02-01-2013, 03:40 PM
Fuzzy Logic in Electrical Systems
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ABSTRACT
With the advent of modern computer technology, the field of Artificial Intelligence is showing a definite utility in all spectrum of life. In the field of control, there is always a need for optimality with improved controller performance. In this paper, the feasibility of Fuzzy Logic as an effective control tool for DC motors is dealt with.
The Fuzzy Logic Controller (FLC) is showing a better performance than conventional controllers in the form of increased robustness.
In this paper, the role of Fuzzy Logic as a controller and its implementation is studied.
INTRODUCTION:
• Fuzzy logic is a powerful problem solving methodology introduced by Lotfi Zadeh in 1960’s.
• It provides tools for dealing with imprecision due to uncertainty and vagueness, which is intrinsic to many engineering problems.
• It is a superset of Boolean or Crisp logic.
• It emerged into mainstream of information technology in late 1980’s and early 1990
FUZZY LOGIC:
• Fuzzy logic resembles human decision making with its ability to work from approximate data and find precise solutions.
• Classical logic or Boolean logic has two values or states. Eg. (true or false). It requires a deep understanding of a system, exact equations, and precise numeric values.
• Fuzzy logic is a continuous form of logic. eg (bad, very bad, poor, average). It allows modeling complex systems using a higher level of abstraction originating from our knowledge and experience.
WORKING OF FUZZY LOGIC:
• The working of fuzzy logic can be understood by considering a simplified example of a thermostat controlling a heater fan.
• The room temperature detected through a sensor is input to a controller, which outputs a control force to adjust the heater fan speed.
• The first step in designing such a fuzzy controller is to characterize the range of values for the input and output variables of the controller.
• Labels such as cool for the temperature and high for the fan speed are assigned and a set of simple English-like rules to control the systems are written.
FUZZIFICATION:
Fuzzification converts the input data namely error, e(t) and change in error, ce(t) into suitable linguistic variables.
A scale mapping is performed using triangular membership function, which transfers the range of input variables into corresponding universe of discourse.
KNOWLEDGE BASE:
Knowledge base consists of database and rule base.
Data base provides necessary definitions that are used to define linguistic control rules with a syntax, such as: IF < fuzzy proportion > THEN < fuzzy proportion >
The 'IF' part is called the 'antecedent' and the 'THEN' part is called the 'consequent'.
In control applications the antecedents are 'error' and 'change in error' and the consequent is the 'control command'.
DECISION MAKING LOGIC:
Decision making logic infers a system of rules through the fuzzy operators namely 'AND' and 'OR' and generates a single truth value which determines the outcome of rules (inferred fuzzy control action).
DEFUZZIFICATION:
Defuzzification yields a crisp, non-fuzzy control action from an inferred fuzzy control action.
In the present work, the center of area method is used as the defuzzification strategy.
OPEN LOOP INVESTIGATION:
The d.c. motor being controlled, is a 12V, 1.5amp, 20 watts armature controlled permanent magnet motor.
The motor has a maximum speed of 2500 rpm and drives an output shaft with a 9:1 reduction, achieved through two stages of belt drive.
CONCLUSION
The present work brings out the potential advantages of applying FLC technique for speed control of d.c. motor.
The FLC performance has good set-point tracking.
Moreover, because of their reliance on rules based on expert knowledge, they provide their environment, a higher machine intelligent quotient.
The center of area method takes the center of gravity of final fuzzy space and produces a result that is sensitive to all the rules in particular.
The results tend to move smoothly across the control surface.
The comparison of closed loop performance of both the schemes show the superiority of FLC scheme over PID control.
FLC can therefore be an effective control strategy for the speed control of d.c. motor.