硬激励下MEMS圆板参数共振的电压响应

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS

Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9059

Julio Beatriz, D. Caruntu

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引用次数: 0

摘要

本文研究了硬激励下静电驱动微机电(MEMS)圆板参数共振的电压响应。采用多尺度法(MMS)和降阶模型法(ROM)两种振动模态对MEMS圆板的电压幅值响应进行了预测。采用auto07p -一个连续分岔软件包对ROM进行求解。本文使用的MMS在静电力中有一项被认为是有效的。这就是MMS用来模拟硬激发的方法。在较低的振幅和较低的电压下，MMS显示出与ROM相似的结果。MMS和ROM两种方法之间的差异在所有电压下的高幅值上都是显著的，在较大电压下的所有幅值上的差异都是显著的。不同参数(如失谐频率和阻尼)对电压响应的影响有显著差异。ROM AUTO 07p使用ROM时间响应进行校准，其中使用Matlab中的求解器ode15s对ROM进行求解。

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Voltage Response of Parametric Resonance of MEMS Circular Plates Under Hard Excitations

This work deals with the voltage response of parametric resonance of electrostatically actuated microelectromechanical (MEMS) circular plates under hard excitations. Method of Multiple Scales (MMS) and Reduced Order Model (ROM) method using two modes of vibration are used to predict the voltage-amplitude response of the MEMS circular plates. ROM is solved using AUTO 07p, a software package for continuation and bifurcation. MMS used in this paper has one term in the electrostatic force being considered significant. This is the way MMS is used to model hard excitations. MMS shows results similar to those of ROM at lower amplitudes and lower voltages. The differences between the two methods, MMS and ROM, are significant in high amplitudes for all voltages, and the differences are significant in all amplitudes for larger voltages. Significant differences can be noted in the effect of different parameters such as the detuning frequency and damping on the voltage response. ROM AUTO 07p is calibrated using ROM time responses in which the ROM is solved using the solver ode15s in Matlab.

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来源期刊

Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.40

自引率

66.70%

发文量

期刊介绍： This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.