Bibliografie

(eng): The paper deals with a modelling and identification of a class of piezoelectric actuators intended for mechatronic and bio-inspired robotic applications. Specifically, a commercial piezoelectric bender PL140 from Physik Instrumente Co. is used. Considering catalogue/datasheet parameters, a physical model of PL140 is derived using Euler-Bernoulli beam theory. This model serves as a substitution of reality to generate proper data without potentially damaging the real actuator. However, due to its complex structure, this model cannot be used for control design. For this purpose, a Hammerstein model is proposed. It consists of a static nonlinear part describing the hysteresis and a dynamic linear part that is represented by the auto-regressive model with exogenous input (ARX model). The nonlinear part of the Hammerstein model is identified by a neural network. The Bayesian approach is used for the estimation of the ARX model parameters.