Identification of IPMC nonlinear model via single and multi-objective optimization algorithms

Riccardo Caponetto; Salvatore Graziani; Fulvio Pappalardo; Francesca Sapuppo

doi:10.1016/j.isatra.2013.11.012

Identification of IPMC nonlinear model via single and multi-objective optimization algorithms

ISA Trans. 2014 Mar;53(2):481-8. doi: 10.1016/j.isatra.2013.11.012. Epub 2013 Dec 14.

Authors

Riccardo Caponetto¹, Salvatore Graziani², Fulvio Pappalardo², Francesca Sapuppo²

Affiliations

¹ Dipartimento di Ingegneria Elettrica Elettronica ed Informatica, Università degli Studi di Catania, V.le A. Doria 6, 95125 Catania, Italy. Electronic address: Riccardo.Caponetto@dieei.unict.it.
² Dipartimento di Ingegneria Elettrica Elettronica ed Informatica, Università degli Studi di Catania, V.le A. Doria 6, 95125 Catania, Italy.

PMID: 24342273
DOI: 10.1016/j.isatra.2013.11.012

Abstract

Ionic Polymer-Metal Composites (IPMCs) are electro-active polymers transforming mechanical forces into electric signals and vice versa. This paper proposes an improved electro-mechanical grey-box model for IPMC membrane working as actuator. In particular the IPMC nonlinearity has been characterized through experimentation and included within the electric model. Moreover identification of the model parameters has been performed via optimization algorithms using both single- and multi-objective formulation. Minimization was attained via the Nelder-Mead simplex and the Genetic Algorithms considering as cost functions the error between the experimental and modeled absorbed current and the error between experimental and modeled displacement. The obtained results for the different formulations have been then compared.

Keywords: Actuator model; Electro-active polymer; Genetic Algorithms; Model identification; Simplex method.