Multiple models input-output adaptive controller applied to Ionic Polymer Metal Composite

Ionic Polymer Metal Composites(IPMCs) belong to the class of wet Electro-active Polymers (EAPs) and is promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design and lack of moving parts. Among the smart materials available, IPMCs seem to fit nicely in the constraints of robotics because they react mechanically when stimulated by an electrical signal. However, being a widely used material in industry, it requires complex control methods due to its strongly nonlinear nature. This paper presents a novel approach to tuning multiple models adaptive controller. By adding additional filters we significantly improve convergence of the estimates to the true values of the IPMC parameters as compared to conventional adaptive controllers. Numerical results and comparison with experimental data are presented. The effectiveness of the proposed multiple models adaptive control strategy is verified in experiments.