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微机电系统陀螺仪的建模、仿真与动态滑模控制

Modelling, Simulation and Dynamic Sliding Mode Control of a MEMS Gyroscope.

作者信息

Fang Yunmei, Fu Wen, An Cuicui, Yuan Zhuli, Fei Juntao

机构信息

College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China.

Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology, Changzhou 213022, China.

出版信息

Micromachines (Basel). 2021 Feb 13;12(2):190. doi: 10.3390/mi12020190.

DOI:10.3390/mi12020190
PMID:33668467
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7918911/
Abstract

An adaptive dynamic sliding mode control via a backstepping approach for a microelectro mechanical system (MEMS) vibratory z-axis gyroscope is presented in this paper. The time derivative of the control input of the dynamic sliding mode controller (DSMC) is treated as a new control variable for the augmented system which is composed of the original system and the integrator. This DSMC can transfer discontinuous terms to the first-order derivative of the control input, and effectively reduce the chattering. An adaptive dynamic sliding mode controller with the method of backstepping is derived to real-time estimate the angular velocity and the damping and stiffness coefficients and asymptotical stability of the designed systems can be guaranteed. Simulation examples are investigated to demonstrate the satisfactory performance of the proposed adaptive backstepping sliding mode control.

摘要

本文提出了一种基于反步法的自适应动态滑模控制方法,用于微机电系统(MEMS)振动z轴陀螺仪。动态滑模控制器(DSMC)的控制输入的时间导数被视为由原系统和积分器组成的增广系统的一个新的控制变量。该DSMC可以将不连续项转换为控制输入的一阶导数,并有效减少抖振。推导了一种基于反步法的自适应动态滑模控制器,用于实时估计角速度以及阻尼和刚度系数,并保证所设计系统的渐近稳定性。通过仿真算例验证了所提出的自适应反步滑模控制具有良好的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eff6/7918911/dae1e64d9e6c/micromachines-12-00190-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eff6/7918911/dae1e64d9e6c/micromachines-12-00190-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eff6/7918911/dae1e64d9e6c/micromachines-12-00190-g005.jpg

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本文引用的文献

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Fuzzy Multiple Hidden Layer Recurrent Neural Control of Nonlinear System Using Terminal Sliding-Mode Controller.基于终端滑模控制器的模糊多层递归神经网络非线性系统控制。
IEEE Trans Cybern. 2022 Sep;52(9):9519-9534. doi: 10.1109/TCYB.2021.3052234. Epub 2022 Aug 18.
2
Bifurcation Analysis of a Micro-Machined Gyroscope with Nonlinear Stiffness and Electrostatic Forces.具有非线性刚度和静电力的微机械陀螺仪的分岔分析
Micromachines (Basel). 2021 Jan 22;12(2):107. doi: 10.3390/mi12020107.
3
Composite Neural Learning-Based Nonsingular Terminal Sliding Mode Control of MEMS Gyroscopes.
通过内部和封装应力释放实现MEMS陀螺仪的零速率漂移降低
Micromachines (Basel). 2021 Oct 29;12(11):1329. doi: 10.3390/mi12111329.
基于复合神经学习的微机电系统陀螺仪非奇异终端滑模控制
IEEE Trans Neural Netw Learn Syst. 2020 Apr;31(4):1375-1386. doi: 10.1109/TNNLS.2019.2919931. Epub 2019 Jun 26.
4
Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.基于模糊补偿器的MEMS三轴陀螺仪鲁棒自适应控制
IEEE Trans Syst Man Cybern B Cybern. 2012 Dec;42(6):1599-607. doi: 10.1109/TSMCB.2012.2196039. Epub 2012 May 3.
5
Sliding mode control of a simulated MEMS gyroscope.模拟微机电系统陀螺仪的滑模控制
ISA Trans. 2006 Jan;45(1):99-108. doi: 10.1016/s0019-0578(07)60069-x.