Modelling and Control of Ionic Electroactive Polymer Actuators under Varying Humidity Conditions

In this work, we address the problem of position control of ionic electroactive polymer soft actuators under varying relative humidity conditions. The impact of humidity on the actuation performance of ionic actuators is studied through frequency response and impedance spectroscopy analysis. Considering the uncertain performance of the actuator under varying humidity conditions, an adaptable model using the neural network method is developed. The model uses relative humidity magnitude as one of the model parameters, making it robust to different environmental conditions. Utilizing the model, a closed-loop controller based on the model predictive controller is developed for position control of the actuator. The developed model and controller are experimentally verified and found to be capable of predicting and controlling the actuators with excellent tracking accuracy under relative humidity conditions varying in the range of 10-90%.