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A Control-Oriented and Physics-Based Model for Ionic Polymer--Metal Composite Actuators
Abstract
Ionic polymer--metal composite (IPMC) actuators have promising applications in biomimetic robotics, biomedical devices, and micro/nanomanipulation. In this paper, a physics-based model is developed for IPMC actuators, which is amenable to model reduction and control design. The model is represented as an infinite-dimensional transfer function relating the bending displacement to the applied voltage. It is obtained by exactly solving the governing partial differential equation in the Laplace domain for the actuation dynamics, where the effect of the distributed surface resistance is incorporated. The model is expressed in terms of fundamental material parameters and actuator dimensions, and is thus, geometrically scalable. To illustrate the utility of the model in controller design, an$H_{\infty}$controller is designed based on the reduced model and applied to tracking control. Experimental results are presented to validate the proposed model and its effectiveness in real-time control design.
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Cited by
Carrico, J. D., Tyler, T., & Leang, K. K. (2017) · International Journal of Smart and Nano Materials · doi:10.1080/19475411.2018.1438534 · Cited by 78
Metadata
- Authors
- Chen, Z., & Tan, X.
- Venue
- IEEE/ASME Transactions on Mechatronics
- Published
- 2008-10
- Volume
- 13
- Issue
- 5
- Pages
- 519-529
- ISSN
- 1083-4435 (ISSN-L)
- 1941-014X
- OpenAlex
- W2041508840
- Cited by
- 230
- References
- 0
- FWCI
- 10.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Control-Oriented and Physics-Based Model for Ionic Polymer--Metal Composite Actuators. https://app.cochat.ai/papers/10.1109/tmech.2008.920021
- The paper
- Chen, Z., & Tan, X. (2008). A Control-Oriented and Physics-Based Model for Ionic Polymer--Metal Composite Actuators. IEEE/ASME Transactions on Mechatronics. https://doi.org/10.1109/tmech.2008.920021
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.