A class of type-2 fuzzy neural networks for nonlinear dynamical system identification

Neural Computing and Applications

Volumn 23, Issue 3-4, 2013, Pages 707-717

  Tavoosi, Jafar ^a   Badamchizadeh, Mohammad Ali ^a  

^a UNIVERSITY OF TABRIZ   (Iran)

Author keywords

Identification; Nonlinear dynamical system; Type 2 fuzzy neural networks

Indexed keywords

ADAPTIVE LEARNING RATES; ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM; GAUSSIAN MEMBERSHIP FUNCTION; GRADIENT DESCENT; LEARNING PHASE; TAKAGI-SUGENO-KANG FUZZY NEURAL NETWORKS; TYPE REDUCTION; TYPE-2 FUZZY;

BACKPROPAGATION; FUZZY NEURAL NETWORKS; IDENTIFICATION (CONTROL SYSTEMS);

NONLINEAR DYNAMICAL SYSTEMS;

EID: 84884593282     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-0981-7     Document Type: Article

References (22)

1. Nelles O (2001) Nonlinear system identification. Springer, Berlin, Heidelberg.
2. Thoma M, Allgöwer F, Morari M (2010) Block-oriented nonlinear system identification. Springer, Berlin, Heidelberg.
3. Ruano AE (2005) Intelligent control systems using computational intelligence techniques. Institution of Engineering and Technology.
4. Castillo O, Melin P (2008) type-2 fuzzy logic: theory and applications. Springer, Berlin, Heidelberg.
5. Castro JR, Castillo O, Melin P, Rodríguez-Díaz A (2009) A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks. J Inform Sci 179: 2175-2193.
6. Abiyev RH, Kaynak O, Alshanableh T, Mamedov F (2011) A type-2 neuro-fuzzy system based on clustering and gradient techniques applied to system identification and channel equalization. Appl Soft Comput 11: 1396-1406.
7. Martínez R, Castillo O, Aguilar LT (2009) Optimization of interval type-2 fuzzy logic controllers for a perturbedautonomous wheeled mobile robot using genetic algorithms. Inf Sci 179: 2158-2174.
8. Sung-Kwun O, Jang H-J, Pedrycz W (2011) A comparative experimental study of type-1/type-2 fuzzy cascade controller based on genetic algorithms and particle swarm optimization. Expert Syst Appl 38: 11217-11229.
9. Karnik NN, Mendel JM (1999) Application of type-2 fuzzy logic systems to forecasting of time-series. Inf Sci 120: 89-111.
10. Lin F-J, Shieh P-H, Hung Y-C (2008) An intelligent control for linear ultrasonic motor using interval type-2 fuzzy neural network. IET Electr Power Appl 2(1): 32-41.
11. Liang Q, Mendel JM (2000) Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters. IEEE Trans Fuzzy Syst 8(5): 551-563.
12. Lin T-C (2010) Based on interval type-2 fuzzy-neural network direct adaptive sliding mode control for SISO nonlinear systems. Commun Nonlinear Sci Numer Simul 15(12): 4084-4099.
13. Hwang C, Rhee FC-H (2007) Uncertain fuzzy clustering: interval type-2 fuzzy approach to C-means. IEEE Trans Fuzzy Syst 15(1): 107-120.
14. Hagras HA (2004) A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans Fuzzy Syst 12(4): 524-539.
15. Dereli T, Baykasoglu A, Altun K, Alptekin Durmusoglu I, Turksen B (2011) Industrial applications of type-2 fuzzy sets and systems: a concise review. Comput Ind 62: 125-137.
16. Castro JR, Castillo O, Martínez LG (2007) Interval type-2 fuzzy logic toolbox. Eng Lett 15: 1, EL_15_1_14.
17. Mendel JM (2001) Uncertain rule-based fuzzy logic systems: introduction and new directions. Prentice-Hall, NJ.
18. Mendel JM (2007) Advances in type-2 fuzzy sets and systems. Inf Sci 177: 84-110.
19. Nilesh N. Karnik, Jerry M. Mendel, and Qilian Liang (1999) Type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 7(6).
20. Singh M, Smriti Srivastava M, Hanmandlu JRP Gupta (2009) Type-2 fuzzy wavelet networks (T2FWN) for system identification using fuzzy differential and Lyapunov stability algorithm. Applied Soft Comput 9: 977-989.
21. Yazdizadeh A, Khorasani K (2002) Adaptive time delay neural network structures for nonlinear system identifcation. Neurocomputing 47: 207-240.
22. Juang C-F, Tsao Y-W (2008) A self-evolving interval type-2 fuzzy neural network with online structure and parameter learning. IEEE Trans Fuzzy Syst 16(6): 1411-1424.