Dynamic Modeling and Functional characterization of NiTi Shape Memory Alloy Spring Actuator for Embedded Systems

Shape Memory Alloy (SMA) actuators have attracted significant attention in the field of non-conventional actuators widely used in embedded systems, due to their unique characteristics such as high-power-to-weight ratio, low driving voltages, and ability to produce large strains. However, achieving precise motion control of SMA actuators poses a challenge due to their complex thermostatically behavior and inherent nonlinear hysteresis. In this paper, the Hammerstein-Wiener black-box modeling technique is proposed to accurately predict the nonlinear behavior of the shape memory alloy actuators. The approach utilizes system identification techniques to develop a dynamic model for the SMA spring actuator, which can predict its behavior accurately under various input conditions. This methodology shifts the challenge of accurately modeling the system’s physics to the task of formulating an input-output structure that encompasses its dynamics. The results demonstrate the efficacy of the proposed model in precisely forecasting the behavior of SMA actuators, thus aiding in the selection and optimal tuning of control system parameters.