\caption{Process of a fuzzy control. The most used method for defuzzification is \textit{center of gravity} (centroid).}
\end{figure}
\end{frame}
\begin{frame}{Fuzzy Control Applications \cite{ross2009fuzzy}}
\begin{frame}{Fuzzy Control Applications}
\begin{itemize}
\item Camera autofocus by Canon
\item Increased effectivity of Mutsushita vacuum robots
@ -281,12 +288,72 @@
\end{itemize}
\vskip .5cm
The fuzzy control systems are commonly used where there are not enough resources for highly advanced systems like \textbf{PID\footnote{Proportional-integral-derivative} controller}, \textbf{Artificial neural network} or \textbf{Genetic algorithm}\cite{rajasekaran2003neural}.
The fuzzy control systems are commonly used \cite{ross2009fuzzy} where there are not enough resources for highly advanced systems like \textbf{PID\footnote{Proportional-integral-derivative} controller}, \textbf{Artificial neural network} or \textbf{Genetic algorithm}\cite{rajasekaran2003neural}.
\end{frame}
\subsection{Software}
\begin{frame}{MATLAB Fuzzy Toolbox Introduction}
\begin{itemize}
\item Provides a complete set of functions to design an implement various fuzzy logic processes \cite{sivanandam2006introduction}
\item Major fuzzy logic operation-fuzzification, defuzzification, and the fuzzy inference
\item Can be implemented using the Graphical User Interface (GUI)
\end{itemize}
\end{frame}
\begin{frame}{MATLAB Fuzzy Toolbox}
Features:
\begin{itemize}
\item It provides tools to create and edit fuzzy inference system (FIS).
\item Allows integrating fuzzy systems into simulation with Simulink.
\item It is possible to create stand-alone C programs that call on fuzzy systems