An error compensator based simplified adaptive inverse control method for IPMC actuators tuning

Abstract

Ionic polymer metal composites (IPMCs), also called artificial muscle, are actuators that lend themselves well to micro manipulators, micro-pump, biomimetics integrated application systems due to their lightweight, flexibility, ability to tailor their geometry, work in water environment, as well as the capability to be miniaturized and implanted into MEMS devices. The major issue with implementing IPMCs into such devices is the ability to control their actuation precisely. Like other EAP materials, IPMCs possess strong nonlinear properties which can be described as hybrid property of creep (also called back relaxation phenomenon) and hysteresis characteristics which also vary with different working conditions like water-content, working temperature and even the usage consumption. To deal with this problem, this paper represented a novel proportional-integral (PI) error compensation (EC) controller combined with simplified adaptive inverse (AI) control method based on the on-line creep and hysteresis (using Prandtl-Ishlinskii operators) hybrid IPMC model estimation techniques to tune the IPMC actuators. Here, the newly-formed controller is called Error Compensation Adaptive Inverse (ECAI) controller. The WLMS (Weighted Least Mean Squares) identification method was employed due to its insensitivity to the input noise. The AI controller will be able to predict the IPMC's performance and accelerate the whole system's response. The error compensation (PI feedback) controller will be able to compensate the error which the AI feed-forward controller failed to tune and will also enhance the precision and robustness. Simulations both with comparison experiments were carried out which confirmed the good performance of the proposed control method.