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Control and Filtering of Fuzzy Systems with Switched Parameters (Hardcover, 1st ed. 2020)
Loot Price: R2,800
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Control and Filtering of Fuzzy Systems with Switched Parameters (Hardcover, 1st ed. 2020)
Series: Studies in Systems, Decision and Control, 268
Expected to ship within 10 - 15 working days
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This book presents recent advances in control and filter design for
Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks
to its powerful ability in transforming complicated nonlinear
systems into a set of linear subsystems, the T-S fuzzy model has
received considerable attention from those the field of control
science and engineering. Typical applications of T-S fuzzy systems
include communication networks, and mechanical and power
electronics systems. Practical systems often experience abrupt
variations in their parameters or structures due to outside
disturbances or component failures, and random switching mechanisms
have been used to model these stochastic changes, such as the
Markov jump principle. There are three general types of
controller/filter for fuzzy Markov jump systems: mode-independent,
mode-dependent and asynchronous. Mode-independence does not focus
on whether modes are accessible and ignores partially useful mode
information, which results in some conservatism. The mode-dependent
design approach relies on timely, complete and correct information
regarding the mode of the studied plant. Factors like component
failures and data dropouts often make it difficult to obtain exact
mode messages, which further make the mode-dependent
controllers/filters less useful. Recently, to overcome these
issues, researchers have focused on asynchronous techniques.
Asynchronous modes are accessed by observing the original systems
based on certain probabilities. The book investigates the problems
associated with controller/filter design for all three types. It
also considers various networked constraints, such as data dropouts
and time delays, and analyzes the performances of the systems based
on Lyapunov function and matrix inequality techniques, including
the stochastic stability, dissipativity, and $H_\infty$. The book
not only shows how these approaches solve the control and filtering
problems effectively, but also offers potential meaningful research
directions and ideas. Covering a variety of fields, including
continuous-time and discrete-time Markov processes, fuzzy systems,
robust control, and filter design problems, the book is primarily
intended for researchers in system and control theory, and is also
a valuable reference resource for graduate and undergraduate
students. Further, it provides cases of fuzzy control problems that
are of interest to scientists, engineers and researchers in the
field of intelligent control. Lastly it is useful for advanced
courses focusing on fuzzy modeling, analysis, and control.
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