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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.
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.
This book provides recent advances in analysis and synthesis of
Large-scale network systems (LSNSs) with sampled-data communication
and non-identical nodes. In its first chapter of the book presents
an introduction to Synchronization of LSNSs and Algebraic Graph
Theory as well as an overview of recent developments of LSNSs with
sampled data control or output regulation control. The main text of
the book is organized into two main parts - Part I: LSNSs with
sampled-data communication and Part II: LSNSs with non-identical
nodes. This monograph provides up-to-date advances and some recent
developments in the analysis and synthesis issues for LSNSs with
sampled-data communication and non-identical nodes. It describes
the constructions of the adaptive reference generators in the first
stage and the robust regulators in the second stage. Examples are
presented to show the effectiveness of the proposed design
techniques.
This book discusses recent advances in the estimation and control
of networked systems with unacknowledged packet losses: systems
usually known as user-datagram-protocol-like. It presents both the
optimal and sub-optimal solutions in the form of algorithms, which
are designed to be implemented easily by computer routines. It also
provides MATLAB (R) routines for the key algorithms. It shows how
these methods and algorithms can solve estimation and control
problems effectively, and identifies potential research directions
and ideas to help readers grasp the field more easily. The novel
auxiliary estimator method, which is able to deal with estimators
that consist of exponentially increasing terms, is developed to
analyze the stability and convergence of the optimal estimator. The
book also explores the structure and solvability of the optimal
control, i.e. linear quadratic Gaussian control. It develops
various sub-optimal but efficient solutions for estimation and
control for industrial and practical applications, and analyzes
their stability and performance. This is a valuable resource for
researchers studying networked control systems, especially those
related to non-TCP-like networks. The practicality of the ideas
included makes it useful for engineers working with networked
control.
This book provides recent advances in analysis and synthesis of
Large-scale network systems (LSNSs) with sampled-data communication
and non-identical nodes. In its first chapter of the book presents
an introduction to Synchronization of LSNSs and Algebraic Graph
Theory as well as an overview of recent developments of LSNSs with
sampled data control or output regulation control. The main text of
the book is organized into two main parts - Part I: LSNSs with
sampled-data communication and Part II: LSNSs with non-identical
nodes. This monograph provides up-to-date advances and some recent
developments in the analysis and synthesis issues for LSNSs with
sampled-data communication and non-identical nodes. It describes
the constructions of the adaptive reference generators in the first
stage and the robust regulators in the second stage. Examples are
presented to show the effectiveness of the proposed design
techniques.
This book discusses recent advances in the estimation and control
of networked systems with unacknowledged packet losses: systems
usually known as user-datagram-protocol-like. It presents both the
optimal and sub-optimal solutions in the form of algorithms, which
are designed to be implemented easily by computer routines. It also
provides MATLAB (R) routines for the key algorithms. It shows how
these methods and algorithms can solve estimation and control
problems effectively, and identifies potential research directions
and ideas to help readers grasp the field more easily. The novel
auxiliary estimator method, which is able to deal with estimators
that consist of exponentially increasing terms, is developed to
analyze the stability and convergence of the optimal estimator. The
book also explores the structure and solvability of the optimal
control, i.e. linear quadratic Gaussian control. It develops
various sub-optimal but efficient solutions for estimation and
control for industrial and practical applications, and analyzes
their stability and performance. This is a valuable resource for
researchers studying networked control systems, especially those
related to non-TCP-like networks. The practicality of the ideas
included makes it useful for engineers working with networked
control.
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