کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5004592 1368987 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Research ArticleRecurrent fuzzy neural network backstepping control for the prescribed output tracking performance of nonlinear dynamic systems
ترجمه فارسی عنوان
مقاله پژوهشی مقاله کنترل جریان مجدد شبکه عصبی فازی با استفاده از عملکرد ردیابی خروجی سیستم های پویا غیر خطی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی


- Designing backstepping controller for a prescribed performance control.
- Defining an error constrained variable to guarantee the prescribed error bound.
- Considering RFNNs to approximate unknown and differential terms.
- Simulation and experiment for the efficacy of the proposed control scheme.

This paper proposes a backstepping control system that uses a tracking error constraint and recurrent fuzzy neural networks (RFNNs) to achieve a prescribed tracking performance for a strict-feedback nonlinear dynamic system. A new constraint variable was defined to generate the virtual control that forces the tracking error to fall within prescribed boundaries. An adaptive RFNN was also used to obtain the required improvement on the approximation performances in order to avoid calculating the explosive number of terms generated by the recursive steps of traditional backstepping control. The boundedness and convergence of the closed-loop system was confirmed based on the Lyapunov stability theory. The prescribed performance of the proposed control scheme was validated by using it to control the prescribed error of a nonlinear system and a robot manipulator.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 53, Issue 1, January 2014, Pages 33-43
نویسندگان
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