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
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Fuzzy-rule emulated networks, based on reinforcement learning for nonlinear discrete-time controllers
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
نویسندگان
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