Abstract

n this paper we develop an algorithm for adaptive compensation class of methods. Literature offers a wide control of unconventional actuators based on Prandtl-Ishlinskii models and Lyapunov design. The chosen family of models is general enough to capture the strongly variable shapes of the hysteresis exhibited by some electro-active materials and has an inverse model that can be computed analytically. The approach proposed in this paper adapts the parameters of the model with a learning law based on the minimization of the tracking error, has the useful property of allowing the analytical and handles the parameters having a nonlinear influence on the output of the model by means of linearization. An outer position loop is then introduced to compensate the residual compensation error and further improve the tracking performance. The advantages and limitations of the approach are discussed and confirmed by experiments on a mechatronic position actuator based on magnetic shape memory alloys.

Autore Pugliese

• Naso David , Turchiano Biagio

Tutti gli autori

• Riccardi, L. , Naso, D. , Turchiano, B. , Janocha, H.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2011

ISSN

Non Disponibile

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

6

Ultimo Aggiornamento Citazioni

2017-04-21 03:20:17

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile