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Stability and Stabilization of Linear and Fuzzy Time-Delay Systems - A Linear Matrix Inequality Approach (Hardcover, 1st ed. 2018)
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Stability and Stabilization of Linear and Fuzzy Time-Delay Systems - A Linear Matrix Inequality Approach (Hardcover, 1st ed. 2018)
Series: Intelligent Systems Reference Library, 141
Expected to ship within 10 - 15 working days
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This book provides a clear understanding in formulating stability
analysis and state feedback control of retarded time delay systems
using Lyapunov's second method in an LMI framework. The chapters
offer a clear overview of the evolution of stability analysis in
terms of the construction of a Lyapunov functional and use of the
integral inequalities in order to reduce the gap of delay upper
bound estimate compared to frequency domain method through existing
and proposed stability theorems. Power system engineering problem
has been presented here to give readers fair idea on applicability
of the model and method for solving engineering problems. Without
deviating from the framework of analysis more complex dynamics of
the system have been dealt with here that includes actuator
saturation and thereby ascertaining local stability for an
estimated time-delay and domain of attraction. Nonlinearity in a
time-delay system has been dealt with in the T-S fuzzy modeling
approach. This book is useful as a textbook for Master's students
and advanced researcher working in the field of control system
engineering, and for practicing engineers dealing with such complex
dynamical systems. The strengths of the book are lucidity of
presentation, lucidity of solution method, MATLAB programs given in
the appendix that help the novice researcher to carry out research
in this area independently, clear idea about the formulation of
desired stability and control problem in a LMI framework,
application problem provided can motivate students and researcher
to recast their problems in the similar framework easily, helpful
for readers to use the stability (stabilization) conditions or
formulate their own stability conditions easily for a complicated
linear or nonlinear dynamical system.
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