Chaotic dynamics of piezoelectric mems based on maximal Lyapunov exponent and Smaller Alignment Index computations

TL;DR

This paper investigates the chaotic behavior of piezoelectric MEMS devices using numerical chaos indicators like Lyapunov exponents and SALI, revealing how system parameters influence complex dynamics.

Contribution

It introduces a comprehensive analysis of piezoelectric MEMS dynamics using multiple chaos detection methods, including the SALI, for the first time in this context.

Findings

Chaotic dynamics increase as the system's natural frequency decreases.

Damping and external forces significantly affect the system's chaotic behavior.

SALI effectively characterizes chaos in piezoelectric MEMS.

Abstract

We characterize the dynamical states of a piezoelectric microelectromechanical system (MEMS) using several numerical quantifers including the maximal Lyapunov exponent, the Poincare Surface of Section and a chaos detection method called the Smaller Alignment Index (SALI). The analysis makes use of the MEMS Hamiltonian. We start our study by considering the case of a conservative piezoelectric MEMS model and describe the behavior of some representative phase space orbits of the system. We show that the dynamics of the piezoelectric MEMS becomes considerably more complex as the natural frequency of the system's mechanical part decreases.This refers to the reduction of the stiffness of the piezoelectric transducer. Then, taking into account the effects of damping and time dependent forces on the piezoelectric MEMS, we derive the corresponding non-autonomous Hamiltonian and investigate its dynamical behavior. We find that the non-conservative system exhibits a rich dynamics, which is strongly influenced by the values of the parameters that govern the piezoelectric MEMS energy gain and loss. Our results provide further evidences of the ability of the SALI to efficiently characterize the chaoticity of dynamical systems.