کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10324097 | 661403 | 2005 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Observer-based indirect adaptive fuzzy sliding mode control with state variable filters for unknown nonlinear dynamical systems
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Observer-based indirect adaptive fuzzy sliding mode control with state variable filters for unknown nonlinear dynamical systems Observer-based indirect adaptive fuzzy sliding mode control with state variable filters for unknown nonlinear dynamical systems](/preview/png/10324097.png)
چکیده انگلیسی
This paper proposes an observer-based indirect adaptive fuzzy sliding mode controller with state variable filters for a certain class of unknown nonlinear dynamic systems in which not all the states are available for measurement. To design the proposed controller, we first construct the fuzzy models to describe the input/output behavior of the nonlinear dynamic system. Then, an observer is employed to estimate the tracking error vector. Based on the observer, a fuzzy sliding model controller is developed to achieve the tracking performance. Then, a filtered observation error vector is obtained by passing the observation error vector to a set of state variable filters. Finally, on the basis of the filtered observation error vector, the adaptive laws are proposed to adjust the free parameters of the fuzzy models. The stability of the overall control system is analyzed based on the Lyapunov method. Simulation results illustrate the design procedures and demonstrate the tracking performance of the proposed controller.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 155, Issue 2, 16 October 2005, Pages 292-308
Journal: Fuzzy Sets and Systems - Volume 155, Issue 2, 16 October 2005, Pages 292-308
نویسندگان
Chung-Chun Kung, Ti-Hung Chen,