Modeling SMA actuated systems based on Bouc-Wen hysteresis model and feed-forward neural network
محل انتشار: مجله مکانیک کاربردی محاسباتی، دوره: 49، شماره: 1
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 437
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JCAM-49-1_002
تاریخ نمایه سازی: 18 تیر 1398
چکیده مقاله:
Despite the fact that shape-memory alloy (SMA) has several mechanical advantages as it continues being used as an actuator in engineering applications, using it still remains as a challenge since it shows both non-linear and hysteretic behavior. To improve the efficiency of SMA application, it is required to do research not only on modeling it, but also on control hysteresis behavior of these materials which are the fundamentals of several research opportunities in this area. Having considered these requirements, we have introduced a mathematical model to describe the hysteresis behavior of a mechanical system attached to SMA wire actuators using Bouc-Wen hysteresis model and feed-forward neural network. Due to inability of linear mass-spring-damper equations of classic Bouc-wen model to explain the hysteresis behavior of SMA actuators, in this paper we have applied changes in the mentioned equations of classic Bouc-Wen model to describe hysteresis loops of model. We also have used flexibility of the neural network systems to describe Bouc-Wen output in the main equation. Parameters of the developed model have been trained for a real mechanical system using simulation data after selecting proper configuration for the selected neural network. Finally, we have checked the accuracy of our model by applying two different series of validation data. The result shows the acceptable accuracy of the developed model.
کلیدواژه ها:
نویسندگان
Ali Mohsenian
School of Mechanical Engineering, College of Engineering, University of Tehran
Mohamadreza Zakerzadeh
School of Mechanical Engineering, College of Engineering, University of Tehran
Masoud Shariat Panahi
School of Mechanical Engineering, College of Engineering, University of Tehran
Alireza fakhrzade
School of Mechanical Engineering, College of Engineering, University of Tehran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :