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Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number (Hardcover)
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Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number (Hardcover)
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An original, systematic-solution approach to uncertain nonlinear
systems control and modeling using fuzzy equations and fuzzy
differential equations There are various numerical and analytical
approaches to the modeling and control of uncertain nonlinear
systems. Fuzzy logic theory is an increasingly popular method used
to solve inconvenience problems in nonlinear modeling. Modeling and
Control of Uncertain Nonlinear Systems with Fuzzy Equations and
Z-Number presents a structured approach to the control and modeling
of uncertain nonlinear systems in industry using fuzzy equations
and fuzzy differential equations. The first major work to explore
methods based on neural networks and Bernstein neural networks,
this innovative volume provides a framework for control and
modeling of uncertain nonlinear systems with applications to
industry. Readers learn how to use fuzzy techniques to solve
scientific and engineering problems and understand intelligent
control design and applications. The text assembles the results of
four years of research on control of uncertain nonlinear systems
with dual fuzzy equations, fuzzy modeling for uncertain nonlinear
systems with fuzzy equations, the numerical solution of fuzzy
equations with Z-numbers, and the numerical solution of fuzzy
differential equations with Z-numbers. Using clear and accessible
language to explain concepts and principles applicable to
real-world scenarios, this book: Presents the modeling and control
of uncertain nonlinear systems with fuzzy equations and fuzzy
differential equations Includes an overview of uncertain nonlinear
systems for non-specialists Teaches readers to use simulation,
modeling and verification skills valuable for scientific research
and engineering systems development Reinforces comprehension with
illustrations, tables, examples, and simulations Modeling and
Control of Uncertain Nonlinear Systems with Fuzzy Equations and
Z-Number is suitable as a textbook for advanced students, academic
and industrial researchers, and practitioners in fields of systems
engineering, learning control systems, neural networks,
computational intelligence, and fuzzy logic control.
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