A review of neuro-fuzzy systems based on intelligent control
  The system's ability to adapt and self-organize are two key factors when it
comes to how well the system can survive the changes to the environment and the
plant they work within. Intelligent control improves these two factors in
controllers. Considering the increasing complexity of dynamic systems along
with their need for feedback controls, using more complicated controls has
become necessary and intelligent control can be a suitable response to this
necessity. This paper briefly describes the structure of intelligent control
and provides a review on fuzzy logic and neural networks which are some of the
base methods for intelligent control. The different aspects of these two
methods are then compared together and an example of a combined method is
presented.
