Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems [electronic resource] / by Hongyi Li, Ligang Wu, Hak-Keung Lam, Yabin Gao.

By:

Li, Hongyi [author.]

Contributor(s):

Publisher: Singapore : Springer Singapore : Imprint: Springer, 2016Edition: 1st ed. 2016Description: XIX, 257 p. 60 illus., 55 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9789811005930

Subject(s):

Genre/Form:

Electronic books.

Additional physical formats: Printed edition:: No titleDDC classification:

006.3 23

LOC classification:

Q342

Online resources:

Click here to access online

Contents:

Introduction -- Stability and Stabilization of CTIT2FMBSs -- Output-feedback Control of CTIT2FMBSs -- Sampled-Data Control of CTIT2FMBSs -- Output Tracking Control of CTIT2FSs -- Switched Output-feedback Control of CTIT2FMBSs -- Filter Design of CTIT2FMBSs -- Fault Detection of CTIT2FMBSs -- Model Reduction of CTIT2FMBSs -- Optimal Control of DTIT2FMBSs -- State-feedback Control of DTIT2FMBSs -- Static Output-feedback Control of DTIT2FMBSs -- Guaranteed Cost Output Tracking Control of DTIT2FMBSs.

In: Springer eBooksSummary: This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances. It also provides numerous simulation results for various examples, which fill certain gaps in this area of research and may serve as benchmark solutions for the readers. Interval type-2 T-S fuzzy models provide a convenient and flexible method for analysis and synthesis of complex nonlinear systems with uncertainties.

Item type:

eBooks

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This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances. It also provides numerous simulation results for various examples, which fill certain gaps in this area of research and may serve as benchmark solutions for the readers. Interval type-2 T-S fuzzy models provide a convenient and flexible method for analysis and synthesis of complex nonlinear systems with uncertainties.