Identification of the bouc-wen hysteresis model for piezoelectric actuated microano electromechanical system

摘要

Piezoelectric actuator (PEA) has been extensively applied in the area of microano electromechanical systems (MEMS/NEMS). To describe and consequently compensate for its inherent hysteresis nonlinearities, the Bouc-Wen model has been widely employed. However, its identification constitutes a challenging problem due to its nonlinear and nondifferentiable nature. This paper presents a numerical optimization scheme for its parameter estimation based on a chaotic self-adaptive differential evolution algorithm (CSaDEA). The proposed CSaDEA offers the advantage of incorporating a relatively simple but efficient form of self-adaptive mutation and crossover operations with a constraint handling technique. Comparative studies with the schemes based on general DEA (GDEA) and a modified particle swam optimization algorithm (MPSOA) are carried out to assess the performances of the proposed method. The numerical simulation results demonstrate that the identification could be well achieved by the proposed method even if the simulated data are corrupted by noise, and the proposed method outperforms than the GDEA and the MPSOA in terms of both solution accuracy and computational efficiency.