Fuzzy logic control (FLC) has proven to be a popular control
methodology for many complex systems in industry, and is often used
with great success as an alternative to conventional control
techniques. However, because it is fundamentally model free,
conventional FLC suffers from a lack of tools for systematic
stability analysis and controller design. To address this problem,
many model-based fuzzy control approaches have been developed, with
the fuzzy dynamic model or the Takagi and Sugeno (T S) fuzzy
model-based approaches receiving the greatest attention.
Analysis and Synthesis of Fuzzy Control Systems: A Model-Based
Approach offers a unique reference devoted to the systematic
analysis and synthesis of model-based fuzzy control systems. After
giving a brief review of the varieties of FLC, including the T S
fuzzy model-based control, it fully explains the fundamental
concepts of fuzzy sets, fuzzy logic, and fuzzy systems. This
enables the book to be self-contained and provides a basis for
later chapters, which cover:
- T S fuzzy modeling and identification via nonlinear models or
data
- Stability analysis of T S fuzzy systems
- Stabilization controller synthesis as well as robust H and
observer and output feedback controller synthesis
- Robust controller synthesis of uncertain T S fuzzy systems
- Time-delay T S fuzzy systems
- Fuzzy model predictive control
- Robust fuzzy filtering
- Adaptive control of T S fuzzy systems
A reference for scientists and engineers in systems and control,
the book also serves the needs of graduate students exploring fuzzy
logic control. It readily demonstrates that conventional control
technology and fuzzy logic control can be elegantly combined and
further developed so that disadvantages of conventional FLC can be
avoided and the horizon of conventional control technology greatly
extended. Many chapters feature application simulation examples and
practical numerical examples based on MATLAB(r).
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