Prediction of the Actuation Property of Cu Ionic Polymer-Metal Composites Based on Backpropagation Neural Networks.

Liang Yang,Xining Zhang,Aifen Tian,Dongsheng Zhang

doi:10.1021/acsomega.9b03725

Abstract

Ionic polymer–metal composite (IPMC) actuators are one of the most prominent electroactive polymers with expected widespread use in the future. The IPMC bends in response to a small applied electric field as a result of the mobility of cations in the polymer network. This paper proposes a Levenberg–Marquardt algorithm backpropagation neural network (LMA–BPNN) prediction model applicable for Cu/Nafion-based ionic polymer–metal composites to predict the actuation property. The proposed approach takes the dimension ratio (DR) and stimulation voltage as the input layer, displacement and blocking force as the output layer, and trains the LMA–BPNN with the experimental data so as to obtain a mapping relationship between the input and the output and obtain the predicted values of displacement and blocking force. An IPMC actuating system is set up to generate a collection of the IPMC actuating data. Based on the input/output training data, the most suitable structure was found out for the BPNN model to represent the IPMC actuation behavior. After training and verification, a 2-9-3-1 BPNN structure for displacement and a 2-9-4-1 BPNN structure for blocking force indicate that the structure can provide a good reference value for the IPMC. The results showed that the BPNN model based on the LMA could predict the displacement and blocking force of the IPMC. Therefore, this model can become an effective solution for IPMC control applications.

Highlights

Ionic polymer−metal composites (IPMCs) are an important class of electroactive polymers consisting of a thin layer of ionic polymer film and two layers of metal electrodes.[1−3] As shown in Figure 1, the membrane contains anions (SO3−) connected to the backbone, cations that can freely travel within the membrane, and water molecules.[4,5]
The Cu content is 85.47% from energydispersive spectroscopy (EDS) data, and it further reveals that Cu particles have been deposited well on the surface of membranes, which is beneficial to the actuation performance of IPMCs
The presence of Ag is due to the fact that Ag+ is not completely replaced during the electroless plating process and a portion remains on the surface.[9]

Summary

Introduction

Ionic polymer−metal composites (IPMCs) are an important class of electroactive polymers consisting of a thin layer of ionic polymer film and two layers of metal electrodes.[1−3] As shown in Figure 1, the membrane contains anions (SO3−) connected to the backbone, cations that can freely travel within the membrane, and water molecules.[4,5] At applied voltage, the transportation of hydrated cations and water molecules to the cathode leads to the expansion of the membrane on one side of the cathode, which leads to the bending motion of the IPMC sample[6] (Figure 1). Ionic polymer−metal composites (IPMCs) are an important class of electroactive polymers consisting of a thin layer of ionic polymer film and two layers of metal electrodes.[1−3] the membrane contains anions (SO3−) connected to the backbone, cations that can freely travel within the membrane, and water molecules.[4,5] At applied voltage, the transportation of hydrated cations and water molecules to the cathode leads to the expansion of the membrane on one side of the cathode, which leads to the bending motion of the IPMC sample[6] (Figure 1). It is important to establish a precise IPMC model to study its bending characteristics and apply it to the system control of the executive mechanism. Caponetto[15] developed an improved electromechanical gray box model with

Objectives

Results

Conclusion