Abstract
In order to deepen the theoretical understanding of the interval type-2 (IT2) fuzzy logic controllers (FLCs), it is meaningful to explore the fundamental properties of IT2FLCs, e.g. continuity, monotonicity, smoothness, adaptiveness, novelty, stability and robustness. This paper studies another fundamental property—the symmetry, which is always required in real-world control applications. Symmetric conditions are derived to ensure the symmetry of FLCs, including both IT2FLCs and type-1 FLCs (T1FLCs). For IT2FLCs, we consider three most commonly-used type-reduction and defuzzification methods—the Karnik–Mendel (KM) method, the uncertainty bound (UB) method and the Begian-Melek-Mendel (BMM) method. At last, an application is given to verify the correctness of the derived results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mendel JM (2001) Uncertain rule-based fuzzy logic systems: introduction and new directions. Prentice-Hall, Upper Saddle River, NJ
Castillo O, Melin P (2008) Type-2 fuzzy logic theory and applications. Springer, Berlin
Wagner C, Hagras H (2010) Toward general type-2 fuzzy logic systems based on zSlices. IEEE Trans Fuzzy Syst 18(4):637–660
Hagras H, Wagner C (2012) Towards the wide spread use of type-2 fuzzy logic systems in real world applications. IEEE Comput Intell Mag 7(3):14–24
Manceur M, Essounbouli N, Hamzaoui A (2012) Second-order sliding fuzzy interval type-2 control for an uncertain system with real application. IEEE Trans Fuzzy Syst 20(2):262–275
Barkat S, Tlemcani A, Nouri H (2011) Noninteracting adaptive control of PMSM using interval type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 19(5):925–936
Castillo O, Melin P (2012) A review on the design and optimization of interval type-2 fuzzy controllers. Appl Soft Comput 12(4):1267–1278
Castillo O, Martinez-Marroquin R, Melin P et al (2012) Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. Inf Sci 192:19–38
Wu D, Mendel JM (2011) On the continuity of type-1 and interval type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 19(1):179–192
Li C, Yi J, Wang M, Zhang G (2012) Monotonic type-2 fuzzy nural network and its application to thermal comfort prediction. Neural Comput Appl. doi:10.1007/s00521-012-1140-x
Li C, Yi J, Zhao D (2009) Analysis and design of monotonic type-2 fuzzy inference systems. FUZZ-IEEE 2009:1193–1198
Wu D (2012) On the fundamental differences between interval type-2 and type-1 fuzzy logic controllers. IEEE Trans Fuzzy Syst 20(5):832–848
Jafarzadeh S, Fadali S, Sonbol A (2011) Stability analysis and control of discrete type-1 and type-2 TSK fuzzy systems: Part I stability analysis. IEEE Trans Fuzzy Syst 19(6):989–1000
Jafarzadeh S, Fadali S, Sonbol A (2011) Stability analysis and control of discrete type-1 and type-2 TSK fuzzy systems: part II control design. IEEE Trans Fuzzy Syst 19(6):1001–1013
Biglarbegian M, Melek W, Mendel JM (2011) On the robustness of type-1 and interval type-2 fuzzy logic systems in modeling. Inf Sci 181(7):1325–1347
Wu D, Tan WW (2010) Interval type-2 fuzzy PI controllers: Why they are more robust. FUZZ-IEEE 20010:802–807
Wu H, Mendel JM (2002) Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 10(5):622–639
Lynch C, Hagras H, Callaghan V (2005) Embedded type-2 FLC for real-time speed control of marine & traction diesel engines. FUZZ-IEEE 2005:347–352
Biglarbegian M, Melek W, Mendel JM (2010) On the stability of interval type-2 TSK fuzzy logic control systems. IEEE Trans Syst Man Cybern: B Cybern 41(5):798–818
Li C, Zhang G, Yi J, Wang T (2011) On the properties of SIRMs connected type-1 and type-2 fuzzy inference systems. FUZZ-IEEE 2011:1982–1988
Phan PA, Gale TJ (2008) Direct adaptive fuzzy control with a self-structuring algorithm. Fuzzy Sets Syst 159:871–899
Hsiao M-Y, Li T-HS, Lee J-Z et al (2008) Design of interval type-2 fuzzy sliding-mode controller. Inf Sci 178:1696–1716
Acknowledgments
This work is supported by National Natural Science Foundation of China (61105077, 61273149, 61074149 and 61273326), and the Excellent Young and Middle-Aged Scientist Award Grant of Shandong Province of China (BS2012DX026).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, C., Zhang, G., Yi, J., Wang, M. (2013). On the Symmetry of Interval Type-2 Fuzzy Logic Controllers Using Different Type-Reduction Methods. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38524-7_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-38524-7_47
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38523-0
Online ISBN: 978-3-642-38524-7
eBook Packages: EngineeringEngineering (R0)