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Adaptive prediction and control of discrete‐time Takagi–Sugeno fuzzy systems
Author(s) -
Qi Ruiyun,
Tao Gang,
Tan Chang,
Yao Xuelian
Publication year - 2012
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2298
Subject(s) - control theory (sociology) , fuzzy control system , parametrization (atmospheric modeling) , adaptive control , fuzzy logic , parametric statistics , stability (learning theory) , basis (linear algebra) , computer science , discrete time and continuous time , adaptive neuro fuzzy inference system , bounding overwatch , property (philosophy) , mathematics , control (management) , artificial intelligence , physics , philosophy , statistics , geometry , epistemology , quantum mechanics , machine learning , radiative transfer
SUMMARY This paper derives a new prediction model of the global discrete‐time input‐output multiple‐delay Takagi–Sugeno (T‐S) fuzzy systems with multiple delays and employs it for adaptive fuzzy control in the presence of system parameter uncertainties. On the basis of a model‐based approach, a new system parametrization and adaptive control scheme are developed with detailed design procedure and complete stability analysis. The derived new fuzzy prediction model involves not only the current values of the membership functions but also their past values, expanding its capacity of approximating dynamic systems. A stable adaptive law is developed on the basis of an error model resulting from a new augmented parametric model for which a signal bounding property is also proved, crucial for closed‐loop system stability. An illustrative example is presented to demonstrate the studied new concepts and to verify the desired performance of the new types of adaptive fuzzy control systems. Copyright © 2012 John Wiley & Sons, Ltd.