Title
Modeling Of Conductive Shape Memory Polymer Nanocomposites Based Structure From A Control Perspective
Abstract
Shape memory polymers (SMPs) can recover their original shape under external stimulus such as light, heat, pH, humidity, and electric power. However, the applications of SMPs are limited by the number of shapes they can memorize and whether or not these shapes can be precisely and repeatedly controlled. Although a vision based PID controller has been shown by the authors to be capable of controlling the deflection angle of a SMP structure, the repeatability and precision are still low. In order to enhance the robustness and repeatability of the SMP shape control system, in this paper, the macro-scale behavior model of the SMP structure from the control perspective is proposed and the unknown parameters are identified using real-time vision, temperature, and resistance signals. Copyright © 2013 by ASME.
Publication Date
1-1-2013
Publication Title
ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2013
Volume
1
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1115/SMASIS2013-3129
Copyright Status
Unknown
Socpus ID
84896385902 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84896385902
STARS Citation
Shen, He; Xu, Yunjun; Liang, Fei; Gou, Jihua; and Mabbott, Bob, "Modeling Of Conductive Shape Memory Polymer Nanocomposites Based Structure From A Control Perspective" (2013). Scopus Export 2010-2014. 7649.
https://stars.library.ucf.edu/scopus2010/7649