A parameter identification model for shape memory alloy actuators for airfoil deformation based on the least squares method

In this paper, we investigated the application of the parameter identification technique based on the least square method in the shape memory alloy (SMA) actuator model. We also designed thermoelectric coupling experiments, in which nitinol SMA wires were used. Supplied with power by a DC constant voltage source, the control module energized and heated the SMA wires. We recorded the changes of the voltage, current, and temperature during the heating process. Based on the least square method, the data in the temperature interval from 50°C to 60°C were analyzed and the specific heat parameters were calculated using linear least squares estimation. The optimization algorithm, on the other hand, seeks the local optimal solution by minimizing the square of the difference between the simulated and experimental values. The results show that both the least square method and the optimization algorithm are effective in specific heat parameter identification, that the relative error of the optimization algorithm (8.53%) is smaller than that of the least square method (18.1%). The comparative analysis of simulation and experimental data confirms the effectiveness of the identification method, which provides an accurate and efficient analysis tool for the design of intelligent deformation aircraft and helps improve the performance and reliability of the vehicle. The study looks forward to the potential application of the identification method in other smart materials and structures, providing a theoretical foundation and technical support for the development of intelligent deformation technology.