DocumentCode :
558846
Title :
Identification of ionic polymer metal composite actuator employing fuzzy NARX model and Particle Swam Optimization
Author :
Nam Doan Ngoc Chi ; Truong Dinh Quang ; Jong Il Yoon ; Kyoung Kwan Ahn
Author_Institution :
Grad. Sch. of Mech. & Automotive Eng., Univ. of Ulsan, Ulsan, South Korea
fYear :
2011
fDate :
26-29 Oct. 2011
Firstpage :
1857
Lastpage :
1861
Abstract :
An ionic polymer metal composite (IPMC) actuator is an Electro-Active Polymer (EAP) that bends in response to a small applied electrical field as a result of mobility of cations in the polymer network. This paper proposes a dynamic fuzzy Nonlinear Auto Regressive Exogenous (NARX) model for modeling and identifying the nonlinear behavior of on type IPMC actuator. Firstly, a set of open loop input voltage signals were applied to the IPMC in order to investigate the IPMC bending actuation. Consequently, a proper fuzzy NARX model was constructed and an identification scheme based on Particle Swam Optimization (PSO) algorithm was developed. Validation results proved the ability of proposed scheme to capture the bending behaviors of IPMC actuator.
Keywords :
actuators; autoregressive processes; fuzzy set theory; metals; particle swarm optimisation; polymers; IPMC bending actuation; fuzzy NARX model; ionic polymer metal composite actuator; nonlinear autoregressive exogenous model; open loop input voltage signal; particle swam optimization; polymer network; Actuators; Adaptation models; Chirp; Legged locomotion; Mathematical model; Polymers; Predictive models; IPMC; Nonlinear Auto Regressive Exogenous model; Particle Swam Optimization; fuzzy; identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems (ICCAS), 2011 11th International Conference on
Conference_Location :
Gyeonggi-do
ISSN :
2093-7121
Print_ISBN :
978-1-4577-0835-0
Type :
conf
Filename :
6106180
Link To Document :
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