and amplitude-dependent asymmetric hysteresis loop is greatly improved, and a foundation is laid for design and practical application of a controller behind a piezoelectric ceramic micro-positioning platform.

Description

technical field [0001] The invention belongs to the technical field of control. Background technique [0002] Piezoelectric actuators have been widely used in many precision manufacturing fields, such as objective scanners, precision positioning, etc. The piezoelectric ceramic micro-positioning platform composed of piezoelectric actuators and flexible hinges has become an important part of the precision drive field due to its fast response speed and large output displacement. However, the hysteretic nonlinear characteristics of the piezoelectric ceramic material itself will significantly reduce the positioning accuracy of the piezoelectric ceramic micro-positioning platform. At present, scholars at home and abroad have carried out a lot of research on the modeling of piezoelectric hysteresis nonlinear characteristics to describe this characteristic more accurately, thus laying a solid foundation for the design of the controller of the piezoelectric ceramic micro-positioning...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/04G06N3/08
CPCG06N3/08G06F30/20G06N3/043
Inventor 周淼磊张晨于业伟张颖吴忠实
Owner JILIN UNIV
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