Improved Mode-Free Adaptive Control for Piezoelectric Micro-Positioning Platform

Piezoelectric micro-positioning (PMP) platforms have been widely applied due to their fast response and high resolution. However, the strong nonlinearities in the PMP plat-form seriously degrade the positioning accuracy. In this study, an improved model-free adaptive control (MFAC) method is proposed to solve the nonlinearities in the PMP platform. In the improved MFAC, the classical dynamic linearization (DL) is extended to a neural network (NN)-based DL. That is, the unmodeled dynamics in the DL is approximated by aNN. Based on the NN-based DL, the performance of the improved MFAC is better than the traditional MFAC. To verify the effectiveness of the proposed method, experiments are conducted on the PMP platform. Experimental results demonstrate that the proposed method can achieve the satisfactory control performance.