Design and experimental validation of a piezoelectric actuator tracking control based on fuzzy logic and neural compensation

This work proposes two control feedback-feedforward algorithms, based on fuzzy logic in combination with neural networks, aimed at reducing the tracking error and improving actuation signal of piezoelectric actuators. These are frequently used devices a wide range applications due to their high precision micro- nanopositioning combined mechanical stiffness. Nevertheless, hysteresis is one main phenomenon that degrades performance these actuators operations. The proposed schemes were tested experimentally commercial actuator. They implemented dSPACE 1104 device, which was for generation acquisition purposes. compared conventional structures proportional-integral-derivative feedback configuration. Experimental results show advantages controllers, since they capable significant magnitude orders.