In this work, we propose an Adaptive Neuro Fuzzy Inference System (ANFIS) based hysteresis modeling and
control strategy for a thin Shape Memory Alloy (SMA) wire. Controlling the SMA wire is a challenging problem
because of its dynamic hysteretic behavior. By using a hybrid learning procedure ANFIS architectures are
powerful tools for many applications, such as identifying nonlinear parameters in a controlled system, predicting
chaotic time series and modeling nonlinear functions. We tested our ANFIS model by making it predict major
and minor hysteresis loops in different driving frequencies and compared them with the experimental data. To
compensate the hysteretic effect, we used an inverse ANFIS model and used it directly as a controller. After
dramatically reducing the hysteretic effect, we implemented a PI control to fine tune the response.