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首页> 外文期刊>ScientificWorldJournal >Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model
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Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

机译：基于Krasnosel'skii-Pokrovskii模型的磁形记忆合金执行器磁形记忆合金执行器的滞后模型

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摘要

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.
机译：作为一种新型智能材料，磁形记忆合金（MSMA）在致动器制造中具有良好的性能。与传统的执行器相比，MSMA执行器具有快速响应和大变形的优点;然而，MSMA致动器的滞后非线性限制了其进一步提高控制精度。本文使用改进的Krasnosel'skii-pokrovskii（KP）模型来建立MSMA执行器的滞后模型。为了识别KP运算符的加权参数，本文提出了一种改进的梯度校正算法和可变步长递归最小二乘估计算法。为了证明所提出的建模方法的有效性，分别进行了仿真实验，研究了具有改进的梯度校正算法和可变步长递归最小二乘估计算法的模拟。鉴定算法的仿真结果表明，本文中所提出的建模方法可以为MSMA执行器建立有效和准确的滞后模型，为提高MSMA执行器的控制精度提供了基础。

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