Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System

被引：1
作者：
Li Yi-Min [1 ]
Yue Yang [1 ]
Li Li [2 ]
机构：
[1] Jiangsu Univ, Fac Sci, Zhenjiang 212013, Jiangsu, Peoples R China
[2] Sch Comp Sci Telecommun Engn, Zhenjiang 212013, Jiangsu, Peoples R China
来源：
JOURNAL OF APPLIED MATHEMATICS | 2012年
基金：
中国国家自然科学基金;
关键词：
NONLINEAR-SYSTEMS; NEURAL-CONTROL; TRACKING CONTROL; LOGIC SYSTEMS; DESIGN; SCHEME; SETS;
D O I：
10.1155/2012/658424
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
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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页数：27
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共 56 条
  • [11] Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
    Ge, SS
    Wang, J
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (06): : 1409 - 1419
  • [12] A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
    Hagras, HA
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2004, 12 (04) : 524 - 539
  • [13] Type-2 FLCs: A new generation of fuzzy controllers
    Hagras, Hani
    [J]. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2007, 2 (01) : 30 - 43
  • [14] Adaptive neural control for a class of nonlinearly parametric time-delay systems
    Ho, DWC
    Li, JM
    Niu, YG
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2005, 16 (03): : 625 - 635
  • [15] Design of interval type-2 fuzzy sliding-mode controller
    Hsiao, Ming-Ying
    Li, Tzuu-Hseng S.
    Lee, J. -Z.
    Chao, C. -H.
    Tsai, S. -H.
    [J]. INFORMATION SCIENCES, 2008, 178 (06) : 1696 - 1716
  • [16] Wavelet adaptive backstepping control for a class of nonlinear systems
    Hsu, Chun-Fei
    Lin, Chih-Min
    Lee, Tsu-Tian
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (05): : 1175 - 1183
  • [17] Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks
    Jammeh, Emmanuel A.
    Fleury, Martin
    Wagner, Christian
    Hagras, Hani
    Ghanbari, Mohammed
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2009, 17 (05) : 1123 - 1142
  • [18] AN EXTENDED DIRECT SCHEME FOR ROBUST ADAPTIVE NONLINEAR CONTROL
    KANELLAKOPOULOS, I
    KOKOTOVIC, PV
    MARINO, R
    [J]. AUTOMATICA, 1991, 27 (02) : 247 - 255
  • [19] SYSTEMATIC DESIGN OF ADAPTIVE CONTROLLERS FOR FEEDBACK LINEARIZABLE SYSTEMS
    KANELLAKOPOULOS, I
    KOKOTOVIC, PV
    MORSE, AS
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1991, 36 (11) : 1241 - 1253
  • [20] Centroid of a type-2 fuzzy set
    Karnik, NN
    Mendel, JM
    [J]. INFORMATION SCIENCES, 2001, 132 (1-4) : 195 - 220
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