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A Design of Observers of Control State and Uncertainty via Transformation of T-S Fuzzy Models
Author(s) -
Hugang Han,
Yuki Sueyama,
Chunjun Chen
Publication year - 2018
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2018.p0194
Subject(s) - computer science , observer (physics) , control theory (sociology) , fuzzy logic , fuzzy control system , transformation (genetics) , state (computer science) , controller (irrigation) , state observer , artificial intelligence , control (management) , algorithm , nonlinear system , biochemistry , chemistry , physics , quantum mechanics , biology , agronomy , gene
When employing the widely used T-S fuzzy model as a model to represent a system concerned with controller designs, it is necessary to consider the precision of the model from the point of view of control performance. Adding a term called uncertainty in the T-S fuzzy model to compensate for the difference between the concerned system and its T-S fuzzy model, this paper focuses on a design of observers for both the control state and uncertainty. Unlike a state observer in the traditional sense, which is usually designed as a whole, the state is divided into two parts by performing a unique matrix transformation; and two observers from the two divided parts of the state are designed separately in order to eliminate the influence of the uncertainty. Finally, an observer of the aforementioned uncertainty based on one of the state observers is suggested.

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