On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models 论文

2000IEEE Transactions on Fuzzy Systems引用 333
Fault Detection and Control SystemsFuzzy Logic and Control SystemsControl Systems and Identification

详细信息

发表期刊/会议
IEEE Transactions on Fuzzy Systems
发表日期
2000-06-01
发表年份
2000

关键词

Fault Detection and Control SystemsFuzzy Logic and Control SystemsControl Systems and Identification

摘要

Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identified from experimental data. It is shown that there exists a close relationship between dynamic Takagi-Sugeno fuzzy models and dynamic linearization when using affine local model structures, which suggests that a solution to the multiobjective identification problem exists. However, it is also shown that the affine local model structure is a highly sensitive parametrization when applied in transient operating regimes. Due to the multiobjective nature of the identification problem studied here, special considerations must be made during model structure selection, experiment design, and identification in order to meet both objectives. Some guidelines for experiment design are suggested and some robust nonlinear identification algorithms are studied. These include constrained and regularized identification and locally weighted identification. Their usefulness in the present context is illustrated by examples.