Adaptive controller with fuzzy rules emulated structure and its applications
In this paper, the adaptive controller inspired by the neuro-fuzzy controller is proposed. Its structure, called fuzzy rules emulated network (FREN), is derived based on the fuzzy if-then rules. This structure not only emulates the fuzzy control rules but also allows the initial value of controller&...
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th-cmuir.6653943832-12792014-08-29T09:29:03Z Adaptive controller with fuzzy rules emulated structure and its applications Treesatayapun C. Uatrongjit S. In this paper, the adaptive controller inspired by the neuro-fuzzy controller is proposed. Its structure, called fuzzy rules emulated network (FREN), is derived based on the fuzzy if-then rules. This structure not only emulates the fuzzy control rules but also allows the initial value of controller's parameters to be intuitively chosen. These parameters are further adjusted during system operation using a method similar to the steepest descent technique. The learning rate selection criteria based on Lyapunov's stability condition is also presented. FREN controller is applied to control various nonlinear systems, for examples, the single invert pendulum plant, the water bath temperature control, the high voltage direct current transmission system and the robotic system. Computer simulations results indicate that the proposed controller is able to control the target systems satisfactory. © 2005 Elsevier Ltd. All rights reserved. 2014-08-29T09:29:03Z 2014-08-29T09:29:03Z 2005 Article 09521976 10.1016/j.engappai.2004.12.006 EAAIE http://www.scopus.com/inward/record.url?eid=2-s2.0-18144378452&partnerID=40&md5=55ab8b7f93665d1ca75164dc3f8b655a http://cmuir.cmu.ac.th/handle/6653943832/1279 English |
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In this paper, the adaptive controller inspired by the neuro-fuzzy controller is proposed. Its structure, called fuzzy rules emulated network (FREN), is derived based on the fuzzy if-then rules. This structure not only emulates the fuzzy control rules but also allows the initial value of controller's parameters to be intuitively chosen. These parameters are further adjusted during system operation using a method similar to the steepest descent technique. The learning rate selection criteria based on Lyapunov's stability condition is also presented. FREN controller is applied to control various nonlinear systems, for examples, the single invert pendulum plant, the water bath temperature control, the high voltage direct current transmission system and the robotic system. Computer simulations results indicate that the proposed controller is able to control the target systems satisfactory. © 2005 Elsevier Ltd. All rights reserved. |
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Treesatayapun C. Uatrongjit S. |
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Treesatayapun C. Uatrongjit S. Adaptive controller with fuzzy rules emulated structure and its applications |
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Treesatayapun C. Uatrongjit S. |
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Treesatayapun C. |
title |
Adaptive controller with fuzzy rules emulated structure and its applications |
title_short |
Adaptive controller with fuzzy rules emulated structure and its applications |
title_full |
Adaptive controller with fuzzy rules emulated structure and its applications |
title_fullStr |
Adaptive controller with fuzzy rules emulated structure and its applications |
title_full_unstemmed |
Adaptive controller with fuzzy rules emulated structure and its applications |
title_sort |
adaptive controller with fuzzy rules emulated structure and its applications |
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2014 |
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http://www.scopus.com/inward/record.url?eid=2-s2.0-18144378452&partnerID=40&md5=55ab8b7f93665d1ca75164dc3f8b655a http://cmuir.cmu.ac.th/handle/6653943832/1279 |
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