Behavior Identification of IPMC Actuators Using Laguerre-MLP Network With Consideration of Ambient Temperature and Humidity Effects on Their Performance

In this paper, we propose a model for ionic polymer metal composite (IPMC) actuators that its superiority over the other models is its capability to make a confident prediction about the bending displacement of all points along the IPMC strip in large bending displacements, without using previous data of the output and also with consideration of the effects of the ambient conditions on its performance. To achieve this aim, we used a nonautoregressive model named as Laguerre-multilayer perceptron network. Moreover, the effect of ambient temperature and humidity changes in the range of biomedical applications of IPMC was investigated using variance analysis of experimental data and also these ambient conditions were applied to the proposed model as operating points. This model was described in detail and validated by experimental results.