Fuzzy logic is a methodology for operational states of a system with the expression of language, rather than mathematical equations. In other words, fuzzy logic-based control system is an expert system that utilizes fuzzy logic algorithm to manipulate qualitative variables. Many systems are too complex to be accurately modeled, albeit with a complex mathematical equation. In such a case, the expression language used in the fuzzy logic can help define the operational characteristics of the system better. Expression language for the characteristics of the system are usually expressed in the form of logical implications, such as the rule IF - THEN :
IF room_temperature WARM, THEN fan_speed MEDIUM
MEDIUM and WARM in this example above are the actual expression of the values' set which is known as as a membership function.
By choosing a range of values and not the values explicitly to
define the input variables "room_temperature", can be controlled
output variable "fan_speed" is more accurate. Fuzzy logic controllers can improve the performance of the control system to suppress the
emergence of the functions of the wild fluctuations in output caused by
the input variables [1].
Conventional approaches
To illustrate the differences between fuzzy logic approach to
conventional approaches, the following examples of issues discussed in a
control system. Suppose, for the following logic statement will explain how the controllers 'firm' handle.
- IF room_temperature > = 70_Fahrenheit, THEN set fan_speed on "1000 rpm"
IF room_temperature <70_Fahrenheit, THEN set fan_speed on "100 rpm"
In the conventional control system - which is often referred to as
'firm control' -, the controller relies on the decision points on the
basis of firm values. In this system, the input must reach a certain definite value before the control system to react in a certain way. Even very small variations in the input values can cause output to react very differently. For example, if the room temperature reaches 70 ° F or more, then use the first rule that the fan speed is set at 1000 rpm. If the temperature changes very small to below 70 ° F, then apply the second rule i.e. fan speed set at 100 rpm. In chart form, controlling the firm value is shown in Figure 1 below:
What happens when the temperature being 69.5 ° F? Or, more-over, what would happen to the system controller when the temperature changes from a value of 70 ° F above 70 ° F? Maybe the temperature fluctuates between slightly above or below 70 ° F (i.e. between 69.0 ° F to 71.0 ° F)?
Firmly on the control system, this incident will cause the fan rotation
varies wildly responds to changes in input variables
room_temperature, despite the fact that the temperature change is not
so pronounced.
Small fluctuations in the input as cases that are very difficult to
describe addressed by control 'firm', as this is contrary to the
condition of fuzzy logic shows its advantages [1].
Fuzzy Logic Approach
Designing
a fuzzy logic system is different from conventional coding. As
mentioned before, within conventional logic, terms can be only "true"
or "false", "low" or "High", or "On" of "Off". Fuzzy logic allows a generalization of
conventional logic. It provides for terms between "true"
and "false" like "almost true" or "partially
false". Therefore, fuzzy logic cannot be directly processed on
computers but must be emulated by special code [2].
Reference:
Reference:
- www.elektroindonesia.com
- www.fuzzytech.com
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