An improved general type-2 fuzzy sets type reduction and its application in general type-2 fuzzy controller design

被引:0
|
作者
Shi Jianzhong
Liang Shaohua
Yang Yong
Li Rong
机构
[1] Nanjing Institute of Technology,School of Energy and Power Engineering
来源
Soft Computing | 2019年 / 23卷
关键词
Interval type-2 fuzzy logic; General type-2 fuzzy logic; plane; Type reduction; KM/EKM; Trough solar;
D O I
暂无
中图分类号
学科分类号
摘要
The Karnik–Mendel (KM) or the enhanced Karnik–Mendel (EKM) algorithm is widely used for interval type-2 fuzzy sets type reduction in many applications. Compared with iterative procedures of KM/EKM, an iterative algorithm with a stop condition or an enhanced iterative algorithm with a stop condition based on the KM algorithm that converges monotonically is more efficient. In this article, a new iterative algorithm with stop condition type reduction for interval type-2 fuzzy sets is proposed, in which switch points are initialized and unidirectional search is performed based on monotone properties of the KM algorithm. Furthermore, the proposed algorithm is applied to general type-2 fuzzy sets type reduction based on α-plane representation. The experimental results of a triangular and gaussian secondary membership function show practicality and efficiency of this method. In accordance with the conventional PI, type-1 or interval type-2 fuzzy controller is difficult to achieve a desired control effect for steam temperature at collector outlet of trough solar thermal power generation system with large time delay, strong inertia and parameter time-variation, and a general type-2 fuzzy controller with more adjustable controller parameters is proposed in this article. In different working conditions, the proposed controller can reduce system overshoot and ensure system stability. Moreover, when the working condition changes, the controller can solve a model mismatch problem under same controller parameters and has faster response.
引用
收藏
页码:13513 / 13530
页数:17
相关论文
共 50 条
  • [1] An improved general type-2 fuzzy sets type reduction and its application in general type-2 fuzzy controller design
    Shi Jianzhong
    Liang Shaohua
    Yang Yong
    Li Rong
    [J]. SOFT COMPUTING, 2019, 23 (24) : 13513 - 13530
  • [2] An improved type-reduction algorithm for general type-2 fuzzy sets
    Wu, Li
    Qian, Fucai
    Wang, Lingzhi
    Ma, Xuehui
    [J]. INFORMATION SCIENCES, 2022, 593 : 99 - 120
  • [3] Extending Similarity Measures of Interval Type-2 Fuzzy Sets to General Type-2 Fuzzy Sets
    McCulloch, Josie
    Wagner, Christian
    Aickelin, Uwe
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013), 2013,
  • [4] Short Remark on Fuzzy Sets, Interval Type-2 Fuzzy Sets, General Type-2 Fuzzy Sets and Intuitionistic Fuzzy Sets
    Castillo, Oscar
    Melin, Patricia
    Tsvetkov, Radoslav
    Atanassov, Krassimir T.
    [J]. INTELLIGENT SYSTEMS'2014, VOL 1: MATHEMATICAL FOUNDATIONS, THEORY, ANALYSES, 2015, 322 : 183 - 190
  • [6] The Construction of general Type-2 Fuzzy Sets
    Hu, Dan
    Lin, Tsau Young
    Fan, Qiang
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC), 2013, : 141 - 146
  • [7] Representation for general type-2 fuzzy sets
    Mo, Hong
    Wang, F-Y
    [J]. 2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION, CYBERNETICS AND COMPUTATIONAL SOCIAL SYSTEMS (ICCSS), 2017, : 389 - 394
  • [8] An Extended Type-Reduction Method for General Type-2 Fuzzy Sets
    Xie, Bing-Kun
    Lee, Shie-Jue
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2017, 25 (03) : 715 - 724
  • [10] On Type-2 Fuzzy Sets and Type-2 Fuzzy Systems
    Shvedov A.S.
    [J]. Journal of Mathematical Sciences, 2021, 259 (3) : 376 - 384