TAILIEUCHUNG - Dynamic model identification of IPMC actuator using fuzzy NARX model optimized by MPSO
In this paper, a novel inverse dynamic fuzzy NARX model is used for modeling and identifying the IPMC-based actuator’s inverse dynamic model. The contact force variation and highly nonlinear cross effect of the IPMC-based actuator are thoroughly modeled based on the inverse fuzzy NARX model-based identification process using experiment input-output training data. | SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 17, 2014 Dynamic model identification of IPMC actuator using fuzzy NARX model optimized by MPSO • Ho Pham Huy Anh FEEE, University of Technology, VNU-HCM • Nguyen Thanh Nam DCSELAB, University of Technology, VNU-HCM (Manuscript Received on December 11th, 2013; Manuscript Revised September 12th, 2014) ABSTRACT: In this paper, a novel inverse dynamic fuzzy NARX model is used for modeling and identifying the IPMC-based actuator’s inverse dynamic model. The contact force variation and highly nonlinear cross effect of the IPMC-based actuator are thoroughly modeled based on the inverse fuzzy NARX model-based identification process using experiment input-output training data. This paper proposes the novel use of a modified particle swarm optimization (MPSO) to generate the inverse fuzzy NARX (IFN) model for a highly nonlinear IPMC actuator system. The results show that the novel inverse dynamic fuzzy NARX model trained by MPSO algorithm yields outstanding performance and perfect accuracy. Keywords: IPMC-based actuator, modified particle swarm optimization (MPSO), fuzzy NARX model, inverse dynamic identification 1. INTRODUCTION The nonlinear IPMC-based actuator is belonged characteristics of Ionic Polymer Metal Composite to highly nonlinear systems where perfect electromechanical properties of IPMC [5]. An knowledge of their parameters is unattainable by empirical control model by Kanno et al. was conventional modeling techniques because of the developed and optimized with curve-fit routines time-varying inertia, external force variation and based on open-loop step responses with three other nonlinear uncertainties. To guarantee a good stages, ., electrical, stress generation, and position tracking performance, lots of researches mechanical stages [6–8]. Feedback compensators have been carried on. During the last decade, were designed using a similar model in a Sadeghipour et al., Shahinpoor et al., .
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