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An ion polymer metal composite (IPMC) is an electro-active polymer that bends in response to a small applied electrical field as a result of the mobility of cations in the polymer network and vice versa. The aim of this paper is the identification of a novel accurate nonlinear black-box model (NBBM) for IPMC actuators with self-sensing behavior based on a recurrent multi-layer perceptron neural network (RMLPNN) and a self-adjustable learning mechanism (SALM).