Integral multiple models online identifier applied to ionic polymer–metal composite actuator

Abstract

Ionic polymer–metal composites are classified as a smart materials group, whose properties can be designed depending on the needs that arise. Ionic polymer–metal composites belong to the class of wet electroactive polymers. They are promising candidates actuator for various potential applications mainly due to their flexible, low voltage requirements, compact design, and lack of moving parts. However, being a widely used material in industry, ionic polymer–metal composite requires complex control methods due to its strongly nonlinear nature. An important prerequisite for an intelligent controller is the ability to adapt rapidly to any unknown operating environment. This article presents a novel approach to tuning multiple models of an online identifier by integral mapping. Through the extension of the estimation law of additional mapping between parameters and measurable signals, we significantly improve transient responses without increasing feedback gain. The authors measured the moisture content of ionic polymer–metal composite and consider in the experiment relationship between drying and varying of curvature output. The effectiveness of the proposed multiple models adaptive control strategy was verified in various experiments. The results of the study illustrated in the experiments show that adding new mapping improves not only the transients of controlled plant, but also increases the performance indexes of adaptive system.