### Fuzzy logic:

Fuzzy control logic is all about this relative importance of precision in presence of complexity and ambiguity. A closed mathematical expression can provide accurate descriptions of a system with little complexity (and, therefore, little uncertainty). But for more complex systems where there are few numerical data and where only ambiguous or imprecise information may be available, fuzzy reasoning can provide a way to understand the behaviour of the system by allowing us to interpolate approximately between observed entry and exit situations.

Fuzzy logic seems to be most successful in two kinds of situations:

- very complex models where understanding is strictly limited or, in fact, quite judgmental, and
- processes where human reasoning, human perception, or human decision making are inextricably involved

The controller consists of the following three parts:

• Fuzzifier

• Inference network

• Defuzzifier

Instead of giving a lot of mathematical functions and logic here, in fuzzy logic we give set of rules and data. A collection of such rules will provide the definition of a nonlinear transition function, without the need for defining each entry of the table individually, and without the knowledge of closed form representation of that function.

### When to Use Fuzzy Control?

- If there already exists a good PID controller where system performance, development and maintenance costs, as well as marketing policy, are satisfactory, it should be retained.
- If there exists a successful fuzzy controller to a problem similar to the one at hand, the chance is that fuzzy controller may click for the present case too.
- If there is adequate knowledge about the system or process that could be used to improve the solution but is difficult to code in terms of conventional control, such as differential equations and PID parameters, fuzzy control can be attempted.

### Advantages of Fuzzy Controller:

- Fuzzy Control provides higher level of automation by incorporating expert knowledge.
- Fuzzy controller provides Robust nonlinear control
- Fuzzy controller needs reduced development and maintenance time.
- Reduce development cost
- Simple programming