Advanced Trajectory Control for Piezoelectric Actuators Based on Robust Control Combined with Artificial Neural Networks

In applications where high precision in micro- and nanopositioning is required, piezoelectric actuators (PEA) are an optimal micromechatronic choice. However, the accuracy of these devices affected by a natural phenomenon called “hysteresis” that even increases instability system. This anomaly can be counteracted through material re-shape or design control strategy. Through this research, novel has been developed; structure contemplates artificial neural network (ANN) feedforward to contract non-linearities robust close-loop compensator reduce unmodelled dynamics, uncertainties perturbations. The proposed scheme was embedded dSpace platform with Thorlabs PEA; parameters were tuned online specific metrics. outcomes compared conventional proportional-integral-derivative (PID) controller terms signal tracking performance. experimental gathered results showed advanced strategy had superior chattering reduction.