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.
