Intelligent vibration control of micro-cantilever beam in MEMS

Abstract

Considerable attention has been devoted recently to vibration control using intelligent materials as sensor/actuator. An intelligent control technique using a neural network is proposed for vibration control of micro-cantilever beam with bonded piezoelectric sensor and actuator. Structure modal characteristic analysis is done to determine the optimal configuration of piezoelectric sensor and actuator. With the piezoelectric elements are surface-bonded near the same position to the flxed end of micro-cantilever beam, an optimal controller, linear quadratic Gaussian (LQG), and an intelligent strategy based on neural network are investigated. Finally, the simulation results are given to demonstrate the effectiveness of the control method in this paper, neural network scheme has strong robustness to Gaussian disturbance compared with the LQG control method, Moreover, it is shown that vibration of micro-cantilever beam in MEMS can be significantly suppressed by the proposed neural network strategy.

Gas Adsorption Response of Piezoelectrically Driven Microcantilever Beam Gas Sensors: Analytical, Numerical, and Experimental Characterizations

“…Various strategies to address the nonlinearity and noise in dynamically actuated PD-MCs have been attempted, with particular emphasis on the development of mathematical response process models for nonlinearity compensation [ 38 , 39 , 40 , 41 ] and microcantilever non-linear vibration control [ 42 , 43 ]. However, they all rely on the determination of corrective system parameters during calibration, which are kept constant over time.…”

Modeling Nonlinear Dynamics of Functionalization Layers: Enhancing Gas Sensor Sensitivity for Piezoelectrically Driven Microcantilever

“…Several methodologies have been put forward to tackle the previously described response phenomenon accompanying the issue of nonlinearities . These are comprised of creating mathematical models of the response functions by compensating for nonlinearities − and nonlinear vibration control. ,− However, these methods rely on theoretical and analytical models that attribute the change in resonance frequency to damping from the mass adsorbed and do not account for the functionalization layer’s adsorption-induced variations in elastic properties.…”