کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4976329 | 1365622 | 2009 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Auto-structuring fuzzy neural system for intelligent control
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
An auto-structuring fuzzy neural network-based control system (ASFNS), which includes the auto-structuring fuzzy neural network (ASFNN) controller and the supervisory controller, is proposed in this paper. The ASFNN is used as the main controller to approximate the ideal controller and the supervisory controller is incorporated with the ASFNN for coping with the chattering phenomenon of the traditional sliding-mode control. In the ASFNS, an automatic structure learning mechanism is proposed for network structure optimization, where two criteria of node-adding and node-pruning are introduced. It enables the ASFNN to determine the nodes autonomously while ensures the control performance. In the ASFNS, all the parameters are evolved by the means of the Lyapunov theorem and back-propagation to ensure the system stability. Thus, an intelligent control approach for adaptive control is presented, where the structure and parameter can be evolved simultaneously. The proposed ASFNS features the following salient properties: (1) on-line and model-free control, (2) relax design in controller structure, (3) overall system stability. To investigate the capabilities, the ASFNS is applied to a kind of nonlinear system control. Through the simulation results the advantages of the proposed ASFNS can be validated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Franklin Institute - Volume 346, Issue 3, April 2009, Pages 267-288
Journal: Journal of the Franklin Institute - Volume 346, Issue 3, April 2009, Pages 267-288
نویسندگان
Kuo-Hsiang Cheng,