This paper proposes a neuro-network-based method for model reduction that combines the generalized Hebbian algorithm (GHA) with the Galerkin procedure to perform the dynamic simulation and analysis of nonlinear microelectromechanical systems (MEMS). An unsupervised neural network is adopted to find the principal eigenvectors of a correlation matrix of snapshots. It has been shown that the extensive computer results of the principal component analysis using the neural network of GHA can extract an empirical basis from numerical or experimental data, which can be used to convert the original system into a lumped low-order macromodel. The macromodel can be employed to carry out the dynamic simulation of the original system resulting in a dramatic reduction of computation time while not losing flexibility and accuracy. Compared with other existing model reduction methods for the dynamic simulation of MEMS, the present method does not need to compute the input correlation matrix in advance. It needs only to find very few required basis functions, which can be learned directly from the input data, and this means that the method possesses potential advantages when the measured data are large. The method is evaluated to simulate the pull-in dynamics of a doubly-clamped microbeam subjected to different input voltage spectra of electrostatic actuation. The efficiency and the flexibility of the proposed method are examined by comparing the results with those of the fully meshed finite-difference method.
Two improved Elman network models, output-input feedback (OIF) and output-hidden feedback (OHF), are proposed based on the modified Elman network. A recurrent backpropagation control (RBPC) network model is developed by using the OIF Elman network as a passageway of the error back-Propagation. The stability of the improved Elman
In this paper, we develop a novel method for the macromodel generation for the dynamic simulation and analysis of a structurally complex MEMS device, by making use of proper orthogonal decomposition (POD), also known as the Karhunen–Loève decomposition and classical component mode synthesis. The complex microelectromechanical systems (MEMS) device is divided into interconnected components and each of these components is treated separately using POD to extract its proper orthogonal modes (POMs) and their corresponding proper orthogonal values. The separate component responses are then expressed in generalized coordinates that are defined by the POMs. The requirements of the displacement and force compatibility at the interface of components serve as constraint equations among the component coordinates, and are used to construct a transformation relating the component coordinates to system coordinates. This transformation is used to formulate the low-order macromodel to determine system dynamic responses. Numerical results obtained from the simulation of pull-in dynamics of a non-uniform microbeam MEMS device subjected to electrostatic actuation force with squeezed gas-film damping effect show that the macromodel generated this way can dramatically reduce the computation time while capturing the device behaviour faithfully.
A mechanical model of a longitudinal oscillation ultrasonic motor and a method of
analyzing its frequency–temperature characteristics are presented. The sticking
and slipping between the stator and the rotor in the intermittent contact region
are analyzed theoretically. An analytical expression for the motor’s driving force
that undergoes continuous changes is given. The behaviors of the ultrasonic motor
(USM), including the revolving speed of the rotor, the output kinetic energy
from the rotor to the other object, the input kinetic energy from the
beam tip, and the efficiency of the energy transformation, are discussed.
The effects of the initial compressive force, driving frequency, load, and
the moment of inertia of the motor on the behavior of the motor are
examined. In the study of the temperature effect, the course of the vibration of
the piezoelectric element inside the USM is expounded, the main factors
affecting the frequency–temperature characteristics are analyzed, and
the analytical expression for the change of the resonance frequency with
respect to the temperature is given. Numerical simulations show that the
results obtained in this paper agree with reported experimental results.
One of the issues in VCM rotary actuation in hard disk drives (HDDs) is the excessive sensitivity of the system to the skew angle. The rotation of the VCM from the inner diameter (ID) to the outer diameter (OD) of the disk results in an angle of skew between the read/write head and the track. The difference in skew angle, between the ID to the OD can be as large as 25 to 30 degrees in conventional 3.5″ and 2.5″ HDDs. A large skew angle affects the slider’s flying performance and off-track capability, causing an increase in side reading and writing, and thus reduces the achievable recording density. Large skewed actuation also complicates the position error signal calibration process in the hard disk drive servo loop. This paper presents a 4 link mechanism which can be designed to achieve near zero skew actuation in hard disk drives. The profiles of the arm, suspension, and links can be designed and optimized such that the skew angle is close to zero while the VCM actuator rotates from the ID to the OD. Study shows that the 4-link mechanism does not degrade the resonance performance along the tracking direction compared to a conventional actuator.
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