DocumentCode
3601573
Title
Relative Degrees and Adaptive Feedback Linearization Control of T–S Fuzzy Systems
Author
Yanjun Zhang ; Gang Tao ; Mou Chen
Author_Institution
Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Volume
23
Issue
6
fYear
2015
Firstpage
2215
Lastpage
2230
Abstract
This paper presents a new study on the relative degrees of single-input and single-output T-S fuzzy systems in general noncanonical forms, and proposes a feedback linearization-based control design method for such systems. The study extends the system relative degree concepts, commonly used for the control of nonlinear systems, to general T-S fuzzy systems, derives various relative degree conditions for general T-S fuzzy systems, and establishes the relative degree dependent normal forms. A feedback linearization-based control design framework is developed for general T-S fuzzy systems using its normal form, to achieve closed-loop stability and asymptotic output tracking under relaxed design conditions. A new adaptive feedback linearization-based control scheme for T-S fuzzy systems in general noncanonical forms with parameter uncertainties is designed and analyzed. Some extensions of relative degrees and their possible application to robust adaptive control for noncanonical form T-S fuzzy systems are also demonstrated. An illustrative example is presented with simulation results to demonstrate the control system design procedure and to show the effectiveness of the proposed control scheme.
Keywords
adaptive control; closed loop systems; control system synthesis; feedback; fuzzy control; linearisation techniques; multivariable control systems; robust control; T-S fuzzy systems; adaptive feedback linearization control; asymptotic output tracking; closed-loop stability; feedback linearization-based control system design; noncanonical form T-S fuzzy system; relative degree conditions; relaxed design conditions; robust adaptive control; single-input single-output T-S fuzzy system; Adaptation models; Adaptive systems; Approximation methods; Bismuth; Control systems; Fuzzy systems; Nonlinear systems; Feedback linearization; T-S fuzzy systems.; T???S fuzzy systems; normal form; output tracking; relative degree;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2015.2412138
Filename
7058407
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