Abstract
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Electroactive polymer actuators, especially those
based on polypyrrole (PPy), possess unique characteristics such
as an ability to operate at the macro or micro scale, large forceto-
weight ratio, biocompatibility, low cost and operation in
aqueous and non-aqueous environments. Therefore, they are
very suitable for the establishment of bio-mimetic devices,
single-cell manipulators, robotics, prosthetics, and numerous
biomedical applications. In this paper, we report on the neurofuzzy
control of these actuators, which are typified by the trilayer
polypyrrole actuators considered in this paper, in order
to improve their positioning accuracy and speed of response.
We experimentally evaluated two model-free intelligent control
strategies, which are fuzzy logic PD+I control and neuro-fuzzy
Adaptive Neural Fuzzy Inference System (ANFIS) control. The
performance of these intelligent controllers is compared to that
of a conventional Proportional Integral Derivative (PID)
controller. The experimental results demonstrated that they
significantly outperformed the conventional PID controller
with an improvement in rise time of at least 18 times and in
settling time of at least 2 times. To the best of authors’
knowledge, this is the first study to design and evaluate fuzzy
logic PD+I and neuro-fuzzy ANFIS PD+I intelligent control
methodologies for an important class of electroactive polymer
actuators.