The main objective of this “Fuzzy logic” white paper is about the role of Fuzzy logic as a speed control tool for DC motors and also about its implementations.
Fuzzy logic is a powerful problem solving methodology and mathematically it is a superset of Boolean or Crisp logic. Fuzzy logic has developed based on fuzzy set theory. In various control parameters like maximum overshoot and settling time for the DC motor control fuzzy logic has its own improvements when compared to PID control strategy.
Fuzzy logic control (FLC) technique has become an effective area in industrial processes applications research.
Design of Fuzzy controller:
Fuzzy logic design includes the following four principal components:
- Fuzzification interface: Fuzzification converts the input data namely error, e(t) and change in error, ce(t) into suitable linguistic variables.
- Knowledge base: Knowledge base consists of database and rule base. Linguistic control rules has been defined by the definitions, which are provided by the Data base. Control surfaces behavior is defined by the rules that tie together the fuzzy variables, these rules are in form of rule base matrix.
- Decision making logic: This logic infers a system of rules through the fuzzy operators namely ‘AND’ and ‘OR’ and generates a single truth value determined by inferred fuzzy control action).
- Defuzzification interface: The center of area method is used as the defuzzification strategy which yields a crispy, non-fuzzy control action from an inferred fuzzy control.
D.C. Motor Using Fuzzy Logic Control Technique In Real Time:
The FLC scheme has 7 quantization levels and 21 rules, which implemented on DC motors. FLC performs well than PID controller. In FLC, the response settled quickly without any oscillations.
This paper discussed about the FLC control as an effective speed control for DC motors when compared to PID controllers.
Download Fuzzy Logic Seminar Report.