Duhem-based piezoelectric actuator neural network parameter identification method

A piezoelectric actuator and neural network technology, applied in the direction of biological neural network models, can solve the problems of difficulty in improving accuracy and limiting applications, and achieve the effects of strong applicability, improved identification speed and identification accuracy, and easy engineering implementation

Inactive Publication Date: 2017-05-17
HENAN POLYTECHNIC UNIV
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Problems solved by technology

However, these methods are either easy to fall into local optimum, or the accuracy is difficult to improve, which limits its application in the engineering field

Method used

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  • Duhem-based piezoelectric actuator neural network parameter identification method
  • Duhem-based piezoelectric actuator neural network parameter identification method
  • Duhem-based piezoelectric actuator neural network parameter identification method

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Embodiment Construction

[0028] The technical solutions of the present invention will be described in further detail below through specific implementation methods.

[0029] Such as figure 1 Shown, a kind of neural network parameter identification method of the piezoelectric actuator based on Duhem model is characterized in that, comprises the following steps:

[0030] Step 1, deduce its discretization parameter model from the differential equation of Duhem model.

[0031] The Duhem model differential equation is

[0032]

[0033] Among them, represents the hysteresis output displacement, represents the hysteresis input voltage, represents the hysteresis state variable, and the four constants represent the shape control parameters of the hysteresis curve.

[0034] Discretizing the Duhem model differential equation according to the sampling time T, the following discretization parameter model can be obtained:

[0035]

[0036] Step 2, constructing a neural network according to the interconnecti...

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Abstract

The invention provides a Duhem-based piezoelectric actuator neural network parameter identification method. The method comprises the following steps: 1, a discrete parameter model is deduced by a Duhem model differential equation; 2, according to an interconnection relationship between the discrete parameter model and parameters, a neural network is built; 3, a static test principle is used to acquire an initial input and output data set for training of the neural network; 4, according to a Levenberg-Marquardt algorithm, the initial input and output data set and a preset training target, the neural network is trained, and according to a training result, a weight-adjustable value of the discrete parameter model is calculated; and 5, according to the discrete parameter model and the weight-adjustable value, values of the parameters are calculated.

Description

technical field [0001] The invention relates to a parameter identification method of a piezoelectric actuator, in particular to a Duhem-based neural network parameter identification method of a piezoelectric actuator. Background technique [0002] Piezoelectric actuators are ideal components used in the field of micro-nano drive and positioning, and have the advantages of high positioning accuracy, fast response speed, and large load capacity. However, the piezoelectric material itself has nonlinear characteristics such as hysteresis and creep, which significantly reduces the positioning repeatability and tracking accuracy of the micro-displacement mechanism, which brings certain difficulties to the application of piezoelectric actuators. In order to overcome this problem, many scientific research institutions and researchers have carried out modeling and parameter identification research on the nonlinear characteristics of piezoelectric hysteresis in order to describe the h...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02
CPCG06N3/02
Inventor 王耿陈国强王海涛王莹黄增武王帅旗
Owner HENAN POLYTECHNIC UNIV
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