Analysis and Design of Monotonic Type-2 Fuzzy Inference Systems

被引：20
作者：
Li, Chengdong [1 ]
Yi, Jianqiang [1 ]
Zhao, Dongbin [1 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3 | 2009年
关键词：
LOGIC SYSTEMS; MODELS; UNCERTAINTY; SETS;
D O I：
10.1109/FUZZY.2009.5277084
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The prior knowledge - monotonicity property is helpful for system analysis, modeling and design, especially when no specific physical structure knowledge about systems is available. This paper presents how to use interval type-2 fuzzy logic systems (IT2FLSs) to incorporate the monotonicity property into system design. First, we present sufficient conditions on the parameters of IT2FLSs to ensure the monotonicity between the inputs and outputs of IT2FLSs. Then, we transform the design of monotonic IT2FLSs to the least squares problem with linear-inequality constraints. At last, simulations are given to show the usefulness of the monotonicity property and the advantages of monotonic IT2FLSs under noisy circumstances.
引用
收藏
页码：1193 / 1198
页数：6
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