Nonlinear Parametric Identification of an IPMC Actuator Model

Ionic polymer metal composite is a class of electro-active polymers which are very attractive smart actuators due to its large bending deflection, high mechanical flexibility, low excitation voltage, low density, and ease of fabrication. These properties make IPMC a proper candidate for many applications in various fields such as robotics, aerospace, biomedicine, etc. Although the actuation behaviors of this material are recently investigated, it is still a challenging problem to develop a promising model which covers all the physical properties associated with it. Further, nonlinear identification methods for IPMC nonlinear actuation model have not yet been applied. In this paper, Bonomo’s nonlinear model is used to formulate IPMC. In the following, the parameters of this model are identified through compromising nonlinear and linear least squares methods. According to the input type, the identification process for the electrical part is decoupled into two groups: nonlinear and linear. This technique resulted in reducing the number of parameters and more accurate identification. The identification method is validated using proper inputs. The generated results show that convergence of the identified parameters is guaranteed by the proposed method.