scholarly journals Modeling and Control of IPMC Actuators Based on LSSVM-NARX Paradigm

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 741 ◽  
Author(s):  
Liangsong Huang ◽  
Yu Hu ◽  
Yun Zhao ◽  
Yuxia Li
Keyword(s):  
Support Vector ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Metal Composites ◽  
Ionic Polymer Metal Composites ◽  
Modeling And Control ◽  
Ionic Polymer ◽  
Polymer Metal ◽  
And Control ◽  
Hysteresis Characteristics

Ionic polymer-metal composites are electrically driven intelligent composites that are readily exposed to bending deformations in the presence of external electric fields. Owing to their advantages, ionicpolymer-metal composites are promising candidates for actuators. However, ionicpolymer-metal composites exhibit strong nonlinear properties, especially hysteresis characteristics, resulting in severely reduced control accuracy. This study proposes an ionic polymer-metal composite platform and investigates its modeling and control. First, the hysteresis characteristics of the proposed Pt-electrode ionic polymer-metal composite are tested. Based on the hysteresis characteristics, ionic polymer-metal composites are modeled using the Prandtl-Ishlinskii model and the least squares support vector machine-nonlinear autoregressive model, respectively. Then, the ionic polymer-metal composite is driven by a random sinusoidal voltage, and the LSSVM-NARX model is established on the basis of the displacement data obtained. In addition, an artificial bee colony algorithm is proposed for accuracy optimization of the model parameters. Finally, an inverse controller based on the least squares support vector machine-nonlinear autoregressive model is proposed to compensate the hysteresis characteristics of the ionic polymer-metal composite. A hybrid PID feedback controller is developed by combining the inverse controller with PID feedback control, followed by simulation and testing of its actual position control on the ionic polymer-metal composite platform. The results show that the hybrid PID feedback control system can effectively eliminate the effects of the hysteresis characteristics on ionic polymer-metal composite control.

Biomimetic Applications of Ionic Polymer Metal Composites (IPMC) Actuators - A Critical Review

2014 ◽  
Vol 20 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Farid ◽  
Zhao Gang ◽  
Tran Linh Khuong ◽  
Zhuang Zhi Sun ◽  
Naveed Ur Rehman ◽  
...  
Keyword(s):  
Critical Review ◽  
Low Voltage ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Metal Composites ◽  
Ionic Polymer Metal Composites ◽  
Ionic Polymer ◽  
Design And Manufacturing ◽  
Polymer Metal ◽  
Biomedical Field

Biomimetic is the field of engineering in which biological creatures and their functions are investigated and are used as the basis for the design and manufacturing of machines. Ionic Polymer Metal Composite (IPMC) is a smart material which has demonstrated a meaningful bending and tip force after the application of a low voltage. It is light-weighted, flexible, easily actuated, multi-directional applicable and requires simple manufacturing. Resultantly, IPMC has attracted scientists and researchers to analyze it further and consider it for any industrial and biomimetic applications. Presently, the research on IPMC is bi-directional oriented. A few groups of researchers are busy to find out the causes for the weaknesses of the material and to find out any remedy for them. The second class of scientists is exploring new areas of applications where IPMC material can be used. Although, the application zone of IPMC is ranging from micropumps diaphragms to surgical holding devices, this paper provides an overview of the IPMC application in biomimetic and biomedical field.

Modeling Ionic Polymer-Metal Composites with Space-Time Adaptive Multimeshhp-FEM

2012 ◽  
Vol 11 (1) ◽  
pp. 249-270 ◽  
Author(s):  
David Pugal ◽  
Pavel Solin ◽  
Kwang J. Kim ◽  
Alvo Aabloo
Keyword(s):  
Coupled System ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
The Finite Element Method ◽  
Metal Composites ◽  
Ionic Polymer Metal Composites ◽  
Ionic Polymer ◽  
Qualitative And Quantitative ◽  
Polymer Metal ◽  
Adaptive Fem

AbstractWe are concerned with a model of ionic polymer-metal composite (IPMC) materials that consists of a coupled system of the Poisson and Nernst-Planck equations, discretized by means of the finite element method (FEM). We show that due to the transient character of the problem it is efficient to use adaptive algorithms that are capable of changing the mesh dynamically in time. We also show that due to large qualitative and quantitative differences between the two solution components, it is efficient to approximate them on different meshes using a novel adaptive multimeshhp-FEM. The study is accompanied with numerous computations and comparisons of the adaptive multimeshhp-FEM with several other adaptive FEM algorithms.

Fractional-order modeling and control of ionic polymer-metal composite actuator

2019 ◽  
Vol 28 (8) ◽  
pp. 084008 ◽  
Author(s):  
Aleksei Tepljakov ◽  
Veiko Vunder ◽  
Eduard Petlenkov ◽  
S Sunjai Nakshatharan ◽  
Andres Punning ◽  
...  
Keyword(s):  
Fractional Order ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Modeling And Control ◽  
Ionic Polymer ◽  
Composite Actuator ◽  
Polymer Metal ◽  
And Control

Integral multiple models online identifier applied to ionic polymer–metal composite actuator

2018 ◽  
Vol 29 (14) ◽  
pp. 2863-2873 ◽  
Author(s):  
Jakub Bernat ◽  
Jakub Kolota
Keyword(s):  
Smart Materials ◽  
Low Voltage ◽  
Feedback Gain ◽  
Multiple Models ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Metal Composites ◽  
Ionic Polymer Metal Composites ◽  
Ionic Polymer ◽  
Polymer Metal

Ionic polymer–metal composites are classified as a smart materials group, whose properties can be designed depending on the needs that arise. Ionic polymer–metal composites belong to the class of wet electroactive polymers. They are promising candidates actuator for various potential applications mainly due to their flexible, low voltage requirements, compact design, and lack of moving parts. However, being a widely used material in industry, ionic polymer–metal composite requires complex control methods due to its strongly nonlinear nature. An important prerequisite for an intelligent controller is the ability to adapt rapidly to any unknown operating environment. This article presents a novel approach to tuning multiple models of an online identifier by integral mapping. Through the extension of the estimation law of additional mapping between parameters and measurable signals, we significantly improve transient responses without increasing feedback gain. The authors measured the moisture content of ionic polymer–metal composite and consider in the experiment relationship between drying and varying of curvature output. The effectiveness of the proposed multiple models adaptive control strategy was verified in various experiments. The results of the study illustrated in the experiments show that adding new mapping improves not only the transients of controlled plant, but also increases the performance indexes of adaptive system.

From modeling to implementation of a method for restraining back relaxation in ionic polymer–metal composite soft actuators

2018 ◽  
Vol 29 (15) ◽  
pp. 3124-3135 ◽  
Author(s):  
Mohsen Annabestani ◽  
Nadia Naghavi ◽  
Mohammad Maymandi-Nejad
Keyword(s):  
Relaxation Effect ◽  
Practical Method ◽  
Specific Pattern ◽  
Driving Voltage ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Metal Composites ◽  
Ionic Polymer Metal Composites ◽  
Ionic Polymer ◽  
Polymer Metal

Ionic polymer–metal composites are an emerging kind of electroactive polymer actuators, which can bend in response to a relatively low driving voltage. However, to enhance the actuation performance of ionic polymer–metal composites, some of their drawbacks should be considered. One of the most important drawbacks is “back relaxation.” The so-called back relaxation effect means, when a step input voltage is applied to the ionic polymer–metal composite, the conventional bending displacement toward the anode is followed by an unwanted and slow back relaxation toward the cathode. Control-based methods for restraining the ionic polymer–metal composite back relaxation effect are feedback-based schemes which apply significant constraints to dominant applications of ionic polymer–metal composite actuators especially in biomedical applications. In this article, we present an entirely scientific-based mathematical modeling to achieve a practical method for restraining the back relaxation effect in Nafion-based ionic polymer–metal composites, relying on creating a specific pattern on Pt layers of the ionic polymer–metal composites and applying a local Gaussian disturbance to this patterned ionic polymer–metal composites.

A recurrent neural network–based model for predicting bending behavior of ionic polymer–metal composite actuators

2020 ◽  
Vol 31 (17) ◽  
pp. 1973-1985
Author(s):  
Hojat Zamyad ◽  
Nadia Naghavi ◽  
Reza Godaz ◽  
Reza Monsefi
Keyword(s):  
Smart Materials ◽  
Autoregressive Models ◽  
Metal Composite ◽  
Ionic Polymer Metal Composite ◽  
Ionic Polymer Metal Composites ◽  
Ionic Polymer ◽  
Practical Applications ◽  
Proposed Model ◽  
Polymer Metal ◽  
Application Potential

The high application potential of ionic polymer–metal composites has made the behavior identification of this group of smart materials an attractive area. So far, several models have been proposed to predict the bending of an ionic polymer–metal composite actuator, but these models have some weaknesses, the most important of them are the use of output data (in autoregressive models), high complexity to achieve a proper precision (in non-autoregressive models), and lack of compatibility with the behavioral nature of the material. In this article, we present a hybrid model of parallel non-autoregressive recurrent networks with internal memory cells to overcome existing weaknesses. The validation results on experimental data show that the proposed model has acceptable accuracy and flexibility. Moreover, simplicity and compatibility with the behavioral nature of the material promote using the proposed model in practical applications.

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