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Displacement Control Method of Magnetically Controlled Shape Memory Alloy Actuator

A memory alloy, displacement control technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problems of unknown system parameters, complex hysteresis dynamic characteristics of magnetic control shape memory alloy actuators, and restricted application.

Active Publication Date: 2021-08-20
JILIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the hysteretic nonlinearity inside the magnetic control shape memory alloy material seriously restricts its application in various fields.
In order to solve the problem of complex hysteresis and nonlinearity in the displacement of magnetically controlled shape memory alloy actuators, and realize the micronano-level precision positioning control of magnetically controlled shape memory alloy actuators, it is necessary to propose more effective control strategies and design controllers with excellent performance
[0004] Magnetically controlled shape memory alloy actuators have the characteristics of complex hysteresis dynamic characteristics and unknown system parameters, so traditional control methods are difficult to achieve satisfactory control effects

Method used

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  • Displacement Control Method of Magnetically Controlled Shape Memory Alloy Actuator

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Embodiment Construction

[0050]A method for controlling the displacement of a magnetically controlled shape memory alloy actuator based on neural network iterative learning control provided by the present invention is characterized in that it comprises the following steps:

[0051] Step 1: Establish a Volterra series model that can describe the rate-dependent hysteresis nonlinearity of the magnetically controlled shape memory alloy actuator, and use the neural network to construct the kernel function of the Volterra series;

[0052] The expression of the Volterra series model is:

[0053]

[0054] Among them, k=0,1,...,N-1 is the discrete time, N is the expected time length and is a positive integer, n is the order of the model, p is the number of iterations, u p (k) and is the input and output values ​​of the model at the pth iteration, h n (κ 1 ,...,κ n ) and K is the nth order kernel function and memory length of the model, κ n is the memory delay corresponding to the nth item.

[0055] C...

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Abstract

The invention discloses a displacement control method of a magnetically controlled shape memory alloy actuator, which belongs to the field of intelligent material and its mechanism modeling and control. The purpose of the present invention is to combine the neural network with the iterative learning control, design the iterative learning controller based on the neural network, and provide the magnetically controlled shape memory alloy actuator of the system convergence condition when the initial state of the system changes within a bounded range Displacement control method. The steps of the invention are: establishing a Volterra series model that can describe the rate-dependent hysteresis nonlinearity of the magnetically controlled shape memory alloy actuator, and utilizing a neural network to construct a kernel function of the Volterra series; adopting a neural network to fit an iterative learning controller, and giving The convergence condition of the system when the initial state of the system changes within a bounded range. The invention not only relaxes the applicable conditions of the iterative learning control, but is more in line with the actual application environment, improves the robustness of the iterative learning control, and improves the control quality.

Description

technical field [0001] The invention belongs to the field of intelligent material and its mechanism modeling and control. Background technique [0002] Since the 1990s, with the vigorous development of the precision manufacturing industry, the traditional machining and manufacturing methods can no longer meet the needs of the rapid development of modern industry, and people have put forward new requirements for high-precision, high-resolution positioning technology. Actuators with emerging smart materials such as piezoelectric ceramics, shape memory alloys, and giant magnetostrictive materials as core devices have become a research field in the field of high-precision manufacturing in various countries in recent years because of their micro-nano precision positioning capabilities. hotspots. [0003] The magnetically controlled shape memory alloy actuator is a high-precision micro-positioning mechanism that uses the magnetic shape memory effect of the magnetically controlled...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/027G05B13/042
Inventor 周淼磊于业伟徐瑞张晨高巍韩志武
Owner JILIN UNIV
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