3 April 2008 ANFIS based modeling and inverse control of a thin SMA wire
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Abstract
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.
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Atilla Kilicarslan, Gangbing Song, Karolos Grigoriadis, "ANFIS based modeling and inverse control of a thin SMA wire", Proc. SPIE 6926, Modeling, Signal Processing, and Control for Smart Structures 2008, 69260H (3 April 2008); doi: 10.1117/12.778218; https://doi.org/10.1117/12.778218
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