کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5005161 | 1369011 | 2008 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fuzzy-rule emulated networks, based on reinforcement learning for nonlinear discrete-time controllers
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
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چکیده انگلیسی
This article introduces an adaptive controller for a class of nonlinear discrete-time systems, based on self adjustable networks called Multi-Input Fuzzy Rules Emulated Networks (MIFRENs), and its reinforcement learning algorithm. Because of the universal function approximation of MIFREN, the first MIFREN called MIFRENc is used to estimate a long-term cost function, which demonstrates as a performance index for the tuning procedure. Another network or MIFRENa is designed as a direct controller via the human knowledge through defined If-Then rules. The selection procedure for any system parameters, such as learning rates and some constant parameters, is represented by the proof of proposed theorems. The system's performance is demonstrated by computer simulations via selected nonlinear discrete-time systems, and comparison results with other controllers to validate theoretical development.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 47, Issue 4, October 2008, Pages 362-373
Journal: ISA Transactions - Volume 47, Issue 4, October 2008, Pages 362-373
نویسندگان
Chidentree Treesatayapun,