Cyber-Physical Systems Oriented Modeling of NiTi Shape Memory Alloy Spring Functionality

Thanks to the unique characteristics of high-power-to-weight ratio, low driving voltages, and superior capability to generate large strains, the Shape Memory Alloy actuators (SMA), have attracted great attentions in the field of nonconventional actuators and show large potentials in a wide variety of Cyber-Physical System applications. 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 technique of Hammerstein–Wiener black-box modeling is proposed for the behavior prediction of the shape memory alloy actuators, which performs in a nonlinear manner. 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. Comprehensive experiments demonstrate the efficacy of the developed model in precisely forecasting the SMA actuators behaviors, thus aiding in the selection and optimal tuning of control system parameters.