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二型模糊系统降型算法综述

赵涛岩 李平 曹江涛

赵涛岩, 李平, 曹江涛. 二型模糊系统降型算法综述[J]. 西南交通大学学报, 2019, 54(2): 436-444. doi: 10.3969/j.issn.0258-2724.20170060
引用本文: 赵涛岩, 李平, 曹江涛. 二型模糊系统降型算法综述[J]. 西南交通大学学报, 2019, 54(2): 436-444. doi: 10.3969/j.issn.0258-2724.20170060
ZHAO Taoyan, LI Ping, CAO Jiangtao. Overview of Type-Reduction Algorithms for Type-2 Fuzzy Logic Systems[J]. Journal of Southwest Jiaotong University, 2019, 54(2): 436-444. doi: 10.3969/j.issn.0258-2724.20170060
Citation: ZHAO Taoyan, LI Ping, CAO Jiangtao. Overview of Type-Reduction Algorithms for Type-2 Fuzzy Logic Systems[J]. Journal of Southwest Jiaotong University, 2019, 54(2): 436-444. doi: 10.3969/j.issn.0258-2724.20170060

二型模糊系统降型算法综述

doi: 10.3969/j.issn.0258-2724.20170060
基金项目: 国家自然科学基金资助项目(61673199);辽宁省高等学校优秀人才支持计划资助项目(LR2015034)
详细信息
    作者简介:

    赵涛岩(1986—),男,博士研究生,研究方向为二型模糊系统的控制与应用,E-mail:zhaotaoyan1986@126.com

    通讯作者:

    李平(1964—),男,教授,研究方向为工业过程的先进控制与优化,E-mail:lping141@126.com

  • 中图分类号: TP273

Overview of Type-Reduction Algorithms for Type-2 Fuzzy Logic Systems

  • 摘要: 二型模糊系统降型过程的计算精度、计算时间和系统信息的损失会对整个二型模糊系统的性能产生很大地影响. 本文首先介绍了二型模糊集合的基本概念及二型模糊系统的计算过程,然后分别对区间二型模糊系统和广义二型模糊系统的降型算法的研究现状进行了详细综述,并对不同降型算法计算的复杂性进行了全面的分析和比较. 最后,总结了各类降型算法存在的问题,并给出了未来研究的展望. 指出,降型算法的计算成本仍是提升二型模糊系统性能的瓶颈,从理论上完善各种降型算法,通过数学方法解决其计算的复杂性问题,并将其应用于实时系统会是未来研究的重点.

     

  • 图 1  二型模糊系统的结构框图

    Figure 1.  Block diagram of type-2 fuzzy logic systems

    图 2  二型模糊集合

    Figure 2.  Type-2 fuzzy sets

  • ZADEH L A. Fuzzy sets[J]. Information and Control, 1965, 8(13): 338-353.
    COUPLAND S, JOHN R I. Type-2 fuzzy logic and the modeling of uncertainty[M]. Berlin: Springer-Verlag, 2008: 3-22
    ZADEH L A. The concept of a linguistic variable and its application to approximate reasoning-I[J]. Information Sciences, 1975, 8(1): 199-249.
    HISDAL E. The IF THEN ELSE statement and interval-valued fuzzy sets of higher type[J]. International Journal of Man-Machine Studies, 1981, 15(44): 385-455.
    JANA D K, BEJ B, WAHAB M H A, et al. Novel type-2 fuzzy logic approach for inference of corrosion failure likelihood of oil and gas pipeline industry[J]. Engineering Failure Analysis, 2017, 80: 299-311. doi: 10.1016/j.engfailanal.2017.06.046
    TAYYEBI S, SOLTANALI, S. A new approach of GA-based type reduction of interval type-2 fuzzy model for nonlinear MIMO system:application in methane oxidtion process[J]. Chemonmetrics and Intelligent Laboratory Systems, 2017, 167: 152-160. doi: 10.1016/j.chemolab.2017.06.004
    COTELI R, ACIKGOZ H, UCAR F, et al. Design and implementation of type-2 neural system controller for PWM rectifiers[J]. International Journal of Hydrogen Energy, 2017, 42(32): 20759-20771. doi: 10.1016/j.ijhydene.2017.07.032
    CASTILLO O, CERVANTES L, SORIA J, et al. A generalized type-2 fuzzy granular approach with application to aerospace[J]. Information Sciences, 2016, 354: 165-177. doi: 10.1016/j.ins.2016.03.001
    MENDEL J M. Type-2 fuzzy sets and systems[J]. IEEE Computational Intelligence Magazine, 2007, 2(1): 20-29. doi: 10.1109/MCI.2007.380672
    WU H, MENDEL J M. Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems[J]. IEEE Transactions on Fuzzy Systems, 2002, 10(5): 622-639. doi: 10.1109/TFUZZ.2002.803496
    胡怀中,张伟斌,杨华南. 区间型二型模糊集重心的直接Karnik-Mendel算法[J]. 系统仿真学报,2010,22(10): 2326-2328.

    HU Huaizhong, ZHANG Weibin, YANG Huanan. Dieect Karnik-Mendel algorithm in interval type-2 fuzzy system[J]. Journal of System Simulation, 2010, 22(10): 2326-2328.
    MAITY S, SIL J. Tuning of centroid with modified Keinik-Mendel (KM) algorithm[J]. International Journal of Modeling and Optimization, 2012, 2(6): 718-722.
    MENDEL J M, LIU X. New closed-form solution for Karnik-Mendel algorithm dezuzzification of an interval type-2 set[C]//IEEE International Conference on Fuzzy Systems. [S.l.]: IEEE, 2012: 1-8
    LIU X, QIN Y, WU L. Fast and direct Karnik-Mendel algorithm computation for the centroid of an interval type-2 fuzzy set[C]//IEEE International Conference on Fuzzy Systems. Brisbane: IEEE, 2012: 1058-1065
    KUMBASAR T. Revisiting KM algorithms: a linear progarmming approach[C]//IEEE International Conference on Fuzzy Systems. Istanbul: IEEE, 2015: 1-6
    DODURKA M F, KUMBASAR T, SAKALLI A, et al. Boundary function based Karnik-Mendel type reduction method for interval type-2 fuzzy PID controllers[C]//IEEE International Conference on Fuzzy Systems. Beijing: IEEE, 2014: 619-625
    SALAKEN S M, KHOSRAVI A, WU D R. Switch point finding using polynomial regression for fuzzy type reduction algorithms[C]//IEEE International Conference on Fuzzy Systems. Istanbul: IEEE, 2015: 45-50
    LIU X W. Extension of Karnik-Mendel algorithms with uncertainty bound method[C]//International Conference on System Science and Engineering. Dalian: IEEE, 2012: 459-464
    KHANESAR M A, KAYNAK O and GAO H J. Improved Karnik-Mendel algorithm: eliminating the need for sorting[C]//International Conference on Mechatronics and Control. Jinzhou: [s.n.], 2014: 204-209
    陈阳,王大志. 基于加权Karnik-Mendel算法的区间二型模糊逻辑系统降型[J]. 控制理论与应用,2016,33(10): 1327-1336.

    CHEN Yang, WANG Dazhi. Type-reduction of interval type-2 fuzzy logic systems with weighted Karnik-Mendel algorithms[J]. Control Theory and Applications, 2016, 33(10): 1327-1336.
    WU D, MENDEL J M. Enhanced Karnik-Mendel algorithms[J]. IEEE Transactions on Fuzzy Systems, 2009, 17(4): 923-934. doi: 10.1109/TFUZZ.2008.924329
    王建辉,纪雯,方晓柯,等. 对区间二型模糊集的EKM降型法的改进[J]. 控制与决策,2013,28(8): 1165-1172.

    WANG Jianhui, JI Wen, FANG Xiaoke, et al. Improvement of enhanced Karnik-Mendel algorithm for interval type-2 fuzzy sets[J]. Control and Decision, 2013, 28(8): 1165-1172.
    SALAKEN S M, KHOSRAVI A, WU D R. Effect of different initializations on EKM algorithm[C]//IEEE International Conference on Fuzzy Systems. Istanbul: IEEE, 2015: 1-6
    YEH C, JENG W, LEE S. An enhanced type-reduction algorithm for type-2 fuzzy sets[J]. IEEE Transactions on Fuzzy Systems, 2011, 19(2): 227-240. doi: 10.1109/TFUZZ.2010.2093148
    MELGAREJO M. A fast recursive method to compute the generalized centroid of an interval type-2 fuzzy set[C]//Proc. of Annual Conference of the North American Fuzzy Information Processing Society. San Diego: [s.n.], 2007: 190-194
    DURAN K, BERNAL H, MELGAREJO M. Improved iterative algorithm for computing the generalized centroid of an interval type-2 fuzzy set[C]//Annual Meeting of the North American Fuzzy Information Processing Society. New York: [s.n.], 2008: 1-5
    WU D. Approaches for reducing the computational cost of interval type-2 fuzzy logic systems:overview and comparisons[J]. IEEE Transactions on Fuzzy Systems, 2013, 21(1): 80-99. doi: 10.1109/TFUZZ.2012.2201728
    CHEN Y, WANG D. Studies on centroid type-reduction algorithms for interval type-2 fuzzy logic systems[C]//IEEE Fifth International Conference on Big Data and Cloud Computing. Dalian: IEEE, 2015: 344-349
    施建中,李荣,杨勇. 一种新的区间二型模糊集合降阶算法[J]. 计算机应用研究,2017,34(2): 378-381. doi: 10.3969/j.issn.1001-3695.2017.02.013

    SHI Jianzhong, LI Rong, YANG Yong. New interval type-2 fuzzy sets type reduction algorithm[J]. Application Research of Computers, 2017, 34(2): 378-381. doi: 10.3969/j.issn.1001-3695.2017.02.013
    WU D R, NIE M. Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems[C]//IEEE International Conference on Fuzzy Systems. Taipei: IEEE, 2011: 2131-2138
    HU H, WANG Y, CAI Y. Advantages of the enhanced opposite direction searching algorithm for computing the centroid of an interval type-2 fuzzy set[J]. Asian Journal of Control, 2012, 14(6): 1-9.
    LIU X W, ZHU Q, GUO S. Three new uncertainty bound methods of Karnik-Mendel algorithms[C]//IEEE International Conference on Fuzzy Systems, Monterey. [S.l.]: IEEE, 2013: 1-8
    ZARANDI M H F, TORSHIZI A D, TURKSEN I B, et al. A new indirect approach to the type-2 fuzzy systems modeling and design[J]. Information Sciences, 2013, 232(5): 346-365.
    JUANG C F, JUANG K J. Reduced interval type-2 neural fuzzy system using weighted bound-set boundary operation for computation speedup and chip implementation[J]. IEEE Transactions on Fuzzy Systems, 2013, 21(3): 477-491. doi: 10.1109/TFUZZ.2012.2230179
    NIE M, TAN W W. Towards an efficient type-reduction method for interval type-2 fuzzy logic systems[C]//IEEE International Conference on Fuzzy Systems. Hong Kong: IEEE, 2008: 1425-1432
    BEGIAN M, MELEK W, MENDEL J. Stability analysis of type-2 fuzzy systems[C]//IEEE International Conference on Fuzzy Systems. Hong Kong: IEEE, 2008: 947-953
    PEDRO P C, ARTURO M, ARTURO T V. Hardware type-2 fuzzy logic position controller based on Karnik-Mendel algorithms[J]. Journal of Control Science and Engineering, 2013, 7(1): 1-12.
    KHANESAR M A, MENDEL J M. Maclaurin series expansion complexity-reduced center of sets type-reduction+defuzzification for interval type-2 fuzzy systems[C]//IEEE International Conference on Fuzzy Systems. Vancouver: IEEE, 2016: 1224-1231
    KHOSRAVI A, NAHAVANDI S, KHOSRAVI R. Evaluation and comparison of type reduction algorithms from a forecast accuracy perspective[C]//IEEE International Conference on Fuzzy Systems. Hyderabad: IEEE, 2013: 1-7
    GORZALCZANY M. Decision making in signal transmission problems with interval-valued fuzzy sets[J]. Fuzzy Sets and Systems, 1987, 23(2): 191-203. doi: 10.1016/0165-0114(87)90058-3
    LIANG Q, MENDEL J M. Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters[J]. IEEE Transactions on Systems, 2000, 8(5): 551-563.
    WU D, TAN W W. Computationally efficient type-reduction strategies for a type-2 fuzzy logic controller[C]//IEEE International Conference on Fuzzy Systems. Reno: IEEE, 2005: 353-358
    LI C, YI J, ZHAO D. A novel type-reduction method for interval type-2 fuzzy logic systems[C]//International Conference on Fuzzy Systems and Knowledge Discovery. Jinan: [s.n.], 2008: 157-161
    DU X, YING H. Derivation and analysis of the analytical structures of the interval type-2 fuzzy PI and PD controllers[J]. IEEE Transactions on Fuzzy Systems, 2010, 18(4): 802-814. doi: 10.1109/TFUZZ.2010.2049022
    TAO C W, TAUR J S, CHANG C W, et al. Simplified type-2 fuzzy sliding controller for wing rock system[J]. Fuzzy Sets and Systems, 2012, 207(8): 111-129.
    GREENFIELD S, CHICLANA F, COUPLAND S, et al. The collapsing method of defuzzification for discretised interval type-2 fuzzy sets[J]. Information Sciences, 2009, 179(13): 2055-2069. doi: 10.1016/j.ins.2008.07.011
    WU D R. An overview of alternative type-reduction approaches for reducing the computational cost of interval type-2 fuzzy logic controllers[C]//IEEE World Congress on Computational Intelligence. Brisbane: IEEE, 2012: 1-8
    TORSHIZI A D, ZARANDI M H F, ZAKERI H. On type-reduction of type-2 fuzzy sets: a review[J]. Applied Soft Computing, 2015, 27: 614-627.
    LU T C. Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers[J]. Engineering Applications of Artificial Intelligence, 2015, 42: 36-44. doi: 10.1016/j.engappai.2015.02.012
    ZHAO X Z, GAO Y B, ZENG J F, et al. PSO type-reduction method for geometric interval type-2 fuzzy logic systems[J]. Journal of Harbin Institute of Technology (New Series), 2008, 15(6): 862-867.
    ULU C, GUZELKAYA M, EKSIN I. A dynamic defuzzication method for interval type-2 fuzzy logic controllers[C]//IEEE International Conference on Mechatronics. Istanbul: IEEE, 2011: 318-323
    LU T C, CHEN S L. A new type reduction method for type-2 fuzzy logic controller[C]//International Automatic Control Conference. Nantou: [s.n.], 2013: 334-338
    TAO C W, CHANG C W, TAUR J S. A simplify type reduction for interval type-2 fuzzy sliding controller[J]. International Journal of Fuzzy Systems, 2013, 15(4): 460-470.
    CHEN C L, CHEN S C, KUO Y H. The reduction of interval type-2 LR fuzzy sets[J]. IEEE Transactions on Fuzzy Systems, 2014, 22(4): 840-858. doi: 10.1109/TFUZZ.2013.2277729
    KHOSRAVI A, NAHAVANDI S. Load forecasting using interval type-2 fuzzy logic systems:optimal type reduction[J]. IEEE Transactions on Industrial Informatics, 2014, 10(2): 1055-1063. doi: 10.1109/TII.2013.2285650
    COUPLAND S, JOHN R I. An investigation into alternative methods for the defuzzification of an interval type-2 fuzzy set[C]//IEEE International Conference on Fuzzy Systems. Vancouver: IEEE, 2006: 1425-1432
    CHAO C C, HSIAO M Y, TSAI S H, et al. Design of an interval type-2 fuzzy immune controller[J]. Information Technology Journal, 2010, 9(6): 1115-1123. doi: 10.3923/itj.2010.1115.1123
    JOHN R I, COUPLAND S. Type-2 fuzzy logic:a historical view[J]. IEEE Computational Intelligence Magazine, 2007, 2(1): 57-62. doi: 10.1109/MCI.2007.357194
    GONZALEZ C, CASTRO J R, MELIN P, et al. An edge detection method based on generalized type-2 fuzzy logic[J]. Soft Computing, 2016, 20(2): 773-784. doi: 10.1007/s00500-014-1541-0
    GREENFIELD S. Type-2 fuzzy logic: circumventing the defuzzification bottleneck[D]. Leicester: De Montfort University, 2012
    LIU F. An efficient centroid type-reduction strategy for general type-2 fuzzy logic system[J]. Information Science, 2008, 178(9): 2224-2236.
    XIE B K, LEE S J. An extended type-reduction method for general type-2 fuzzy sets[J]. IEEE Transactions on Fuzzy Systems, 2015, 14(8): 1-10.
    WU H J, SU Y L, LEE S J. A fast method for computing the centroid of a type-2 fuzzy set[J]. IEEE Transactions on Systems,Man,and Cybernetics,Part B:Cybernetics, 2012, 42(3): 764-777. doi: 10.1109/TSMCB.2011.2177085
    WAGNER C, HAGRAS H. zSlices based general type-2 FLC for the control of autonomous mobile robots in real word environment[C]//IEEE International Conference on Fuzzy Systems. Jeju Island: IEEE, 2009: 718-725
    ZHAI D, MENDEL J. Comment toward general type-2 fuzzy logic systems based on zSlices[J]. IEEE Transactions on Fuzzy Systems, 2012, 20(5): 996-997. doi: 10.1109/TFUZZ.2012.2190076
    WAGNER C, HAGRAS H. Towards general type-2 fuzzy logic systems based on zSlices[J]. IEEE Transactions on Fuzzy Systems, 2010, 18(4): 637-660. doi: 10.1109/TFUZZ.2010.2045386
    ROBERT I. Perception modelling using type-2 fuzzy sets[D]. Leicester: De Montfort University, 2000
    LUCAS L, CENTENO T, DELGADO M. General type-2 fuzzy inference systems: analysis, design and computational aspects[C]//IEEE International Conference on Fuzzy Systems. London: IEEE, 2007: 1-6
    GREENFIELD S, CHICLANA F. Defuzzification of the discretised generalised type-2 fuzzy set:experimental evaluation[J]. Information Sciences, 2013, 244(7): 1-25.
    GREENELD S, JOHN R I. Fuzzy logic and computational geometry[C]//Proceedings of the International Conference on Recent Advances in Soft Computing. Leicester: IEEE, 2004: 3-8
    COUPLAND S, JOHN R I. Geometric type-2 sets[M]. New York: Springer, 2013: 81-96
    COUPLAND S, JOHN R I. New geometric inference techniques for type-2 fuzzy sets[J]. International Journal of Approximate Reasoning, 2008, 49(1): 198-211. doi: 10.1016/j.ijar.2008.03.001
    GREENFIELD S, CHICLANA F, JOHN R I. Type-reduction of the discretised interval type-2 fuzzy set[C]//IEEE International Conference on Fuzzy Systems. Jeju Island: IEEE, 2009: 738-743
    GREENFIELD S, JOHN R I, COUPLAND S. A novel sampling method for type-2 defuzzification[C]//Proceedings of UKCI 2005. London: IEEE, 2005: 120-127
    ZHAI D, MENDEL J. Centroid of a general type-2 fuzzy set computed by means of the centroid-flow algorithm[C]//IEEE International Conference on Fuzzy Systems. Barcelona: IEEE, 2010: 895-902
    GAFA C, COUPLAND S. A new recursive type-reduction procedure for general type-2 fuzzy sets[C]//IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems. Paris: IEEE, 2011: 44-49
    CHICLANA F, ZHOU S M. Type-reduction of general type-2 fuzzy sets:the tyep-1 OWA Approach[J]. International Journal of Intelligent Systems, 2013, 28(5): 505-522. doi: 10.1002/int.2013.28.issue-5
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出版历程
  • 收稿日期:  2017-01-19
  • 修回日期:  2018-04-04
  • 网络出版日期:  2018-04-23
  • 刊出日期:  2019-04-01

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