Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System

A novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced b...

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Main Authors: Ll Yi-Min, Yue Yang, Li Li
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2012/658424
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author Ll Yi-Min
Yue Yang
Li Li
author_facet Ll Yi-Min
Yue Yang
Li Li
author_sort Ll Yi-Min
collection DOAJ
description A novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced by the average of two type-1 fuzzy systems. Ultimately, the adaptive laws, by means of backstepping design technique, will be developed to adjust the parameters to attenuate the approximation error and external disturbance. According to stability theorem, it is proved that the proposed Type-2 Adaptive Backstepping Fuzzy Control (T2ABFC) approach can guarantee global stability of closed-loop system and ensure all the signals bounded. Compared with existing Type-1 Adaptive Backstepping Fuzzy Control (T1ABFC), as the advantages of handling numerical and linguistic uncertainties, T2ABFC has the potential to produce better performances in many respects, such as stability and resistance to disturbances. Finally, a biological simulation example is provided to illustrate the feasibility of control scheme proposed in this paper.
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series Journal of Applied Mathematics
spelling doaj-art-ee10cdc7496348e5a21a1e80a6a6b71a2025-08-20T02:21:42ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/658424658424Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy SystemLl Yi-Min0Yue Yang1Li Li2Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013, ChinaFaculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013, ChinaSchool of Computer Science Telecommunication Engineering, Zhenjiang, Jiangsu 212013, ChinaA novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced by the average of two type-1 fuzzy systems. Ultimately, the adaptive laws, by means of backstepping design technique, will be developed to adjust the parameters to attenuate the approximation error and external disturbance. According to stability theorem, it is proved that the proposed Type-2 Adaptive Backstepping Fuzzy Control (T2ABFC) approach can guarantee global stability of closed-loop system and ensure all the signals bounded. Compared with existing Type-1 Adaptive Backstepping Fuzzy Control (T1ABFC), as the advantages of handling numerical and linguistic uncertainties, T2ABFC has the potential to produce better performances in many respects, such as stability and resistance to disturbances. Finally, a biological simulation example is provided to illustrate the feasibility of control scheme proposed in this paper.http://dx.doi.org/10.1155/2012/658424
spellingShingle Ll Yi-Min
Yue Yang
Li Li
Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
Journal of Applied Mathematics
title Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
title_full Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
title_fullStr Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
title_full_unstemmed Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
title_short Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System
title_sort adaptive backstepping fuzzy control based on type 2 fuzzy system
url http://dx.doi.org/10.1155/2012/658424
work_keys_str_mv AT llyimin adaptivebacksteppingfuzzycontrolbasedontype2fuzzysystem
AT yueyang adaptivebacksteppingfuzzycontrolbasedontype2fuzzysystem
AT lili adaptivebacksteppingfuzzycontrolbasedontype2fuzzysystem